April 2014
Talent Development & Excellence
Guest Editors: Hans Gruber & Heidrun Stoeger
Official Journal of the
Editor-in-Chief: Albert Ziegler Associate Editors: Bettina Harder Jiannong Shi
Wilma Vialle This journal Talent Development and Excellence is the official scholarly peer reviewed journal of the International Research Association for Talent Development and Excellence (IRATDE). The articles contain original research or theory on talent development, expertise, innovation, or excellence. The Journal is currently published twice annually. All published articles are assessed by a blind refereeing process and reviewed by at least two independent referees. Editor-in-Chief is Prof. Albert Ziegler, University of Erlangen- Nuremberg, Germany. Manuscripts can be submitted electronically to [email protected].
Editor-in-Chief: Albert Ziegler, University of Erlangen-Nuremberg, Germany
Associate Editors: Bettina Harder, University of Erlangen-Nuremberg, Germany Jiannong Shi, Academy of Sciences, Beijng, China Wilma, Vialle, University of Wollongong, Australia
International Advisory Board: Ai-Girl Tan, Nanyang Technological University, Singapore Barbara Schober, University of Vienna, Austria Carmen M. Cretu, University of IASI, Romania Elena Grigorenko, Yale University, USA Hans Gruber, University of Regensburg, Germany Ivan Ferbežer, University of Ljubljana, Slovenia Javier Tourón, University of Navarra, Spain Mantak Yuen, University of Hong Kong, P.R. China Marion Porath, University of British Columbia, Canada Osamah Maajeeni, King Abdul Aziz University, Saudi- Arabia Peter Merrotsy, University of New England, Australia Petri Nokelainen, University of Tampere, Finland Robert Sternberg, Tufts University, USA Wilma Vialle, University of Wollongong, Australia Wolfgang Schneider, University of Würzburg, Germany
Impressum: V.i.S.d.P.: Albert Ziegler, St.Veit-Str. 25, 81673 München, Germany
Talent Development & Excellence Volume 6 Number 1 2014
Contents
Special Issue – Guest-Editors: H. Gruber and H. Stoeger
Cultures of Expertise: The Social Definition of Individual Excellence 1 H. Stoeger and H. Gruber
How Does Collaborative Authoring in Doctoral Programs Socially Shape Practices of 11 Academic Excellence? K. Hakkarainen, K. Hytönen, K. Lonka, and J. Makkonen
Experts in Science: Visibility in Research Communities 31 M. Rehrl, T. Palonen, E. Lehtinen, and H. Gruber
Brain Cancer, Meat Glue, and Shifting Models of Outstanding Human Behavior: Smart 47 Contexts for the 21st Century J. McWilliams and J. A. Plucker
“Persons in the Shadow” Brought to Light: Parents, Teachers, and Mentors – How 57 Guidance Works in the Acquisition of Musical Skills A. C. Lehmann and F. Kristensen
The Organisational Embedding Of Expertise: Centres of Excellence 71 H. A. Mieg
Technology and Social Interaction: Notes on the Achievement of Authoritative 95 Knowledge in Complex Settings B. Jordan
Talent Development & Excellence Cultures of Expertise 1 Vol. 6, No. 1, 2014, 1–10 Cultures of Expertise: The Social Definition of Individual Excellence Heidrun Stoeger1* and Hans Gruber1
Abstract: The development of research on excellence is outlined. It is argued that a focus on the heredity of excellence, which marked the beginnings of scientific research into excellence and then prevailed for a long time, fails to explain many important issues. Social mechanisms underlying the growth and acquisition of individual excellence are classified in terms of clusters of excellence at different levels (cultures, families, geographical clusters, groups, excellent organizations). Misconceptions about the emergence of clusters of excellence and about individual expertise are analyzed. It is reviewed how the contributions to this special issues help to overcome these misconceptions.
Keywords: Clusters of excellence, Cultures of expertise, Individual expertise, Social definition of excellence
The Individual as the First and Principal Object of Inquiry in Excellence Research Excellence research got off to a bad start. The pioneer of excellence research, Francis Galton, was interested in the heredity of intelligence and talents. In Hereditary genius (1869), Galton attempted to substantiate his assumption about the inherited nature of excellence using a method known as historiometry. Galton’s 1874 book English men of science: Their nature and nurture ranks as the first empirical study in the field of excellence research. Using his historiometric approach, Galton designed a questionnaire and sent it to 190 fellows of the Royal Society. He wanted to find out about the social and ethnic backgrounds of their families. He was interested, for instance, in the fellows’ respective order of birth among their siblings. Galton’s larger concern was to understand the relationship between nature and nurture in the development of excellence. Galton was, in fact, the person who coined the term ‘nature and nurture’ that later became a catchphrase common in developmental psychology and educational science. While Galton’s work produced interesting results, in particular with respect to questions of the sociology of science, its implications were also quite limited. His notion that excellence was a condition resulting almost exclusively from individuals and their heritable traits sent generations of researchers down the wrong heuristic path. According to today’s terminology, Galton would qualify as an expertise researcher in that he studied individuals with long track records of exceptional achievement (Posner, 1988). Giftedness research complements this line of inquiry, and early giftedness researchers also accepted Galton’s assumption by focusing on identifying individuals (usually children and adolescents) whom they suspected had an innate potential for excellence. The leading early representative of this line of inquiry is Lewis M. Terman, who established empirical giftedness research about 50 years after Galton published his seminal works. Using his so-called contrastive approach, Terman set out to compare “bright boys” with “stupid boys,” as he put it (Terman, 1906). In 1921, Terman started what
1 Institute of Educational Science, University of Regensburg, Germany *Corresponding author. University of Regensburg, Institute of Educational Science, D-93040 Regensburg, Germany. Email: [email protected]
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
2 H. Stoeger & H. Gruber was to become the most renowned longitudinal study in the history of giftedness research. The study, known as “The genetic studies of genius,” was originally documented in five publications (Cox, 1926; Terman, 1926, 1930; Terman & Oden, 1947, 1959) and qualifies as the longest-running longitudinal study ever. The data Terman chose to collect reflect his acceptance of Galton’s assumption that inherent personal traits explain excellence or its lack thereof. Terman viewed IQ as the truest measure of giftedness. He also assumed that various measures of personality traits and interests would reflect inherent traits. For Terman, other variables such as family interests were only indirectly relevant. They might impede or facilitate the development of an individual’s exceptional traits. 150 years have passed since Galton presented his ideas, and a century separates us from Terman’s early work. Nevertheless, to this day excellence researchers continue to focus most of their attention on the individual. Recently published reference works in the field of excellence and talent acquisition offer ample evidence of this tendency (Ericsson, Charness, Feltovich, & Hoffman, 2006; Sternberg & Davidson, 2005). At the same time, however, a number of promising approaches suggests that this view is now undergoing fundamental change. Emblematic of such new approaches is a remark made by Csikszentmihalyi and Wolfe (2000) that the mind is not the locus of genius. Rather, excellence exists in systems made up of individuals and their environments. Ziegler describes such systems as actiotopes and sociotopes (Ziegler, 2005; Ziegler, Vialle, & Wimmer, 2013), and his view is becoming more common in giftedness and excellence research. While it reflects a rather straightforward observation, its implications for excellence research are manifold and far-reaching. The distribution of excellence is not a matter of chance – excellence is not evenly distributed. Excellence is topographically and chronologically clustered.
Clusters of Excellence Unwittingly, Galton got one particular observation right about genius in his historiometric studies. The exceptional individuals he selected were topographically and chronologically contiguous. As a metaphor for the typically contiguous grouping of individuals who have achieved domain-specific excellence, we speak of clusters. In the following, we describe various types of clusters of excellence (cultures, families, geographical clusters, groups, and clusters of excellent organizations), starting first with those already described in Galton’s work.
Cultures Galton’s studies consider, among others, leading poets, scholars, and philosophers of Ancient Greece (e.g., Homer, Aeschylus, Aristophanes, Aristotle, Thales, Pythagoras, Socrates, Plato). In the domain of musical excellence it is striking that most of the composers Galton considered (e.g., Mozart, Bach, Beethoven, Haydn, Mendelssohn) came from German-speaking Europe. Furthermore, all of them were active within a relatively short period of time. The excellent painters in Galton’s study were assigned by him to three schools, the Italian School (e.g., Correggio, Bellini, Michelangelo, Veronese, Giorgione, Giotto, Tintoretto, Raffael, Titian, da Vinci), the Spanish School (e.g., Murillo, Ribera, Velásquez), and the Dutch School (e.g., Rembrandt, Rubens, Ruysdael, Teniers, van Dyck, van de Velde). He made these lists of eminent artists because he was trying to understand whether such artists were more likely to be related to other exceptional individuals. Only more recently have researchers recognized the topographical and chronological patterns in Galton’s lists. Further analyses combining historiometric methods and methods of exploring practice and performance patterns of experts revealed how the opportunities for life-span developments of outstanding performance are supported and shaped by the appropriate cultural background (Kopiez, Lehmann, & Klassen, 2009). Cultures of Expertise 3
Families Galton did, of course, notice that exceptional achievements were not evenly distributed among all families. He interpreted this fact as proof of the hereditary nature of high achievement. In drawing this conclusion, however, Galton overlooked the roles played by socialization and genotype-environment interactions (Plomin, 1994; Scarr & McCartney, 1983). Passive genotype-environment interactions are seen when, for instance, children share hereditary and environmental influences with their family members. Talented parents are particularly effective at finding the best social environment for their talented children. In the case of a reactive genotype-environment interaction, the environment reacts to the talents that a child demonstrates by providing her or him with appropriate learning opportunities. Active genotype-environment interactions are assumed when talented children actively reshape their own environments to suit their needs according to their own talents. A musically talented child, for instance, may prefer social interactions with those relatives and peers who also show particular interests and skills in music. Consideration of the possible types of genotype-environment interactions makes clear that explanations of excellence focusing on the individual are incomplete.
Geographical Clusters Excellence clusters often appear in striking geographical proximity. Alpine winter sports, for instance, are dominated by individuals from the Alps and the Rocky Mountains. In the case of cross-country skiing, on the other hand, many people from Scandinavia rank among the best. Academic achievements correlate positively in many parts of the world with urbanization. Rural populations tend to have less access to educational institutions and specialized forms of instruction. Geographical clustering patterns also bespeak the inadequacy of explanations of excellence that focus on the individual. In the case of our winter-sports example, the point is not simply that successful alpine winter-sports athletes live in the mountains. By doing so, they also ensure that they will have easy access to the best trainers and training facilities. And in the case of intellectual excellence, the best schools, research institutions, and universities are more often located in larger cities that provide more opportunities to build networks with other organizations and companies. The same geographical clustering patterns hold for the people upon whom the success of an individual in a particular domain will invariably depend: Successful people need to have the right promoters, agents, and publicists nearby (Hancock, Ste-Marie, & Schinke 2010). The fact that a remarkably high number of twentieth-century rock and pop singers and bands have a London background (e.g., Elton John, the Birds, the Who, the Kinks, the Police, the Rolling Stones, Cat Stevens, the Sex Pistols, Phil Collins, David Bowie) also clearly illustrates the tendency of domain-specific excellence to cluster geographically. London provided a sufficiently large audience and the ample performance opportunities and financial support without which these acts could not have become well known. A geographical cluster thus consists of social communities that bring together various interests and skills.
Groups Excellence also clusters in certain social groups. A leading professional soccer team is an example of such a group, in particular when one thinks of the team in the largest sense, in other words not just as the players but as all individuals working with or for the team (e.g., also the physical therapists, managers, and ticket sellers). The raison d’être for such an excellence cluster is the group that is accorded an exclusive label such as ‘excellent’ or ‘champion’ when successful. As home to the current world champion of soccer, Spain offers a case in point. Although the leading Spanish soccer teams have recently suffered setbacks, Real Madrid has won 4 H. Stoeger & H. Gruber
32 and Fútbol Club Barcelona 21 national soccer championships. All other soccer teams in Spain have won a total of only 28 national championships. Particularly remarkable is the fact that the two leading teams’ victories reflect the efforts of completely different members who belonged to different generations of players. Fútbol Club Barcelona won its first national championship in 1929, and Real Madrid took the national championship for the first time in 1932. Group-clustered excellence also defies notions of individual excellence. Even if all current members of one of these two teams were to be replaced, it is still reasonable to assume that Real Madrid or Fútbol Club Barcelona will still continue to frequently become national champions in the future – even though a less renowned Spanish team of the likes of Atlético de Madrid S.A.D. might occasionally win the national title. Clearly, then, the historical excellence of Fútbol Club Barcelona and Real Madrid cannot be explained merely in terms of the individual players who are playing for one of the teams at a given point in time. Similar phenomena have been described in other fields. Most of the German orchestras that pay their musicians the best will continue to be among the world’s finest when all of their current members have moved on or retired. In a similar sense, the assumption is reasonable that the professors who will be teaching at Harvard and Oxford in 2084 will still be found in the world’s leading research groups, even though these individuals have yet to be born. A deeper understanding of what leads to the long-term excellence of groups requires an examination at an organizational level.
Excellent Organizations The distinctions between groups and organizations are not always clear. Organizations are typically defined as social entities in which members work together in a coordinated manner involving a division of labor (March & Simon, 1958). Viewed from this perspective, organizations often consist of groups. Numerous examples show that excellence is also unevenly distributed at the organizational level. In their respective heydays, for instance, Roman, Chinese, and Prussian systems of government were more advanced than those of their neighbors. National educational systems offer a similar example. Results of comparative international educational studies such as those provided by the Organisation for Economic Co- operation and Development (OECD) with its Programme for International Student Assessment (PISA) show that the educational output of national educational systems can differ dramatically from one country to the next (OECD, 1999, 2014). The point is not simply that national educational systems differ according to how well they function but that they also differ according to the probability with which they produce excellence. The same is true of subsystems within each national education system. The legendary Middle School No. 8 in Beijing or traditionally strong universities such as Cambridge University educate cohorts of students who are consistently more likely to achieve excellence in various domains. These subsystems owe their own excellence to a number of factors which tend to propitiously coalesce: prominent researchers, talented students, excellent financial backing, infrastructure, etc.
The Emergence of Clusters As we have illustrated, excellence does not arise by chance. Its clustered distribution reminds us of the fact that excellence is a product of specific circumstances. In the following, we describe three particularly important causes of the emergence of clusters. Other articles in this special issue address similar factors that are situated on different levels of analysis such as individual practice, formation on centers of excellence, or cultural immersion.
Cultures of Expertise 5
The ‘Self-Made’ Genius Is a Misnomer – Excellence Is a Product of Professionalization Academies in which philosophy, arts, and sciences are taught have existed for thousands of years. This fact invites a thought experiment. If such academies had not existed and Aristotle had had no opportunity of receiving training in contemporary fields of knowledge, would he have become a ‘genius’? Probably not. People cannot single- handedly turn themselves into geniuses. Going beyond our thought experiment, we can also support this assertion with hard scientific data from today. Although our genetic predispositions have more or less remained unchanged over the past millennia, we nevertheless find enormous achievement increases in nearly every talent domain since the nineteenth century. This holds both for average levels of achievement such as, for example, average intelligence (Flynn, 2012) as well as for achievement peaks (Ericsson et al., 2006). And the same is true in non-intellectual talent domains. The record set for marathon running in Athens in 1896 in the first modern Olympics was, just a few decades later, much worse than the lower qualification limit for the Rotterdam marathon race. If such across-the-board improvements cannot be explained in terms of phylogeny, what, then, made such an abrupt improvement in performance possible? In the case of improving marathon running times, the single most important contributing factor has been the substantial improvement in resources available to athletes for improving their performance. A resource which has improved dramatically in almost all domains is instructional knowledge. Instructional knowledge includes insights on how outstanding learning works as well as on just what needs to be learned in the first place. Improvements in instructional knowledge, again, do not arise by chance. In almost any given domain, a process of professionalization precedes the development of instructional knowledge. Institutional recognition of this requirement can be seen, at the university level, in the fact that universities in many countries have professorships and departments dedicated to the didactics of fields such as mathematics, English, music, and sports. And outside of universities, parents often engage professional music or athletics instructors for their children. Today, teachers in many fields can draw on sophisticated instructional resources. Former top athletes often write books with insights on effective training regimens. Violin virtuosi prepare etude collections to help musicians master important techniques. Thanks to such professionalization processes, well-trained laypersons now perform at levels once achieved only by a select few within a given domain. Geniuses and virtuosi cannot achieve that status on their own nowadays. Their success is also the success of the myriad professions that contribute the instructional knowledge that allowed these individuals to develop.
Excellence Is Not About Isolation, It Is About Convergence Given that individual excellence is the product of cooperative efforts, it makes sense to think about the relationship between an individual who is pursuing excellence in a given talent domain and all of those assisting individuals and institutions who make this development possible. In short, the assertion that an individual’s achievement of excellence in a given domain is indicative of myriad support efforts is correct, but incomplete. The individual who achieves excellence will usually do so not just with any sorts of support, but with support of others who have also achieved excellence in their respective fields. In other words, once one’s eyes are opened to the cooperative nature of excellence attainment, one will also notice a convergence effect. As standards of excellence rise, so do the standards for the resources upon which an individual relies when developing excellence in a given domain. In the case of human resources (e.g., teachers, mentors, coaches), the people assisting an individual in the pursuit of excellence tend to be excellent in their own domain. Returning briefly to our soccer example, for instance, an excellent soccer team needs more than just great players. It also needs high-quality coaches, medical staff, etc. The same applies to an excellent scientist. A leading scientist needs a support staff consisting of people who are exceptionally good 6 H. Stoeger & H. Gruber at the jobs they do in their supporting roles. A brilliant scientist who leads an inept team of mediocre individuals to greatness by dent of a stroke of genius is highly unlikely. Edwin Hubble, for instance, was indeed a brilliant scientist. Nevertheless, he never would have been able to discover Hubble’s Law without new telescopes. These new telescopes were made possible by the financial support of foundations which had been organized by a number of leading business people (Sharov & Novikov, 1993). It is highly unlikely that Hubble could have single-handedly secured the funding for these telescopes. In addition to financing new telescopes, actually building what would become, at the time, the world’s best telescopes was in and of itself an exceptional achievement. Good will and effort most certainly would not have sufficed. Building the world’s best telescopes required exceptionally well-trained individuals who had access to the best materials available at the time. In other words: ‘Lonely excellence’ is also a misnomer. Rather, excellence begets excellence.
Limited Access to Resources As we have shown, excellence development depends on access to a variety of resources. Various factors limit individuals’ access to resources (e.g., political, economic, and ecological factors). Excellence tends to cluster in those locations that provide the best overall access to resources. Where individuals cannot access relevant resources, excellence will not develop. Ziegler and Stoeger (2011; Ziegler & Baker, 2013) developed a system for classifying resources underlying the development of excellence. At the level of the society in which excellence development takes place, Ziegler and Stoeger (2011) distinguish five types of educational capital that an individual will need in order to develop domain-specific excellence: Economic educational capital (money or valuables that can be invested in educational endeavors), cultural educational capital (value systems or thinking patterns that set up preferences for specific learning and educational goals), social educational capital (persons and social institutions that can contribute to the success of learning and educational processes), infrastructural educational capital (material possibilities for learning and education), and didactic educational capital (know-how about the design and governance of educational processes). Each form of educational capital obviously constitutes a case of limited resources. Access to these resources differs from person to person and from family to family. Differing levels of access to cultural educational capital, for instance, reflect the fact that only some people are born into families that place a high value on education and excellence. In the case of the Williams sisters we can assume that an exceptionally high level of social educational capital (e.g., support by parents who drove them to tennis practice) must have been available during the sisters’ formative years. Educational capital issues may also exert a negative impact. For many families, the tuition charged by leading private universities in some countries can vastly exceed or overtax available economic educational capital and thus prevent individuals from progressing down an otherwise well-planned path to excellence. Cultures that propagate gender-role stereotypes regarding mathematics aptitude (e.g., “Girls just aren’t as good as boys in math.”) saddle young people with negative cultural educational capital (Stoeger, 2007). If an athlete has the bad fortune of working with a trainer who, by a lack of judgment or by carelessness, should select a harmful training method, such an instance of negative didactic educational capital can have counterproductive consequences (e.g., injury, loss of motivation, development of ineffective techniques).
Contributions in this Special Issue In this special issue, renowned scholars collaborate on envisioning a perspective on expertization in which the social definition of individual excellence is taken seriously. As we illustrated in the first part of this contribution, the strong historical bias of expertise Cultures of Expertise 7
and giftedness research towards individual variables bespeaks the need for collaborative discussions of the social components of expertization. The following contributions make important inroads in this respect. In the first part of this special issue, three articles extend the picture of the expert by describing the social world surrounding excellent performance. Hakkarainen, Hytönen, Lonka, and Makkonen describe what has been called “epistemic cultures” since the publication of Knorr-Cetina’s (1999) book, in which the author showed that scientific communities tend to be clustered in an increasing number of subgroups and disciplines. According to Knorr-Cetina (1999), “science and expertise are obvious candidates for cultural divisions” (p. 2). She interprets existing disciplines and specializations in science as terms of knowledge differentiation in our society and applies network analysis to find out how those “knowledge machines” are structured. There has been general agreement for some time now that the social solidarity of research communities that are associated with particular research fields is constantly being formed and re-formed. Through the development of paradigms, models of problems and solutions are communicated to a community of scholars. Knorr-Cetina (1999) aptly summarizes her outlook and reasoning as follows: “In a knowledge society, exclusive definitions of expert settings and social settings – and their respective cultures – are theoretically no longer adequate; this is why the study of knowledge settings becomes a goal in the attempts to understand not only science and expertise, but also the type of society that runs on knowledge and expertise” (p. 8). Hakkarainen and colleagues agree that expert performance is defined and acknowledged within the social and societal networks in which knowledge cultures and epistemic cultures develop. These networks thus form the frame in which individual excellence is recognized and esteemed. In order to understand the development of individual expertise, it is thus necessary to describe, analyze, and measure what is believed (and shared) to be important, true, wise, and laudable. The practice of collaborative authoring found in doctoral programs in Finnish and European science centers of excellence is highly illustrative of such characteristics. In their contribution in this issue, Rehrl, Palonen, Lehtinen, and Gruber address a similar field by analyzing how expertise in science can be conceived and how researchers’ visibility in research communities increases. Expertise in science is determined both by research excellence and by acknowledgment of the respective research communities. Only rarely have these determinants been investigated jointly. The aim of Rehrl and colleagues is to empirically study researchers’ different network positions in a scientific community and to analyze how personal attributes on the one hand and network positions on the other hand predict the development of later scientific visibility, as bibliometrically measured via citations. The study focuses on two different types of interaction: communication via scientific publications and verbal communication taking place in conferences and in researchers’ daily work. Their findings reveal that the strength of the network position and activities in scientific communities were the strongest predictors of later scientific visibility as measured in terms of the h-index of publications. As predictors of later scientific success, personal attributes such as seniority and professional status were not as important as variables describing persons’ positions in their scientific networks. McWilliams and Plucker understand the social dimension of individual excellence by way of the concept of “smart contexts.” They argue that the creation, provision, and maintenance of smart contexts are the major educational contributions to talent and excellence development. Studies of “excellence education” should focus, they argue, on the creation and maintenance of smart contexts rather than on the abilities of individual students. The authors assert that research on excellence should heed the “social turn” and, furthermore, also acknowledge the relevance of the “digital turn” in the modern world. The second part of the special issue brings together three articles that investigate the arena of excellent performance at a later, more developed stage by examining the 8 H. Stoeger & H. Gruber contributions made by social factors to the acquisition and maintenance of high-level performance. Lehmann and Kristensen outline the role of “third persons” for the development of deliberate practice. They stress that such individuals both provide appropriate directions for practice and reduce the adverse influences threatening their mentees. A better understanding of how these interactions and activities work is important for improving the processes of acquiring and maintaining expertise. The concept of deliberate practice was developed around examples from professional music; Lehmann and Kristensen mainly focus on this domain as well, but their findings can be transferred to other domains. Deliberate practice is practice that aims to develop one’s performance level beyond its current level. The improvement of specific components is addressed in order to refine the efficiency of related activities. As such developmental activities are neither mindless drilling nor pleasurable recreation, they tend to be experienced as being not conformable according to typical definitions of intrinsically motivating activities. It’s difficult to decide which components or subcomponents within larger activities are candidates for specific phases of deliberate practice. Usually, certain individuals define the direction of practice and guide and monitor learners during practice. They design practice activities, set goals for practice, motivate, and sometimes even force individuals to engage in certain forms of practice, which often involve the breaking down of complex performance activities into smaller units to be practiced. Lehmann and Kristensen show that although expert performance, and musical performance in particular, is often individual in nature, the expertise towards which such practice is directed is situated within a social context. Individual strength and group acknowledgment are thus intrinsically related: Skilful people “become” experts through translating and integrating their knowledge into popular meaning systems (Walter, 2004). Other members of their expert culture guide them during (and often are the driving force behind) the acquisition of expertise. Mieg’s analysis of the organizational embedding of experts in “centers of excellence” puts the level of analysis even one step higher onto a macro level. Experts do not only excel individually and have access to outstanding mentors who guide their deliberate practice, they are also part of powerful organizations that aim to foster the development and maintenance of certain forms of expertise. Questions remain unanswered as to how such centers of excellence – or other organizational forms, networks, and communities – assess their members’ qualities and to which extent they refer to accounts of expertise and excellence in their policies. The article sheds light on the processes behind the development of centers of excellence and on the methods used to assess success within such centers. Finally, Jordan takes a cultural-anthropological stance on expertization. In her analysis of how technology influences social interaction and how both factors contribute to the creation and validation of knowledge, Jordan argues that much of our knowledge is not individually possessed but rather “authoritative knowledge.” Interestingly, her examples come both from advanced technological settings and from highly traditional settings. According to Jordan’s findings, any particular social situation brings together a multitude of ways of knowing. Crucially, however, some of these ways of knowing carry more weight than others. Certain kinds of knowledge are thereby discredited and devalued, while others become socially sanctioned, consequential, and “official” and are accepted as grounds for legitimate inference and action. Jordan explains, furthermore, that her article reflects central aspects of a working paper that was written two decades ago, at the Palo Alto Institute for Research on Learning, but has yet to be published. The working paper was drafted in what was one of the most advanced, innovative, and (thought-)provoking research labs worldwide at that time in the field of educational science. The work done there by J. S. Brown, Rogoff, Lave, Wenger, Jordan, Suchman, Collins, and many others challenged many established perspectives on learning and instruction. The concepts of cognitive apprenticeship, communities of practice, and situated learning emerged from the debates held at the Palo Alto Institute for Research on Learning. Jordan’s concept of Cultures of Expertise 9
“authoritative knowledge” is a thought-provoking and important example that illustrates how cultures of expertise contribute to the social definition of individual excellence.
Acknowledgment This paper was written during a sabbatical stay of the second author as Visiting Professor at the Centre for Learning Research, University of Turku, Finland.
References Cox, C. M. (1926). The early mental traits of 300 their own environments: A theory of geniuses. Vol 2. Genetic studies of genius. genotype-environment effects. Child Stanford: Stanford University Press. Development, 54, 424-435. Csikszentmihalyi, M., & Wolfe, R. (2000). New Sharov, A. S., & Novikov, I. D. (1993). Edwin Hubble: conceptions and research approaches to The discoverer of the big bang universe. New creativity: Implications of a systems York: Cambridge University Press. perspective for creativity in education. In K. Sternberg, R., & Davidson, J. (Eds.). (2005). A. Heller, F. J. Mönks, R. J. Sternberg, & R. F. Conceptions of giftedness. Cambridge: Subotnik (Eds.), International handbook of Cambridge University Press. giftedness and talents (pp. 81–93). New York: Stoeger, H. (2007). Berufskarrieren begabter Pergamon. Frauen. In K. A. Heller & A. Ziegler (Eds.), Ericsson, K. A., Charness, N., Feltovich, P., & Begabt sein in Deutschland [Being gifted in Hoffman, R. R. (Eds.). (2006). Cambridge Germany] (pp. 266–290). Berlin: LIT. handbook of expertise and expert Terman, L. M. (1906). Genius and stupidity: A study performance. Cambridge: Cambridge of some of the intellectual processes of seven University Press. ‘bright’ and seven ‘stupid’ boys. Pedagogical Flynn, J. R. (2012). Fate and philosophy: A journey Seminary, 13, 307–373. through life’s great questions. Wellington: Terman, L. M. (1926). Mental and physical traits of a AWA. thousand gifted children. Vol. 1. Genetic Galton, F. (1869). Hereditary genius. London: studies of genius (2nd ed.). Stanford: Stanford Macmillan. University Press. Galton, F. (1874). English men of science: Their Terman, L. M. (Ed.). (1930). The genetic studies of nature and nurture. London: Cass. genius. Stanford: Stanford University Press. Hancock, D. J., Ste-Marie, D. M., & Schinke, R. J. Terman, L. M., & Oden, M. H. (1947). The gifted (2010). The development and skills of expert child grows up. Vol. 4. Genetic studies of major junior hockey player agents. Talent genius. Stanford: Stanford University Press. Development & Excellence, 2, 51–62. Terman, L. M., & Oden, M. H. (1959). The gifted Knorr-Cetina, K. (1999). Epistemic cultures. group at mid-life. Vol. 5. Genetic studies of Cambridge: Harvard University Press. genius. Stanford: Stanford University Press. Kopiez, R., Lehmann, A. C., & Klassen, J. (2009). Walter, W. (2004). Experts’ discourses as judicial Clara Schumann’s collection of playbills: A drama or bureaucratic coordination: Family historiometric analysis of life-span debate in the United States and Germany. In development, mobility, and repertoire E. Kurz-Milcke & G. Gigerenzer (Eds.), Experts canonization. Poetics, 37, 50–73. in science and society (pp. 27–46). New York: March, J., & Simon, H. (1958). Organizations. New Kluwer. York: Wiley. Ziegler, A. (2005). The actiotope model of OECD (1999). Measuring student knowledge and giftedness. In R. J. Sternberg & J. E. Davidson skills. A new framework for assessment. Paris: (Eds.), Conceptions of giftedness (pp. 411– OECD. 434). New York: Cambridge University Press. OECD (2014). PISA 2012 results: What students Ziegler, A., & Baker, J. (2013). Talent development know and can do: Student performance in as adaption: The role of educational and mathematics, reading and science (Vol. 1, rev. learning capital. In S. Phillipson, H. Stoeger, & ed., February 2014). PISA, OECD Publishing. A. Ziegler (Eds.), Development of excellence Retrieved from http://dx.doi.org/10.1787/ in East-Asia: Explorations in the actiotope 9789264201118-en model of giftedness (pp. 18–39). London: Plomin, R. (1994). Genetics and experience. The Routledge. interplay between nature and nurture. Ziegler, A., & Stoeger, H. (2011). Expertisierung als Thousand Oaks: Sage. Adaptions- und Regulationsprozess: Die Rolle Posner, M. I. (1988). What is it to be an expert? In von Bildungs- und Lernkapital. In M. Dresel & M. T. H. Chi, R. Glaser, & M. J. Farr (Eds.), The L. Lämmle (Eds.), Motivation, Selbstregulation nature of expertise (pp. xxix–xxxvi). Hillsdale: und Leistungsexzellenz [Motivation, self- Erlbaum. regulation, and excellence] (pp. 131–152). Scarr, S., & McCartney, K. (1983). How people make Münster: LIT. 10 H. Stoeger & H. Gruber
Ziegler, A., Vialle, W., & Wimmer, B. (2013). The Ziegler (Eds.), Exceptionality in East-Asia: actiotope model of giftedness: A short Explorations in the actiotope model of introduction to some central theoretical giftedness (pp. 1–17). London: Routledge. assumptions. In S. Phillipson, H. Stoeger, & A.
The Authors and Guest-Editors
Heidrun Stoeger, PhD is chair professor for Educational Science at the University of Regensburg, Germany. She holds the Chair for School Research, School Development, and Evaluation. She is Editor-in-Chief of the journal High Ability Studies and member of the editorial board of the German journal of Talent Development. Her publications include articles and chapters on giftedness, self- regulated learning, motivation, fine motor skills and gender.
Hans Gruber (born 1960) is Professor of Educational Science at the University of Regensburg (Germany) since 1998 and Senior Fellow at the Faculty of Education, University of Turku (Finland) since 2013. His main research interests lie in the fields of professional learning, expertise, workplace learning, social network analysis and higher education. He is member of the Review Board “Education Sciences” of the German Research Foundation (Deutsche Forschungs- gemeinschaft) and President-Elect of the “European Association for Research on Learning and Instruction” (EARLI) where he is also founding chair of the special interest group “Learning and Professional Development”. Besides he serves as reviewer for many international journals, book series and research organizations.
Talent Development & Excellence Collaborative Authoring in Doctoral Programs 11 Vol. 6, No. 1, 2014, 11–29 How Does Collaborative Authoring in Doctoral Programs Socially Shape Practices of Academic Excellence? Kai Hakkarainen1*, Kaisa Hytönen2, Kirsti Lonka3 and Juho Makkonen4
Abstract: The purpose of the present investigation was to examine the social shaping of practices of collaborative authoring in doctoral programs which have led to the achievement of academic excellence in the natural sciences and in education. Toward that end, we interviewed 9 leaders of Finnish national centers of excellence doing science research and 12 Finnish and European leaders of educational research communities both of whom were engaged in supervising article-based doctoral dissertations consisting of international refereed articles co-authored by students and their supervisors. Qualitative analyses of the interviews revealed various ways that supervisors socially facilitate academic activity of their students. Their methods, which are expanding from natural to such social sciences as education, included guiding students in structuring articles, selecting publication forums, framing their investigations according to journal-specific requirements, and addressing review feedback collectively. Despite receiving a great deal of support, doctoral students were usually first authors of their articles. While doctoral students needed much support in the first article, their contribution became increasingly central in subsequent ones. Because of rising academic standards, however, senior researchers’ support continued to be important in later articles. Intellectual socialization to shared academic knowledge practices effectively boosts the development of academic competence allowing doctoral students gradually to make more productive contributions to joint knowledge-creation efforts.
Keywords: academic writing, article thesis, co-authoring, identity, knowledge practice, epistemic artifact
Academic achievements are still often attributed to the personal gifts and talents of individual researchers. Such conceptions do not appear to fit very well in the collective research practices that modern research communities have cultivated across many decades (Hakkarainen, Hytönen, Makkonen, Seitamaa-Hakkarainen, & White, 2013). The present investigation is aimed at addressing the sociocultural foundations of the collaborative practices of research and publication designed to produce academic excellence; the context is doctoral programs which have, in fact, achieved excellence in their recognized publications in natural sciences and social sciences. Academic excellence is a complex attribute of scholarly and scientific activity of a community; it is a capability based in sophisticated theoretical, methodological, and practical competencies that allow a participant to take productive part in designing, conducting, and publishing original scientific investigations in collaboration with his or her research community. Such competencies constitute academic expertise (Ericsson, 2006) that develops across a sustained process of socializing to practices of an academic research community and deliberately practicing various aspects of investigation under guidance of senior researchers. The present investigation focuses specifically on examining practices of intellectually socializing doctoral students to produce published articles in international,
1* Corresponding author. Department of Education, 20014 University of Turku, Finland. Email: [email protected] 2 Department of Teacher Education, University of Turku, Finland 3 Department of Teacher Education, University of Helsinki, Finland 4 Institute of Behavioural Sciences, University of Helsinki, Finland
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
12 K. Hakkarainen et al. refereed journals. Toward that end, we will examine the role of co-authoring in the epistemic socialization of doctoral students to knowledge practices of academic communities in natural sciences and in the field of educational research. By knowledge practices we refer to personal and social practices related to working with knowledge and carrying out academic inquiries (Hakkarainen, 2009; Ritella & Hakkarainen, 2012). We use the term “knowledge” here in the broadest sense, to include what is explicit in published texts and articles in refereed journals; we conceive of knowledge existing in disciplinary funds inherited from networks of published findings of earlier generations of investigators (Fleck, 1979); it comprises the theoretical and methodological repertoire of research communities. Further, we would include the procedures that implicitly and pre- reflexively shape an investigator’s working habits; and further yet that tacit capability which underlies the methodological and procedural skills and competencies of academic experts. Elaborating Knorr Cetina’s (2001) concepts, it may be argued that research communities rely on fuzzily determined, dynamically developing, exploration-oriented, and problem-laden practices that are occasionally innovative. Knowledge practices, while sometimes just supporting routine learning (transmission), at their creative edge, diverge from other routine social practices in that they take place in specific purposefully dynamic and fluid settings designed for the furtherance of innovation and knowledge (Hakkarainen, Lallimo, Toikka, & White, 2011; Knorr Cetina, 1999; Paavola, Lipponen, & Hakkarainen, 2004). Rather than relying only on mere mundane habits or repeated routines (that may also be needed), such practices are aimed at solving emergent problems and constantly pursuing novelty and innovation. Such practices are socially and physically distributed, and therefore cannot be located in individual minds only. Practices that emphasize collective knowledge creation and networked expertise (Hakkarainen, Palonen, Paavola, & Lehtinen, 2004) are typical in natural sciences, where pursuit of “big science” capitalizes on expensive equipment and large internationally networked research communities (Holmes, 2004; Nersessian, 2006; Pickering, 1995; Thagard, 1999). Academic research communities may be seen as learning environments (Pyhältö, Stubb, & Lonka, 2009) that acculturate doctoral students to academic practices of their discipline (Austin, 2009; Delamont, Atkinson, & Odette, 2000; Hakkarainen et al., 2013; Knorr Cetina, 1999; Lee & Boud, 2009). Academic practices rely on relatively stable disciplinary genres that may be characterized as socially and culturally recognizable forms of textually mediated communication or discursive practice (Bazerman, 1988; Hyland, 2004; Prior, 1998). The genre of journal article emerged through efforts of Isaac Newton and other investigators to find an appropriate way of justifying their knowledge claims. Hence, research genres have their own historically evolved and relatively stable implicit norms that are not easy to recognize and grasp by students. Natural sciences have perfected, across decades, academic practices that allow new cohorts of doctoral students to pursuit of cutting edge research; they learn, through coauthoring, to appropriate the scientific genre, write like scientists, and gain the competencies required for publishing in high- ranking journals (Florence & Yore, 2004; Kamler, 2008). Toward that end, doctoral students are engaged in pursuing article-based theses that consist of a summary and 3–5 internationally published articles co-authored between junior and senior researchers (about PhD by publication, see Dong, 1998; Dudley-Evans, 1999; Kwan, 2013; Green & Powell, 2005); such knowledge practices put doctoral students in the very heart of collective knowledge-creation efforts.Though co-authoring practices supervisors and other senior researchers come to the visible forefront of fostering the development of their students’ academic expertise, rather than remain “in the shadows” (Gruber, Lehtinen, Palonen, & Degner, 2008). Interviews of doctoral students functioning in natural science communities reveal how the students learn to capitalize on collectively shared investigative practices and socially distributed resources of investigation (Hakkarainen et al., 2013; Vekkaila, Pyhältö, Hakkarainen, Stubb, & Lonka, 2013). The article-based approach emphasizes the importance of acculturating doctoral students to work iteratively with shared research objects embedded in an evolving network of a Collaborative Authoring in Doctoral Programs 13 supervisor’s research projects (Gruber, 1981) that are transmitted from one cohort of inquirers to the next. Social sciences have, in contrast, relied on the traditional individual model of doctoral education that involves pursuing an extensive monograph based on personal research objects often not related to those of the supervisor (Becher & Trowler, 2001; Hakkarainen et al., 2013). This is partially due to different paradigms and qualitative research methodologies, requiring more theoretical framing and lengthier explanations. Historical examinations of knowledge practices across disciplines reveal that natural sciences relied on the lone-scholar model in the beginning of the last century, and that the collectivization of academic research is a relatively recent phenomenon (Merton, 1973; Thagard, 1997). While natural sciences have historically pioneered the collective approach to academic research, collaborative research communities are emerging in social sciences and some areas of their application in which the researchers have focused on collective creation of knowledge, by co-authoring articles (Figure 1a and 1 b). Many Scandinavian and other European investigators have been working to extend the collective, article-based model to social sciences in general and educational research in
A
B
Figure 1. Collectivization of academic research in terms of increasing proportion of co-authored articles (A) and increasing number of co-authors (B) in high-impact journals. Three selected journals with very high-impact values across six disciplines and classified 36000 articles according to percentage of co- authored articles and number of authors. 14 K. Hakkarainen et al. particular. The individual model of doctoral education functions rather well in thousands of cases of social sciences, and the point of the present investigation is not to argue for complete replacement of the individual model with the collective one. Detailed examination of the collective practices of doctoral education allows one, however, to investigate various processes and mechanisms crucial for the social shaping of academic competence. Article theses appear to represent a very productive “pedagogic practice” of writing for publication in doctoral education (Kamler, 2008; Kamler & Thomson, 2007): publication of refereed journal articles often does not take place at all in social sciences in absence of co-authoring practices. Kamler (2008) found that publishing the results of one’s academic dissertation is the best predictor of a student’s later scholarly productivity. Academic productivity is subject to tremendous variation: about 20% of the investigators produce most of the publications. Early socialization to collaborative publication and resulting appropriation of the implicit genre of “journal science” (Fleck, 1979, p.112) appear to be critical in terms of assisting the participant to move to the highly productive section of the academic population. Nevertheless, there is evidence that most social science students do not receive adequate mentoring, but instead, have to learn publication through sustained and troublesome, personal trial-and-effort efforts, if at all. Learning to produce academic knowledge is not only an intellectual challenge, but a personal and identity-related one as well (McAlpine & Amundsen, 2009). Doctoral students who experience that they are valuable members of their scholarly community express higher levels of well-being and also proceed faster in the doctoral projects (Stubb, 2012; Stubb, Pyhältö, & Lonka, 2011). Solo-publishing social-science students feel personally vulnerable when being evaluated by external investigators. They have a propensity to seek “safe spaces of publication” (Kamler, 2008; Kamler & Thomson, 2007), such as conference proceedings or journals with low criteria of peer review. The article- based model arises from the assumption that students should not be left on their own to produce academic publications, but should be provided collective support, deliberate supervision, and constructive feedback during their writing process (Kamler, 2008; Lonka, 2003). Coauthoring facilitates the growth of students’ academic competence, makes otherwise tacit strategic aspects of writing visible, and integrates personal with collective knowledge-creation efforts (Florence & Yore, 2004). Thus, deliberate and systematic co- authoring with supervisors in pursuing an article thesis appears to be “the crucial part of learning the ropes of academic publishing” (p. 288). We believe that there is something to be learned from the natural sciences in terms of levels of social engagement and collaborative productivity (Hakkarainen, Hytönen, Makkonen, & Lehtinen, 2014; Stubb, 2012). Although social sciences are still, to a great extent, based on an individual definition of excellence as exceptional personal competence, it appears that much can be learned from the more collective model of doctoral education characterizing natural sciences. Hence it appears beneficial to expand collective practices of academic knowledge production from natural to social sciences. The purpose of the present article is to examine to what extent practices of collaborative authoring, characteristic of the article-based collective model of doctoral education, may be fruitfully expanded from natural sciences to the field of educational research. By interviewing leaders of both science and education research communities oriented to supervise article-based theses, we examined the central academic practices that their respective research communities have developed for socializing doctoral students to article publication. The intention was to learn something of the best practices in both fields. We addressed the following questions: How do senior researchers assist students in structuring their articles, selecting publication forums, and framing their arguments? How are doctoral students assisted in dealing with review feedback? How do the present research collectives determine authorship, and what kinds of tensions and challenges have emerged? How do research communities representing natural sciences and educational research differ across these knowledge practices? Collaborative Authoring in Doctoral Programs 15
Method
The Context of the Study The present investigation is aimed at developing doctoral education in Finland, therefore, the requirements of Finnish doctorate may be explained as follows: The Finnish students do not pay any tuition fee, and their studies are usually funded by grants from private foundations, discipline-specific doctoral schools, university posts, or research grants. Characteristic for Finnish doctoral education is that it is quite unstructured compared to many other European countries (or the USA) and highly embedded in conducting doctoral research, although more systematic pedagogical models have been developed over the last decade. There is no extensive course work required before undertaking the doctoral research. Subject and methodological studies require 40 to 60 ECTS credits (1 credit in the European Credit Transfer System equals approximately 27 hours of study) for a doctoral degree, depending on the discipline.1 Doctoral studies are recommended to be completed in four years of full-time study, but it often takes longer. When completed, a Finnish doctoral dissertation is evaluated by two external evaluators, usually professors coming from other national or international universities. In Finland, the dissertation may be either a monograph (50k words) or an article-based thesis consisting of a synthesizing summary (20k words) and 3–5 internationally refereed journal articles. Although practically all theses of natural sciences are article-based, three quarters of theses accepted in the field of educational research are monographs. The article-based model is being extended to educational research by pioneering efforts of certain professors oriented to international publication. After evaluation, the manuscript is approved by the faculty for public defense, and the “academic opponent” (i.e., examiner) is nominated. After the public oral defense, the opponent decides whether he or she recommends ratification of the thesis, and the faculty grants the doctoral degree to the student and publishes her dissertation locally with an ISBN number (International postgraduate student mirror, 2006). The article-based approach of doctoral dissertation was initially developed in science and medical research from the 1940s, expanded to psychology and became the dominating model in these disciplines in 70s and 80s in Finland. In the field of educational research, article-based dissertations have been produced since the beginning of the 90s; although this approach still represents a minority (about 20%), it has become a well-established aspect of doctoral education in this field in Finland and many other countries in Scandinavia and Europe (Hakkarainen et al., 2014).
The Participants In order to examine the role of collaborative authoring in socializing doctoral students to practices of scientific publication, the first author interviewed 21 research leaders (table 1) from well-known Finnish and European universities representing a) leaders of Finnish national centers of excellence (medicine, physics, neuroscience, N1-N9) and b) professors of education engaged in collective practices of supervising article-based theses, involving journal articles co-authored with the supervisors (E1-E12).2 The educational research leaders were selected for interview because they have worked to extend the article-based practices of doctoral education to their field of social science. Research groups of the present research leaders varied in size from a few doctoral students and the supervisor to large communities with several subgroups led by professors and tens of doctoral students. Although acculturation of science students often takes place through laboratory settings, the present educational research communities rely on the more or less continuous presence of doctoral students, postdocs and senior researchers in shared office spaces; in the background there is the insight that effective academic socialization appears to require a physically present community (compare Delamont et al., 2000; Gardner, 2007; Knorr Cetina, 1999; Nersessian, 2006).
16 K. Hakkarainen et al.
Table 1. Background of the Participants and Research Data Length of interview Gender Nation Own PhD Superviseda Prestigeb Minutes Words N1 F FIN Article >31 1 125 15461 N2 M FIN Article 1–10 1 94 10752 N3 F FIN Article 11–20 2 128 10893 N4 M FIN Article >31 1 42 5667 N5 M FIN Mono 21–30 1 110 11943 N6 M FIN Article 11–20 1 57 6935 N7 M FIN Mono >31 2 91 19802 N8 M FIN Article 1–10 2 98 13843 N9 F FIN Article 21–30 2 86 10002 E1 F FIN Mono 1–10 3 144 14738 E2 M INT Mono 11–20 3 103 12976 E3 F FIN Article 11–20 2 141 16120 E4 M FIN Mono 21–30 2 155 15413 E5 F FIN Mono 1–10 3 97 11192 E6 M INT Mono >31 1 118 16933 E7 F FIN Article 1–10 2 64 6593 E8 F FIN Article 1–10 2 110 11852 E9 F FIN Article 11–20 2 93 12795 E10 M INT Mono >31 2 81 10672 E11 M FIN Mono >31 1 155 17349 E12 M FIN Mono 1–10 2 152 15850 Note. FIN=Finnish; INT=international. a In order to protect anonymity of the participants, only a rough estimation of supervised PhDs is provided. b The citation record of the participants was assessed by using the Publish or Perish program (http://www.harzing.com) and categorized according to the most highly cited ones (1) to the least cited ones (3): Group 1 (10.001-25.000), Group 2 (1001-10.000), and Group 3 (less that 1000 citations).
Practices of collaborative authoring were addressed as a part of an extensive interview covering knowledge creation processes from the collective nature of research problems and socialization of doctoral students to shared academic practices to scientific supervision. The length of interviews varied from 42 minutes to 155 minutes; interviews took longer when the interviewee wanted to share detailed aspects of his or her activities. Finnish participants were interviewed in Finnish and international ones in English. The interviews were audio recorded and transcribed word-by-word from audio files by experienced research assistants. The transcribed data were analyzed according to qualitative content analysis using the ATLAS.TI 6.0 program. The contents of transcribed interviews in which the participants addressed collaborative authoring practices were adjudged to represent the same hermeneutic category and structured according to the main themes of co-authoring that emerged from the data.
Results The results section is organized as follows: We will, firstly, examine extending the article- based model from natural-science to education programs and address, in subsequent sections, various practices of supporting students’ publication, such as structuring manuscripts, selecting publication forums, framing manuscripts for specific journals, and collective addressing of review feedback. Finally, there will be a discussion of issues regarding determination of authorship and associated challenges. In each section, we will first examine academic practices characteristic of natural science programs and subsequently those of educational research by relying on the interviewee data. Collaborative Authoring in Doctoral Programs 17
Emergence of Article-Based Practices of Doctoral Education All of the natural science communities that were investigated here pursued article-based dissertations, and co-authored doctoral articles constituted a major part of their research output. Focusing on solving collectively shared research problems related to a supervisor’s research projects, more than personal ones; this puts doctoral students into the heart of a collective knowledge-creation agenda instead of merely pursuing their personal study projects. The fact that some of the leaders had themselves completed monograph theses indicated that a major transformation of practices of producing scientific knowledge had taken place in their research communities. The interviewed education professors were transforming practices of doctoral training in their field toward the collective model by following the lead of natural sciences: “It came from the models given by other sciences, because I mean we already had incredibly capable research groups in the 70’s and 80’s in the fields of natural science and medicine, so of course we were interested in finding out how it is that they do it” (E4). The first article theses were authored by students only because it would not have been possible to have dissertation articles approved with a supervisor’s name on them. Education leaders have moved to an article- based approach in order to make the doctoral process more transparent in terms of pursuing shared objects rather than mere personal projects. Currently, the article model dominates the practices of doctoral training in the interviewed education professors’ research communities in Finland (E1, E3, E4, E7, E8, E9) and Europe (E2, E6, E10). Almost all dissertations of their core students aiming at a professional academic career are based on co-authored international articles: “Normally it is a dissertation by publications and everybody accepts that now” (E6). Students may, however, pursue monographs when warranted by specific reasons, such as a huge amount of ethnographic or historic data on a national language. Many education doctoral students are, further, practicing teachers (or other professionals) who pursue doctoral degrees to facilitate their self-development and may not trust in their capabilities of producing international articles. In general, doctoral students need encouragement, support, and active persuasion so as to orient themselves toward article-based dissertation: A supervisor is “like a salesman who tries to convince them to buy this way of doing an article dissertation, but I also help and do a lot for them as well” (E1). After seeing their peers do it and getting first articles out, the students gradually build their confidence and establish a disciplinary identity based on article pursuit (E6). Students cannot, however, be asked to do article-based dissertations without provision of full-time funding; this requires that education professors also obtain external research grants.
Structuring a Manuscript According to Disciplinary Genre Although academic writing is a critical aspect of scientific knowledge creation, the current educational system produces “very weak writers” (N4); students are seldom able to tell a good story that is required for effective communication of one’s findings to external investigators. Because learning of academic English is also difficult for many students, a great deal of effort has to be invested to coach students in academic writing. In natural sciences, the whole community assumes responsible for the quality of publications, and both junior and senior researchers take part in writing and rewriting dissertation articles. Social shaping of the students’ academic competence takes place by introducing students to the disciplinary genre (Bazerman, 1988) through coauthoring. Accordingly, doctoral students are taught what elements are commonly present in articles, how the elements should be integrated to reach desired coherence, and how the knowledge claims may be justified or supported. Toward that end, the student author will typically create an outline of an article so that each bulleted point will correspond to one paragraph of the completed article (N6, N7). A student writes a draft for each section starting from method, moving to results, discussion, introduction, and finally abstract; gets feedback from seniors and moves to the subsequent section when he or she feels ready. It is essential, further, to learn to use appropriate figures and interpret and explain them so 18 K. Hakkarainen et al. as to communicate to the readers what is truly significant in the findings. N8 estimated that the time required for constructing an article is cut in half with each dissertation article (from 18 months to 9 months, and finally 3-4 months). Although the senior researcher initially, to a large extent, determines the content and structure of an article, an experienced student may suggest his or her own structure and make a greater contribution. When completing their theses, students often become main writers who are able to independently generate ideas and drafts that are only reviewed by the leader. The interviewed education professors also highlighted collaborative practices of writing. Although it has seldom been a problem in educational research to collect data or cultivate methodological competences, producing “a coherent text, a claim, background, substantiation, and a main point is something which some people do easily and other people have big big big problems in” (E6). Consequently, students are sometimes selected (E12) according to their proven capacity to produce a high quality academic text (e.g., master’s thesis). The article-based practices acculturate students to writing articles so that the main burden for molding students to appropriate the article genre is carried out by postdocs and senior researchers: “I try to demystify this writing process by making it step by step, so now you present the background, you have one page, what would you say, and now you present your data, how you collected them, what is relevant about them, and then to decide on what are the main things you want to say, and then to see how that can be fitted into an article” (E6). Co-writing starts in E1’s community after they have collected and partially analyzed data and a doctoral student has produced a draft. She works intensively with a doctoral student in front of a joint computer over the whole day, creating joint frameworks for categorizing data, analyzing results, and composing other parts of the article. The student is responsible of completing each part of the article and formatting it according to disciplinary- and journal-specific guidelines. Reciprocal sharing of competence plays a crucial role in her community: “As a person gets it [an article] published their capability grows and then in turn they can help others” (E1). By circulating manuscripts between co-authors synchronously and asynchronously, doctoral students are socialized to a process of writing that involves thoroughly rewriting manuscripts several times during the publication process (E2). Doctoral students’ development is facilitated by involving them as co-authors in writing many side articles besides their dissertation ones. Students vary a great deal according to the level of support they need; this is not visible in the end product because co-authors compensate for each other’s weaknesses. Supervisors highlight the importance of early socialization to writing for publication. Toward that end, students are often engaged in publishing their master’s thesis as a journal article co-authored with the supervisor (the first dissertation publication).
Expanding Abstracts to Journal Articles Collectively oriented research leaders guide their students to learn academic writing by starting from writing short abstracts, upgrading and extending those to long abstracts, assuming responsibility for writing a section to an article, and finally constructing a whole article. In communities of N1, N3, and N4, students are guided to publish an abstract or poster immediately after they have collected “good data”. Correspondingly, educational research leaders send students to conferences to introduce their own work and become familiar with the disciplinary community as early as possible. “They must learn to write outlines and abstracts for conferences and then we refine them” (E6). Conferences are good environments for testing one’s research ideas; formal and informal discussions indicate whether ideas can be communicated, how argumentation should be improved, and what kind of new evidence should be obtained (E4). Conferences also provide deadlines and facilitative structures that assist in building articles (E12). Thus, when completing their dissertations, students not only write articles but also participate in an international academic network. By the time they finish their Ph.D.s, the doctoral students have to master academic writing as a generic competence, being able to produce comprehensive Collaborative Authoring in Doctoral Programs 19 academic knowledge for synthesizing literature and adequately reporting empirical research findings.
Selecting a Publication Forum One of the first tasks in submitting a publication is selection of the publication forum. In natural sciences, journals are selected according to their impact, scope, target community (academic; clinical), length of reviewing process, and article-specific publication price (many journals require researchers to pay for publication). Many articles are rejected because they fall outside the scope of journal; because of that, one needs to select journals to which one has “something to say and contribute” (N7). Experiences of natural sciences indicate that you need to put your objectives as high as possible, focusing on quality rather than quantity (N5). Departmental incentives of natural sciences emphasize the importance of having articles appearing in journals with an impact factor more than five. The present science communities start from considering Nature and Science and move down if data are not of sufficient quality and impact (N1). Many investigations adequate for a dissertation cannot, however, be published in the best journals. Risky doctoral studies do not often, so to say, produce the “desired jacket but only a pair of pants or just a hankie”(N1) that functions as a student’s training piece. Publishing in high-impact journals is a challenging and long-term process; according to one participant half of the submitted articles are initially rejected and need to be sent elsewhere (N4). This has to be taken into consideration in selecting journals because “time is money” (N6) in the doctoral process. Non-publishing education professors used to claim, according to E1 and E3, that there are no international forums for publishing data on the Finnish education system; hence they did not try. Successful experiences of supervising article-based theses have, however, revealed that numerous publication forums are available. When submitting manuscripts, it is essential to be aware that the journals are working within certain research fields, which submissions need to advance further (E7). Targeting high-quality forums, respective to the field, is an important concern of many of the interviewed educational research leaders (E1, E3, E4, E7, E8, E9) when selecting journals. Nevertheless, discourse regarding journal impact is, overall, new in the field of educational research. Initially, supervisors of article theses had had to try publishing “by improvising; we just tried to think about where they [doctoral students’ manuscripts] fit in thematically, and for example this whole idea about the varying demands or impact of different journals was totally unknown to us” (E4). Investigators who have just started to create a publication culture tend to focus on quantity of publications. Article pursuit has guided the present education leaders, however, to follow citations, and publish less frequently, but in better journals (E2, E7). Many of the interviewed education leaders utilized the European Science Foundation’s (ESF) ranking of educational journals to select publication forums so that articles are deliberately aimed at journals with “high quality”. Tightening academic standards are supported by emerging departmental and university-level incentive systems that emphasize quality so that articles in high-quality journals, respective to the field, count more that low impact ones. By following practices of medical research, there is an attempt to get the last submitted manuscript, the final piece of an article thesis, to one of the highest-quality or - impact journals (E7). Submitting manuscripts to high-quality journals provides useful review statements, even when they are not accepted. Doctoral articles are often not sent to the most demanding journals because it may take such a long time (E3); one picks the tenth of the ranking rather than the most prestigious one. Doctoral students socialized to journal science are reported to become aware of the quality of scientific journals; they have made statements opposing departmental publication discourse focused on quantity (E7, E8). Overall, many educational leaders stated that publishing in high-quality journals should be better recognized and supported. In a rapidly evolving research field, impact based on journal history cannot, however, be the only criteria of publication, as mentioned by E6; it is also essential to publish in journals representing new methods and 20 K. Hakkarainen et al. fields of research in spite of initially low impact. ESF rankings in educational sciences are not only based on impacts, but for instance, the rejection rate is one of the additional measures among others.
Framing and Justifying Arguments The interviews revealed that doctoral students need a great deal of support in framing articles and justifying their arguments. In order to adequately frame their investigations, doctoral students need to comprehend the wider context of their investigations rather than focus only on a specific area of investigation assigned to them. To truly understand what they are doing and the deeper significance of the problem they are working with, doctoral students need to read widely (N5). They should not, however, read too widely because students who know everything easily become academic “fire extinguishers” (N1) who may prematurely end potentially promising lines of investigation on the basis of superficial information about earlier research efforts. Without being able to contextualize one’s work adequately, doctoral students would not be able to “highlight the fundamental significance of their work” (N8). In natural sciences, investigators have to be economical in their argumentation through making only those knowledge claims that are necessary for the main point of the article. When submitting to the most prestigious journals, it is, moreover, essential to convince the editors that one’s contribution is substantial enough and interesting to a large body of readers. Because framing plays such a crucial role in publishing in high-impact journals, senior researchers’ support is often needed long after science students have learned other aspects of academic publication. Framing of investigations is a central concern also of the interviewed educational leaders. When assisting a student with an article that includes a good question and research design, E7 emphasizes “focusing and argumentation… they probably need my help most in that, smoothing out the rough edges and that you don’t need to say everything in one article and all the data doesn’t need to be used to solve one research question…” (E7). Cultures of publication vary, for instance, between European and American journals, and each journal has its own preferences regarding methods and argumentation that may be difficult for doctoral students to understand. In order to surmount the publication threshold, it is essential, according to E1, E2, E3, and E10, to guide doctoral students to investigate articles that have appeared earlier in the target journal so that they are able to make a contribution that advances associated academic discourse. It is also essential to cite relevant articles that have formerly been published in the journal. In E1 and E3’s groups, students are guided to read and analyze a large number of articles published in the target journal and give a corresponding presentation to their research groups. Students of E7 and E8 have collected a database regarding a number of journals and the length and nature of review processes so as to rapidly select an appropriate publication forum. While other supervisors focus on facilitating data analysis, E3, in contrast, guides students systematically to examine their manuscripts from the perspective of specific academic audiences: “They always learn in the beginning what journal they can send to, what’s the readership, how to frame them [manuscripts]; this is where I help a lot.” (E3). She stated that the senior researcher’s contribution is to provide “an invisible hand” that assists in framing a student’s good manuscript in a way that makes it publishable in the target journal. This entails writing the manuscript deliberately for a specific audience and providing transparent arguments without excessive jargon.
Collective Address of Review Feedback All interviewees across natural sciences and educational research had developed practices of addressing review feedback collectively. Rather than leaving doctoral students alone to deal with oftentimes strict review criticism, natural science groups of N2, N3, N4, and N5 sent it to all co-authors and other relevant community members to be collectively responded to. An inexperienced student cannot adequately interpret the meaning of review statements; even critical feedback may be a positive indication that a Collaborative Authoring in Doctoral Programs 21 manuscript is about to be accepted. Doctoral students are guided to accept rejection; immediate acceptance of manuscripts would imply following too low standards and submitting pieces to weak journals. Participation in the journal science acculturates students to work productively with external reviewers, forcing them to do inquiry in depth, contextualize findings, and try to go beyond the next edge of knowledge creation. Doctoral students are challenged to stretch their capacities for initially considering how to respond to review criticism (N5); senior researchers come to help only when necessary. In many other cases, the seniors are more closely involved in considering rebuttal of review criticism, making changes to improve the submission, and constructing the final cover letter accompanying the manuscript. Review comments are also shared among co-authors and other relevant community members rather than processed by doctoral students alone in the selected educational research communities. Receiving unforgiving review criticism is always a “shock” (E8) to a doctoral student. “If [the student] was alone in this kind of a phase he or she would think there was something wrong with them, that they were talentless or something” (E3).Working closely with external reviewers makes the doctoral process more transparent in nature because “you get much more regular feedback from the group and the feedback by reviewers” (E10) so as to overcome weaknesses that are not obvious to students. Co- authoring acculturates students to deliberately seek criticism outside of their immediate academic circle, and, thereby, expand their creativity by relying on experience and competence of investigators coming from different contexts. Going through repeated reviews is essential because it socializes students to openly share their unfinished manuscripts without which collective resources could not be mustered to support improvement. Partially because writing a monograph is a lonely process, “there are a lot of people that are afraid to show their texts …to [outsiders]”(E1). E3 is deliberately training her students to work productively with people commenting on his or her manuscripts: “I try to train each group to give constructive and encouraging feedback. It’s the whole idea of the seminar, that you form a collective flow and people start to help one another” (E3). Instead of individual rumination on negative feedback, E3’s community has created a practice of warmly congratulating a student who is requested to make “major revisions and resubmit this thing. Then we congratulate them that it’s excellent for this thing to be moving forwards, and then we do the corrections [as soon] as possible and move on” (E3). Even if a manuscript were to be rejected, the spirit is to get good review comments and submit it elsewhere. E6 and E10 taught students to understand seemingly punitive review criticism as a communication problem. A very detailed critical feedback is a good sign that a busy evaluator has some appreciation for the manuscript in question. The manuscript needs to be improved so as to better communicate its ideas to reviewers coming from a different context. According to E6, it is sometimes equally crucial to furnish a more extensive cover letter interpreting and rebutting reviewers’ critiques and explaining changes when resubmitting the actual, revised article. In submitting manuscripts, it is essential to learn to understand the target community, appropriate corresponding academic language, identify proper references, and share the relevant research paradigm. Also personal connections matter; getting articles accepted is difficult if nobody knows your work and face. E11’s community organizes specific research seminars for collectively responding to review feedback of doctoral students or other researchers: “We take the reviewers’ arguments or corrections and go through them one by one, examine them and think about how we could plausibly implement them without it turning into an impossibly large assignment” (E11). Senior researchers are required to carefully prepare for such discussions often intended to produce concrete guidelines of improving the manuscript in question. The acceptance of the first dissertation article is often critical, but sometimes it could take two or three years, and keeping up the motivation becomes difficult: “One important thing is to keep the flame burning in the beginning once the idea has been hatched because usually it comes with a fair bit of excitement, but then there’s arduous long 22 K. Hakkarainen et al. work, and it isn’t always obvious that the inspiration stays the same; there can come a time when it runs out” (E4).
Determining Authorship for Collaborative Publications Practically all science publications are co-authored. The science leaders agreed that only those who have made “a sufficient intellectual contribution” (N1), in accordance with the sciences’ ethical principles, should be included as authors. The participants may have very different but relevant roles in joint publications, from creating research ideas and theories, developing instruments and methods, experimenting and collecting data, and analyzing and modeling data, to writing of the manuscript. Overall, it is essential to try to find a balance between the most loose and most constrained criteria of authorship (N7). Doctoral articles are co-authored because of being embedded in collective research achievements (N9). In most science-research communities, doctoral students were first authors of publication credited in their dissertation, even if they received substantial support from senior colleagues: “Well, they become the first authors, get the primary credit on their works, even if they need a lot of support, even if we write it over 20 times” (N1). Students who do the hard work of collecting data will always be the first authors in spite of being pushed and supported. In N3’s community, the starting point is that each article published is a part of a doctoral student’s dissertation. Sometimes research assistants are taken as co-authors to encourage their academic interests. In medicine, it is sufficient that the doctoral student be the first author in a half of the doctoral articles; elsewhere three or four first authorships are needed. Most of the education leaders were also oriented toward systematic collaborative publication. As E7 stated, “Nobody here publishes alone. Our work is collaborative, it’s difficult to identify a single person who has created our solutions or ideas” (E7). Co- authoring was considered an essential form of collectivity; it gives visibility to the whole group, indicating that they are engaged in doing interesting studies. E2 stated that the doctoral students “learn to publish together with me. So the regular proceeding is that the first article is published with me as a supervisor, the second is quite often either with me or other senior colleagues, and the third article, or the fourth article is either alone or it could be together with other PhD students” (E2). While the importance of publishing doctoral investigations was emphasized by E11 and E12, it did not necessarily mean co- authoring; often students prepared and submitted their studies personally. E1 often asks doctoral students to submit one article without the supervisor’s direct assistance so as to facilitate their academic independence. Some research leaders proposed that it is essential to vary the composition of co-authors from one publication to the next. Sometimes capable research assistants are involved as coauthors to “spark” them to become researchers later on (E4). In the case of dissertation articles, doctoral students are the first authors, carrying the main responsibility for creating the draft, constructing the outline, analyzing and interpreting the data; they control the process and keep up the pace when the manuscript is written in turns (E6). Various contributions should be recognized, from creating research ideas, determining research designs, constructing tools and instruments, analyzing results, and writing the article. Because of the increasing complexity of research designs and methods, it is more and more important to have methodological experts as co-authors (E4).
Challenges and Possibilities of Collaborative Publication The collectivization of academic research entails that it is more difficult to determine the boundaries of authorship, especially in natural sciences, which rely on complex and heterogeneous division of academic labor in massively distributed global knowledge production centers. Investigations increasingly have to rely on socially distributed expertise, such that one participant knows information technology; another one, experimental methods; a third one, human genetics; a fourth one, academic writing, and so on (N5, N6). Consequently, for a single paper, the number of authors has been rapidly Collaborative Authoring in Doctoral Programs 23 increasing in medicine and physics (from five to ten authors on average) across the last two decades. It used to be relatively easy to agree about authorship among half a dozen participants along the same corridor. In present contexts, such decisions present intricacies: There are varying contributions to data acquisition, instrument development, and data analyses from 15 researchers in 10 different countries. In order to proactively avoid conflicts, it is essential to inform relevant stakeholders that an article is about to be produced, agree about authorship beforehand, and provide participants with opportunities to contribute to the actual writing. When several doctoral students were involved in investigations, conflicting expectations could emerge, for instance, regarding first authorships or order of authors. In order to avoid conflicts, “I’ve always had the opinion that borderline cases are included, so that nobody’s feelings are hurt. If someone thinks that he should be in, … it’s not [taking] away from anyone else, if there’s a seventh name there, why should we drop it?” (N5) Education professors reported that conflicts sometimes emerge because the publication process takes a long time and within an open community a student may quickly utilize another one’s pioneering idea as a part of his or her publication before the former one has been able to complete his or her investigation (E4). Sometimes students coming from an individualist culture do not understand why the supervisor should be included as an author in an article. E3 compared the supervisor’s contribution with creating trails that assist a student to successfully ski across difficult terrain:“It’s really consuming [demanding] to ski where nobody has skied before, there’s no route and you don’t know where you’re going. So you can go to ski there, but it’ll take a damn long time and there’s no guarantee you’ll make it back alive. When you do go skiing, you’ll have to do the physical work, you’ve got to ski for yourself, [because] that’s your job. But [in the contrasting situation] you are skiing along a track that’s been readymade; your skis are waxed and you’re wearing a hat. So you can think, when you’ve skied fifty kilometers, that you’ve skied it all by yourself, but you didn’t build the track. So [in fact] the track is there, you’ve got a hat on and the skis are sliding, you can’t even begin to imagine what it would be like to ski without those things” (E3).Usually, problems can be avoided by contributors openly discussing principles of co-authorship and beginning to negotiate about authorship when first preparing publications. One interviewed education professor was reluctant to put his name to a doctoral student’s article because it would mean taking advantage of the latter’s work in building the professor’s own CV. Because education is a more literate activity than science, it would, said this professor, be “incomprehensible and against norms of science” (E12) to be included as an author in an article without taking part in the actual writing of it. The other supervisors of article theses did not at all consider being designated co-authors with doctoral students, in such cases, to be ethically problematic. Nevertheless, because the whole rationale of the collective model is to acculturate doctoral students to knowledge creation through co-authoring, it is critical to have seniors contributing to the actual writing of publication, beyond mere reading and commenting on a student’s manuscripts. The present interviews indicated consistently that the research leaders were actively involved in pursuing investigations in which students’ dissertation articles were embedded. Substantial collective support and facilitation by senior researchers appeared to play a crucial role in getting student papers accepted by rigorous journals. In any case, if one is setting up a collaborative approach to scientific publication in order to genuinely improve the quality of doctoral education, it is essential to recognize and overcome potential biases of co-authoring (including too loose criteria for authorship of senior investigators). An advantage of pursuing article theses is in fostering collaboration within a research community as well as assisting supervisors and postdocs to “get some merit [credit] for doing it [supervision], that they get publications under way” (E6). It would be “a suicide in terms of academic practices” (E3) to stay many years in a cubicle and create a monograph destined for a library shelf. Doctoral investigations become a part of the collective body 24 K. Hakkarainen et al. of scientific knowledge and subject to citation only after being published. An advantage of an article thesis is that even if something goes wrong, the student at least has the articles to his or her credit. It is, further, possible to be fairly confident that after the articles have gone through the peer review, the dissertation is likely to be approved; said one professor, “I’ve had doctoral students whose first publications have been already been cited 60 times by the time that they’re defending their thesis” (E3). The collective approach appears, on the present evidence, to be a desirable way to proceed in the future, in educational research, but there are certain risks involved as well. According to E4, it does not assist in improving the quality of educational research if one moves mechanically to the “classic model of repetitive empirical research” (E4) recycling similar questionnaires infinitely with new populations, so as to maximize the number of publications. E11 agreed that it is a risk if “the pressure to produce is interpreted to [mean] this kind of quick putting out [of] these articles, no matter the cost” (E11). Because projects have short life cycles, doctoral studies often relate to more than one project; keeping a coherent focus can become a problem: “The risk is that it [the research object] begins to fragment because working one article at a time is a threat [to coherence]. So that’s when the supervising relationship becomes incredibly important, [in order] that the totality of the project needs to be bigger than just the one article, so these two levels need to be made to work together with some certainty” (E11).
Discussion The role of co-authoring practices in doctoral education was examined by interviewing leaders of cutting-edge groups in the natural sciences as well as leaders of educational research communities oriented to supervising article theses. Because actual enacted academic practices were not directly observed, the responses should be taken to represent the interviewees’ perceptions and interpretations of the collective facilitation of the development of doctoral students’ academic competence. Yet the interviews provided striking similarity across natural-science and educational research communities regarding social shaping of practices that give rise to recognized academic excellence through socializing doctoral students to scientific publication through co-authoring. Co-authoring is a principal method for acculturating doctoral students to producing knowledge publishable in peer reviewed journals. It appears as a truly significant educational achievement of leading-edge science communities to be able to systematically train doctoral students capable of pursuing publications appearing in highly regarded, refereed, scientific journals. Although only a few dissertation articles are likely to end up being published in the top, prestigious journals and meeting the highest standards of professional creativity, deliberate enculturation of doctoral students to international publication raises epistemic standards and facilitates the scientific competence and productivity of the participants. Hakkarainen and his colleagues’ (2013) analyzed the knowledge-creating agency of doctoral students of physics and medicine: the study revealed that two-thirds of the doctoral students’ talk addressed the intellectual and social support that their research community provided for academic knowledge creation. Doctoral students taking part in research collectives are able to use collective resources to surpass their individual capabilities; they co-develop with their research objects, investigative processes and resulting co-authored articles, “authoring themselves” during the process (Holland, Lachicotte, Skinner, & Cain, 1998). Such accounts of the collective facilitation of investigative competencies in natural sciences are very valuable because academic achievements are still often considered to mainly rely on individual gifts and talents, and there are only a few studies concerning collective creativity of academic research (e.g., Delamont et al., 2000; Hakkarainen et al., 2013; Knorr Cetina, 1999). Collective publication practices appropriated from natural sciences are being productively implemented in research communities of the interviewed education professors. Creation of a publication culture is a long-standing and labor-intensive Collaborative Authoring in Doctoral Programs 25 process. A senior researcher interested in appropriating it should ensure that his or her university accepts article-based theses consisting of co-authored articles. As far as the supervisor is also him- or herself struggling to learn practices of international publication, creating and moving the first article thesis to completion could take a relatively long time. After the first students have graduated, however, they can guide and support the newcomers. In order to become quickly socialized to journal science, doctoral students should be involved in publication efforts already when they are doing their master’s theses. Initially, senior researchers should provide a great deal of guidance and support; later on, the doctoral student’s contribution becomes more central so that the supervisor may fade to the background. It is very important to encourage collaboration and support between newcomers and more experienced peers. After acculturating a few cohorts of doctoral students to journal science, resources of supervision distributed among a community are likely to kick in. Nevertheless, the supervisor should take care of his or her students and personally ensure that they get the support and guidance needed. Social support is critical because learning to publish is not only an epistemic but identity related achievement as well. Going through the publication process with assistance of senior researchers and seeing his or her own article published, is likely to build the doctoral student’s self-efficacy (Bandura, 2006). When extending the collective model to the educational research, it should, however, be taken into consideration that many students are practicing professionals who are not aiming at a professional research career; in their cases the traditional approach of doing a monograph and going through corresponding formative experiences may be adequate. Rooting collaborative publication culture has been difficult because co-authored publications are still sometimes devalued and considered dubious in the field of educational research, even when published in high-impact journals. Nevertheless, collectivization of doctoral investigations is worthwhile because well-functioning research communities amplify available socio-epistemic resources beyond the sum of individual ones (Hakkarainen et al., 2013). Yet, the collective model is not without limitations and risks. In academic cultures, often hierarchical and competitive in nature, doctoral students pursuing articles co-authored with their seniors may become even more dependent on their supervisors than those relying on the traditional individual model (Hakkarainen et al., 2013). The downside of enhanced academic achievements, may be “academic capitalism” (Slaughter & Rhoades, 2004), characteristic of publication cultures in which doctoral students are treated instrumentally as a part of a “publication machine”, serving the interests of senior researchers and their funders. When co-authoring with students, academic supervisors are not only helping students but also building their own publication record. In order to cope with tightening quality standards and international scientific competition, research in social sciences takes place more and more often in competitively funded multi-disciplinary research projects (Green 2009; Nowotny, Scott, & Gibbons, 2001) which are expected to produce verifiable results published in internationally refereed journal contributions. Funding of Finnish universities relies more and more on their performance measured by academic degrees and internationally refereed scientific publications across all disciplines. In parallel with extending the collective practices of supervision from natural sciences to such social sciences as education, the Finnish university system is going through a major reform that involves a significant percentage of university or departmental funding being determined according to internationally refereed publication, with a specific emphasis of articles in high-impact journals. This is likely to increase publication pressures in general and contribute to further extension of the article-based collective model in particular. When asked to specify contributions required for co-authoring, the supervisors from natural sciences to education highlighted importance of making a genuine contribution to designing, conducting, and analyzing investigations and participating in actual writing of articles. Ethical problems emerge if a senior researcher expects to be included as an author without actually taking part in relevant aspects of a study. Observing such ethically problematic situations has made some senior researchers, such as E12, decide to distance 26 K. Hakkarainen et al. themselves from their students’ publications. In order to avoid internal conflicts, it is essential to explicitly agree about principles of co-authoring and procedures of solving disagreements, and ask newcomers to sign a corresponding research agreement. Co- authoring principles should be transparent and fair (in terms of protecting right of both doctoral students and their supervisors) and focus on maximizing the research community’s collaborative efforts. The present investigation is in accordance with Walker and his colleagues’ (2008) suggestion to improve the quality of doctoral education by establishing intellectual communities focused on collaborative research at the heart of doctoral scholarship. As the seminal investigations of Howard Gruber (1981, see also Hakkarainen, 2012) have revealed, research communities and their leaders pursue evolving networks of mutually supporting and complementary research projects which provide ample opportunities for deliberately producing insights, going beyond prevailing frontiers of knowledge, and gradually establishing cutting-edge practices of academic research. Truly significant academic achievements are always made in research communities; “one person can never be the best in the world but a group can be the best” (N3). Many of the present research leaders had invested many years of effort to cultivate collective practices that support effective journal publication. While pursuit of journal science is very difficult to learn on one’s own, innovative practices gradually emerging from such intensive transformative efforts may become crystallized and embodied as a part of a research community’s shared, routine, everyday knowledge practices. Hence, deliberate epistemic socialization of new cohorts of doctoral students to collaborative practices of journal science arguably represents inter-generational learning (Holmes, 2004; Hakkarainen et al., 2013) and plays a crucial role in the dynamic facilitation of academic knowledge creation. It may be proposed that in such communities, innovation and pursuit of novelty are themselves transformed to shared social practices through the deliberate cultivation of desired personal and collective competencies and patterns of shared activity (Knorr Cetina, 1999, 2001; Paavola et al., 2004; Sawyer, 2007; Simon, 2002). This process allows the immersion of subsequent student cohorts immediately in journal-based scientific endeavor when they enter a research community. Appropriation of such innovative knowledge practices as an initial cornerstone of one’s academic activity appears to provide a good basis for further expansive efforts, for instance, to cultivate research practices rigorous enough to meet requirements of high- quality journals. Accumulating publication and citation records allow academic research communities to obtain competitively funded national, European, and international research projects and initiate novel lines of inquiry breaking boundaries of prevailing knowledge and competence. Although academic communities do not always function perfectly, growing into a community characterized by distributed academic practices enhances doctoral students’ cognitive capacities to an extent that enables them to solve significantly more complex problems than would otherwise be possible. Such capacities are best not thought of as individual characteristics or gifts, but, we argue, rather as the appropriation, within individuals, of the capabilities of the research cultures in which they function. Taking part in advancing an already started “long march” (Holmes, 2004) of academic investigation is likely to enable junior researchers to reach higher peaks of knowledge creation than reached when one relies mainly on personal and local experiences (Hakkarainen et al., 2013). In order to facilitate students’ acculturation to collaborative production of academic knowledge, it is important to have supervisors who are willing to invest time for guiding and coaching newcomers. In collaborative research communities supervision is, moreover, distributed across junior (doctoral students and post-doc at different stages of their investigations) and senior participants; learning by working at the elbow of more experienced peers is, in many cases, as important as direct guidance of the supervisor (Hakkarainen et al., 2014). Getting access to sophisticated collective academic practices cultivated across many years and decades appears to be the only known (relative) short- Collaborative Authoring in Doctoral Programs 27 cut to acquiring the practices of academic excellence. Doctoral students participating in cutting-edge research communities may become competent in knowledge creation, as we have termed it, even if the productions are not necessarily extraordinary or ground breaking. Deep intellectual enculturation to knowledge practices of leading-edge research communities appears to have parallels with races on a track: “when they [students, newcomers] have the opportunity to launch themselves from such a high platform, then they can go for the Nobels and things, when they’re not wasting their time and are given – like in a relay race – … kind of a running start” (N5).
Contributions and Acknowledgements The present investigation was supported by grants 2106008 (University of Helsinki),127019, 1265528 (Academy of Finland) and 462054 (RYM Indoor Environment, TEKES). Hal White MA assisted in improving the English language of the present study. Antti and Otto Seitamaa assisted in translating transcriptions of Finnish interviews to English.
Notes 1 We are thankful for Kirsi Pyhältö for helping us to explain differences between Finnish and European doctoral education. 2 Some of the present neuroscientists designated themselves as working in the field of psychology, in which capacity investigators commonly rely on the methods of both the natural and social sciences. Historically, psychology has played a central role in promoting the appropriation of the collective approach in social sciences. In order to examine how the collective model of doctoral education can be extended from natural to social sciences, however, the participants were clustered into groups according to their methodological preferences. Some of the present educational research leaders have roots in psychology and are oriented to study educational psychology. These issues were, however, not further considered for purposes of the present study.
References Austin, A. E. (2009). Cognitive apprenticeship and deliberate practice on the development theory and its implications for doctoral of superior expert performance. In K. A. education. International Journal of Academic Ericsson, N. Charness, P. Feltovich, & R. Development, 14, 173–183. Hoffman (Eds.), The Cambridge handbook of Bandura, A. (2006). Toward a psychology of human expertise and expert performance (pp. 683– agency. Perspectives on Psychological Science, 704). Cambridge, MA: Cambridge University 1, 164–180. Press. Bazerman, C. (1988). Shaping written knowledge: Fleck, L. (1979). Genesis and development of a The genre and activity of the experimental scientific fact. Chicago: The University of article in science. Madison: University of Chicago Press. Wisconsin Press. Florence, M. K., & Yore, L. D. (2004). Learning to Becher, T., & Trowler, P. R. (2001). Academic tribes write like a scientist: Coauthoring as an and territories: Intellectual enquiry and the enculturation task. Journal of Research in cultures of disciplines. Second Edition. Science Teaching, 41, 637–668. Berkeley, CA: University of California Press. Gardner, S. K. (2007). “I heard it through the Delamont, S., Atkinson, P., & Odette, P. (2000). The grapevine”: Doctoral student socialization in doctoral experience. London: Falmer. chemistry and history. Higher Education, 54, Dong, Y. R. (1998). Non-native graduate students’ 723–740. thesis/dissertation writing in science: Self- Green, B. (2009). Challenging perspectives, reports by students and their advisors from challenging practices: Doctoral education in two US institutions. English for Specific transition. In D. Boud & A. Lee (Eds.), Purposes, 17(4), 369–390. Changing practices of doctoral education (pp. Dudley-Evans, T. (1999). The dissertation: A case of 239–248). London: Routledge. neglect? In P. Thompson (Ed.), Issues in EAP Green, H., & Powell, S. (2005). Doctoral study in writing research and instruction (pp. 28–36). contemporary higher education. London: Reading: Reading University, Centre of Open University Press. Applied Language Studies. Gruber, H. E. (1981). Darwin on man: A Ericsson, K. A. (2006). The influence of experience psychological study of scientific creativity. 28 K. Hakkarainen et al.
Second Edition. Chicago: The Chicago In B. Somekh & T. Schwandr (Eds.), Knowledge University Press. production: Research in interesting times (pp. Gruber, H., Lehtinen, E., Palonen, T, & Degner, S. 166–179). London, UK: Routledge. (2008). Persons in the shadow: Assessing the Knorr Cetina, K. (1999). Epistemic cultures. social context of high abilities. Psychology Cambridge, MA: Harvard University Press. Science Quarterly, 50, 237–258. Knorr Cetina, K. (2001). Objectual practices. In T. Hakkarainen, K. (2009). A knowledge-practice Schatzki, K. Knorr Cetina, & E. Von Savigny perspective on technology-mediated (Eds.), The practice turn in contemporary learning. International Journal of Computer theory (pp. 175–188). London: Routledge. Supported Collaborative Learning, 4, 213–231. Kwan, B. S. C. (2013). Facilitating novice Hakkarainen, K. (2012). Mapping the research researchers in project publishing during the ground: Expertise, collective creativity, and doctoral years and beyond: A Hong Kong- shared knowledge practices. In H. Gaunt & H. based study. Studies in Higher Education, Westerlund (Eds)., Collaborative Learning in 38(2), 207–225. Higher Music Education (pp. 13–26). Surrey; Lee, A., & Boud, D. (2009). Framing doctoral UK: Ashgate. education as practice. In D. Boud & A. Lee Hakkarainen, K., Hytönen, K, Makkonen, J, & (Eds.), Changing practices of doctoral Lehtinen, E. (2014). Extending collective education (pp. 10–25). London: Routledge. practices of doctoral education from natural Lonka, K. (2003). Helping doctoral students to to educational sciences. Manuscript finish their theses. In L. Björk, G. Bräuer, L. submitted for publication. Rienecker, G. Ruhmann, & P. Stray Jørgensen, Hakkarainen, K., Hytönen, K., Makkonen, J., (Eds.), Teaching academic writing across Seitamaa-Hakkarainen, P., & White, H. (2013). Europe. London: Kluwer Academy Press. Interagency, collective creativity, and McAlpine, L., & Amundsen, C. (2009). Identity and academic knowledge practices. In A Sannino agency: Pleasures and collegiality among the & V. Ellis (Eds.), Learning and collective challenges of the doctoral journey. Studies in creativity: Activity-theoretical and socio- Continuing Education, 31, 109–125. cultural studies (pp. 77–98). London: Merton, R. K. (1973). The sociology of science. Routledge. Chicago: University of Chicago Press. Hakkarainen, K., Lallimo, J., Toikka, S., & White, H. Nersessian, N. (2006). The cognitive-cultural (2011). Cultivating collective expertise within systems of the research laboratory. innovative knowledge-practice networks. In S. Organization Studies, 27, 125–145. Ludvigsen, A. Lund, I. Rasmussen, & R. Säljö Nowotny, H., Scott, P., & Gibbons, M. (2001). Re- (Eds.), Learning across sites: New tools, thinking science: Knowledge and the public in infrastructures and practices (pp. 69–86). Earli a gage of uncertainty. Cambridge, MA: Polity series: New perspectives on learning and Press. instruction. New York: Routledge. Paavola, S., Lipponen, L., & Hakkarainen, K. (2004). Hakkarainen, K., Palonen, T., Paavola, S., & Modeling innovative knowledge Lehtinen, E. (2004). Communities of networked communities: A knowledge-creation expertise: Professional and educational approach to learning. Review of Educational perspectives. Advances in Learning and Research, 74, 557–576. Instruction Series. Amsterdam: Elsevier. Pickering, A. (1995). The mangle of practice: Time, Hakkarainen, K., Wires, S., Stubb, J., Paavola, S., agency, and science. Chicago: The University Pohjola, P., Lonka, K., & Pyhältö, K. (2013). On of Chicago Press. personal and collective dimensions of agency Prior, P. A. (1998). Writing/disciplinarity: A in doctoral training: Medicine and natural sociohistoric account of literate activity in the science programs. Studies in Continuing academy. Mahwah, NJ: Erlbaum. Education, 36(1), 83–100. Pyhältö, K., Stubb, J., & Lonka, K. (2009). Holland, D., Lachicotte, W., Skinner, D., & Cain, C. Developing scholarly communities as (1998). Identity and agency in cultural worlds. learning environments for doctoral students. Cambridge, MA: Harvard University Press. International Journal for Academic Holmes, F. L. (2004). Investigative pathways: Development, 14, 221–232. Patterns and stages in the careers of Ritella, G., & Hakkarainen, K. (2012). Instrument experimental scientists. New Haven: Yale genesis in technology mediated learning: University Press. From double stimulation to expansive Hyland, K. (2004). Disciplinary discourses: Social knowledge practices. International Journal of interactions in academic writing. Ann Arbor: Computer-Supported Collaborative Learning, The University of Michigan Press. 7, 239–258. International postgraduate student mirror (2006). Sawyer, R. K. (2007). Group genius: The creative Catalonia, Finland, Ireland and Sweden. power of collaboration. New York: Basic Högskoleverket: Swedish National Agency for Books. Higher Education (2006: 29R). Simon, H. (2002). Achieving excellence in Kamler, B. (2008). Rethinking doctoral publication institutions. In M. Ferrari (Ed.), The pursuit of practices: Writing from and beyond the thesis. excellence through education (pp. 181–194). Higher Education, 33, 283–294. Mahwah, NJ: Erlbaum Kamler, B., & Thomson, P. (2007). Rethinking Slaughter, S., & Rhoades, G. (2004). Academic doctoral work as text work and identity work. capitalism and the new economy: Market, state, Collaborative Authoring in Doctoral Programs 29
and higher education. Baltimore, Maryland: Thagard, P. (1997). Collaborative knowledge. Noûs The John Hopkins University Press. 31(2), 242–261. Stubb, J. (2012). Becoming a scholar: The dynamic Thagard, P. (1999). How scientist explain disease. interaction between the doctoral student and Cambridge, MA: MIT Press. the scholarly community. (Doctoral Vekkaila, J.,Pyhältö, K., Hakkarainen, K., Stubb, J., & dissertation, University of Helsinki, Helsinki, Lonka, K. (2013). Doctoral students’ key Finland). Retrieved from http://urn.fi/URN: learning experiences in a top-level natural ISBN:978-952-10-6867-6 sciences research community. International Stubb J., Pyhältö, K., & Lonka, K. (2011). Balancing Journal for Research Development, 3, 154–183. between inspiration and exhaustion: PhD Walker, G. E., Golde, C. M., Jones, L., Conklin students’ experienced socio-psychological Bueschel, A., & Hutchins, P. (2008). The well-being. Studies in Continuing Education, formation of scholars. San Francisco, CA: 33, 33–50. JosseyBass.
The Authors Kai Hakkarainen, Ph.D. (www.utu.academia.edu/KaiHakkarainen) is the professor of educational research at the Department of Education, University of Turku. With his colleagues, Hakkarainen has, for 15 years, carried out learning research based on psychology and cognitive science at all levels, from elementary to higher education. Many investigations have included a strong theoretical component, and have addressed how learning and human intellectual resources can be expanded using collaborative technologies based on the information and communication technologies. During recent years, Hakkarainen’s research activity has expanded toward investigating personal and collective learning processes taking place in knowledge-intensive organizations, including innovative private corporations and academic research communities.
Kaisa Hytönen, M.Ed., is a PhD student working at the University of Turku, Faculty of Education. Her dissertation focuses on examining horizontal and vertical transitions during expert careers in emerging knowledge-intensive fields. Her research interests focus on networked expertise and professional learning and development.
Kirsti Lonka, PhD, is professor of educational psychology at the Department of Teacher Education, Faculty of Behavioural Sciences, University of Helsinki, Finland. She is the Principal Investigator of Mind the Gap project (1265528) and RYM Indoor Environment WP4, Task 1.1 (462054). She is also President of the Teachers’ Academy, University of Helsinki (2013-2014). Previously she was Vice Dean of the Faculty of Behavioural Sciences (2011-2013) and Foreign Adjunct Professor at the Karolinska Institutet, Sweden (2007-2011). Earlier she was working as professor of medical education at the Karolinska Institutet (2001- 2005). Prof. Lonka has received several awards and honors, including the J.H. Bijtel Chair, University of Groningen, The Netherlands (2007-2008).
Juho Makkonen is a student of education at the University of Helsinki. He is currently pursuing a longitudinal investigation of doctoral students’ social networks and experiences of pursuing monograph versus article thesis in the field of education.
30 K. Hakkarainen et al.
Talent Development & Excellence Experts in Science 31 Vol. 6, No. 1, 2014, 31–45 Experts in Science: Visibility in Research Communities Monika Rehrl1*, Tuire Palonen2, Erno Lehtinen2 and Hans Gruber1
Abstract: Expertise in science is both determined by research excellence and by acknowledgment of the research communities. Only rarely these determinants have been investigated jointly. The aim of the present study is to describe researchers’ different network positions in a scientific community and to analyse how personal attributes and network positions predict the development of later scientific visibility, measured with citations. The target group studied was the Learning and Professional Development special interest group of the EARLI (N = 66). The data included information about attendance to conferences from the years 2002–2010 and citation counts from the years 2006 and 2012. The results indicate that the members of the community did not form a highly coherent group. The results showed that the strength of the network position and the level of professional qualification were the strongest predictors of later scientific visibility.
Keywords: citations, expertise, network position, scientific community, social network analysis, visibility in research
Similarly to expertise in other domains, scientific excellence has traditionally been explained in terms of individual attributes. However, in contemporary research it is commonly accepted that expertise development wears an important social facet. Outstanding skills and knowledge do only emerge after there is a social mechanism through which certain individuals are more or less collectively recognised to be experts in the field. Expertise is constituted as a socially initiated nomination by the experts’ constituency (Agnew, Ford, & Hayes, 1994). The ascription of expert status is based on perceived differences in knowledge and skills so that the expert can only be defined relationally to the knowledge and skills of other members inside a shared context. Expertise in that sense implies not only particular cognitive components but also an acknowledged role as expert within the constituency. There is no doubt that knowledge and content matter are important to expertise, and that these individual attributes are acquired through long periods of deliberate practice (Ericsson, 2009), because experts’ skills are primarily influenced by acquired domain-specific patterns and associated actions (Feltovich, Prietula, & Ericsson, 2006). Experts are denoted by “reproducible superior performance” (Ericsson, Roring, & Nandagopal, 2007), but the definition of what counts as “reproducible superior performance” is based on a social appreciation of this performance. Usually the constituency within science is organised by national or international communities or networks, thus social interaction and communication play a decisive role. In science, two different ways of interaction have to be distinguished, namely communication via scientific publications, and – either formal or informal – verbal communication taking place in conferences and in researchers’ daily work (Gruber, Lehtinen, Palonen, & Degner, 2008). In order to better understand the social nature of scientists’ careers and visibility it is crucial to analyse both of these two parallel aspects of scientific communities: publications and social positions in scientific networks. Even though bibliometric analysis is an effective technique to illuminate some fundamental
1 Institute of Educational Science, University of Regensburg, Germany * Corresponding author. Institute of Educational Science, University Regensburg, D-93040 Regensburg, Germany. Email: [email protected] 2 Centre for Learning Research, University of Turku, Finland
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
32 M. Rehrl et al.
features of scientific communities, it is also important to understand underlying informal aspects of communication, such as mentoring, collegiality, or different forms of informal collaboration. There is still a lack of research, however, which combines both ways of interaction in order to understand their reciprocal relationship.
Scientific Collaboration Scientific communication takes place in social processes through which individuals and groups repeatedly engage in joint scientific products, such as commonly organised presentations in conference symposia or jointly written publications. If the communication is fruitful, it can develop up to collaboration, or friendship (White, Wellman, & Nazer, 2004), and obviously it is related to local nearness and reachability of collaboration partners (Evans, Lambiotte, & Panzarosa, 2011; Kienle & Wessner, 2006). Connections or ties between actors indicate the access to critical resources of a community (Gruber et al., 2008). Ties facilitate an intensive flow of information across the wider network of actors in the same field, helping to gather richer information than would be possible for an individual working alone. According to Larson (1992) and Hansen (1999), social dimensions like reputation, trust, reciprocity, or interdependence of the transaction are pivotal in the exchange structures of organisations in general. It is plausible to assume that longstanding ties among experts enhance communication and help to achieve cohesion in science, too. Further, social interactions between scientific groups are essential for knowledge accumulation and scientific progress. Informal knowledge exchange allows researchers to verify, extend, and generalise the research findings (Carolan & Natriello, 2005; Palonen & Lehtinen, 2001). The integration of informal and formal communication may lead to collaborative activities like co-publishing and joint research projects. The concept of an invisible college (Crane, 1972; Price, 1986) provides a link between formal and informal aspects of scientific practice. According to Mulkay, Gilbert, and Woolgar (1975) invisible colleges are concentrations of research ties without clear boundaries or amorphous social groupings that are in a state of constant flux. Lievrouw (1990) argues that this idea of informality has not been reflected well enough because researchers tend to focus more on products of scholarship (documents and citation data) and/or network structures rather than on the actual communication processes of people who do scholarly work. Invisible colleges, however, are not only structures of scholarship but also social processes rooted in informal human behaviour. Scholars that share similar research interests produce publications and communicate both formally and informally with one another, working towards important goals, although they may live geographically distant from each other. In science, subject specialty is a source of the intellectual motivation for social activity, information sharing and collaborative research (Zuccala, 2006). The quality of information resources, however, does not only depend on the volume of information flow, but on the patterns of connections as well. The same amount of ties can be much more or less fruitful for scientists depending on who is involved in his or her network. Larger patters of connections form a kind of potential network, which can be activated whenever specific support, for example in using novel methods, is needed (Gruber et al., 2008). One way to understand complexity of network contacts is brought up by the tradition of structural equivalence or similarity. Structural similarity can be understood as “radio channels” inside the (scientific) community. Those having similar network positions, in a way, listen to the same radio channel. They may or may not be tied to other listeners of the same channel but overall cohesive groups are not evidently needed. In scientific communities “listening to the same channel” typically means participation in the same theoretical and methodological discourses. An interesting question related to science and expert studies is, whether these channels are qualitatively different. Do the best Experts in Science 33 performers in the science “listen to the same radio channels”, or are they randomly distributed over the field? When we combine them with other indicators of scientific performance, such as citations, we can study how similar network positions in the scientific community are related to the quality, popularity, or visibility of the scientific activity.
Citations as Indicator of Scientific Visibility Bibliometric indicators, such as the number of publications and of citation counts, are increasingly used in measuring the quality and performance of individual researchers, academic institutions, and national research systems (Diem & Wolter, 2011). There are many reasons to prefer citation counts instead of mere numbers of publications in measuring scientific quality and impact. According to the very nature of the scientific process the value of individual research findings is evaluated by the critical audience, which consists of other researchers in the field (Francis, 1989). In every scientific field there are numerous publication forums which have large differences in their publication thresholds and rejection rates (Glänzel & Moed, 2002). Only those scientific publications that are used by other researchers have an impact on the accumulation of scientific knowledge. The most widely used database in citation analysis in natural sciences and medicine is Thomson Reuters Web of Science (WoS; Diem & Wolter, 2011; Norris & Oppenheim, 2007). In particular in science and medicine, WoS is considered to be a reliable source, because it is based on the data of most established journals (Larivière, Archambault, Gingras, & Vignola-Gagné, 2006). In addition it provides well-elaborated tools for citation analysis. The problem, however, is that WoS does not give equal coverage to publication forums in social sciences and humanities. Until recently WoS citation count has only included refereed journals. For example in educational sciences less than 50% of references are made to journal articles (Larivière et al., 2006; Norris & Oppenheim, 2007). Since 2004 Google Scholar has provided an alternative for WoS. The important difference is that Google Scholar covers scholarly publications available on the Web. It does not only include peer-reviewed journal articles but also books, book chapters, and conference papers (van Aalst, 2010). Because of the larger coverage the number of citations in Scholar Google are typically greater in number than Web of Science citations (Bar-Ilan, 2008; Diem & Wolter, 2011). The total number of citations can be used as a measure of scientific impact and visibility but it has been considered to be a problematic indicator. High numbers of citations can be based on a large number of lowly cited papers or a few highly cited ones. A large number of lowly cited papers is an indicator of high publication activity but it does not necessary indicate high scientific quality (Bornmann & Daniel, 2007). A few very highly cited papers can mean high scientific quality but are not a reliable indicator of a sustainable scientific impact. Because of the problems of mere citation counts, different, more balanced indicators have been proposed. In 2005, Hirsch proposed a mathematically simple index, called h-index, which integrates citations and the number of papers cited. A scientist has an index h if h of his or her total of N publications have at least h citations each, and the remaining N-h publications have fewer than h citations each (Hirsch, 2005). For example a scientist’s h-index is 20 if he or she has 20 publications that have 20 or more citations. This index eliminates the problems of mere citation count presented above by Bornmann and Daniel (2007).
Social Network Analysis Approach Social Network Analysis (SNA; Wasserman & Faust, 1994) is an increasingly used approach to investigate both the social structure of interaction within subgroups and the attributes that are related to the actors inside a community. Although SNA allows to study practically all kinds of connections, the method has especially been used to uncover the patterning 34 M. Rehrl et al.
of people’s interaction that leads to various types of applications, such as inter- organisational relations, the spread of contagious diseases, social support, the diffusion of information and animal social organisation. That is, SNA facilitates the analysis of structural data. There are alternative streams in SNA, the cohesion approach and the structural equivalence approach. The former is related to the connectedness of the network’s actors, whereas the latter is based on similar network positions, the analysis of a group’s participants who share same third parties in communication networks. The actors who are structurally equivalent or similar do not need to be in direct contact with each other. Many studies on scientific networks comprehend the importance of both cohesion and structural equivalence, especially if both bibliometric and social relations are investigated (Carolan & Natriello, 2005). Evidence exists that similar network positions are tied to some kind of hierarchy among network members (Wasserman & Faust, 1994). The structural position has been shown to be an important indicator of power, because a good network position provides access to information, people, and other resources (Burt, 1987; Lomi, Snijders, Steglich, & Torló, 2011). In a narrow sense, structural equivalence requires that two persons have identical relationships with all other individuals in the given population. In real life, structural equivalence occurs only to a certain degree. A common way to analyse structural similar persons thus is to use a stochastic criterion to identify positions within networks (Frank, 1996).
Network Ties and Scientific Publication and Citation Practices There have been a few studies combining social network data and bibliographic analysis. However, it is beneficial to study social and intellectual networks in parallel. The networks based on social ties between scientists (social networks) and on citation patterns (intellectual networks) are not fully congruent. Relatively fewer scholars have studied communication processes between the scientists than have studied the structural properties of science. Both aspects are needed for a comprehensive understanding of the dynamics of scientific communities (Lievrouw, 1989). Scientific publication practices are related to the social structures of scientific fields (Moody, 2004). In studying researchers’ visibility it is important to analyse how social networks, within and between scientific communities and citation practices are related. White et al. (2004) proposed two alternative hypotheses concerning the relationship between social ties and intercitations. The social network hypothesis is based on the assumption that members of a group or network would cite each other’s publications because they know each other. According to this hypothesis intercitations are associated with the closeness of the social and communication ties, such as friendship and frequent conversation. As an alternative model they present the intellectual network hypothesis. According to that hypothesis intercitation cannot be explained with mere social ties but it is based on a common discipline and shared subject matter. The empirical data of the study supported the intellectual network hypothesis. Therefore, the joint interest in specific topics and methods is a stronger predictor of intercitations than content-neutral social ties (White et al., 2004). Content-driven intercitation and co-authoring practices have been demonstrated in many studies within different disciplines (Kajikawa, Ohno, Takeda, Matsushima, & Komiyama, 2007; Moody, 2004; Palonen & Lehtinen, 2001). From these studies it can be derived that multiple analysis tools have to be combined in order to understand the relation between individual attributes of expertise in science and the position and visibility in research communities. Most prior work using a combination of bibliometric and sociometric research techniques (social network analysis and citation analysis) have focused on the possible congruence between social relations and intercitations between certain scientists. However, in order to better understand the social aspect of the development of research expertise (Gruber et al., 2008) it is important to Experts in Science 35 study how a researcher’s network position within a scientific community predicts his or her later scientific visibility in terms of citations. In the study reported in the following this research question is addressed.
Research Questions The aim of the study is to examine how the researchers participating in a scientific organisation are positioned and grouped within the network of researchers (research question 1) and whether these network positions result in later visibility of their scientific work (research questions 2–4). (1) How is the scientific community constructed? The centrality of the members is evaluated based on the number of their collaboration partners and on how valuable their advice is seen by other members in the scientific community. We thus study the volume and experienced relevance of knowledge exchange inside the community and the kinds of network positions that exist in the community, interpreted by the indicators of structural equivalence. (2) How does social position, defined in terms of social contacts in the scientific community, relate to expert performance measured with citation count? (3) Are there qualitative differences among various equivalent network positions? To what degree are individual attributes, such as gender, seniority, length of professional experience, and scientific popularity, related to scientists’ network positions? (4) Does a similar network position within a scientific community predict the later citation profile of the community members: Can we predict expert performance in the field of science by the network position inside a scientific community?
Method
Participants As a starting point for the analysis of expertise in science through the study of visibility in research communities, it was decided to identify as community a relatively newly founded sub-organisation of a large research association. This group was founded a decade ago with the purpose to support the growth of research in a particular field. Membership in this group was thus primarily determined by a particular research focus, which not necessarily is the only focus of the involved researchers. The target group were the members of the Special Interest Group (SIG 14) “Learning and Professional Development” of the European Association for Research on Learning and Instruction (EARLI). The EARLI was founded in 1985; before that time, research in Europe was organised and supported only at the level of individual states. Language, culture and the different traditions of the various educational systems were widely thought of as barriers for meaningful collaboration or any co-ordination efforts. Since then, EARLI has grown into a dynamic scientific community that attracts more than 2000 participants from over 50 countries. The EARLI journals “Learning and Instruction” (impact factor May 2013: 3.732) and “Educational Research Review” (impact factor May 2013: 2.333) have grown into two of the most influential scientific journals in educational research. EARLI has a strong focus on junior researchers (JURE) and encourages communication between researchers through a total of 23 Special Interest Groups. All EARLI communication is held in English language: publication in the journals, attendance of the conferences, working in SIG networks or in JURE networks. One typical characteristic of the EARLI is that SIG membership is only one part of one’s scientific network. Those who are peripheral actors in a SIG may well be central actors in another network. In particular, all SIG members are also members of the EARLI organisation itself. This example illustrates that network characteristics partly depend on the size of the network. A 2000+ member network like EARLI necessarily has a less dense 36 M. Rehrl et al.
relational structure than a 100 member network like a SIG. As the SIGs are at the core of the scientific interaction, a SIG was selected as network for the present study. With only some persons missing from the target group (which comprised N = 66 members at that time), altogether 52 registered members of the SIG 14 (28 females, 24 males) participated in the study at its first step in 2006. Among the participants there were 19 professors, 4 assistant professor, 18 postdoctoral researchers and 11 PhD students representing 15 different countries. Participants were assured that their names and their nationalities would not be published.
Instruments The network variables and attribute data that were collected are summarised in table 1. Network Variables. Participants were asked to rate their relation to all other members of the SIG 14. The network questions asked were: (1) “With whom have you already collaborated (for example in the form of joint publications, joint symposia, or joint memberships on scientific committees)?” (2) “With whom do you discuss your own research projects and outcomes?” In both questions, the answers were given as a scale 0 = never, 1 = once, 2 = several times, 3 = regularly. In addition, the respondents were asked to evaluate (3) how relevant the discussions are for their work progress (0 = of no importance, 1 = rarely relevant, 2 = quite often important, 3 = very helpful). Attributive Data. The data about individuals’ scientific indicators were categorised into: (1) seniority, (2) membership in other scientific communities, (3) professional qualification in a university or in another research institution, (4) scientific visibility (based on citation count from the electronic data base Google Scholar at 2006 and at 2012; the Publish or Perish software was used to collect the 2012 citations and h-indexes; in unclear cases the listings were checked by using the lists of publications presented in the author’s web page), and (5) SIG 14 community activities (number of attendances in SIG conferences). (6) We classified the answers about the scientists’ research focus reported in the questionnaire into the following categories: (a) vocational education, (b) higher education, (c) teacher education, (d) researching on expertise, (e) workplace learning, (f) computer-supported learning, and (g) a rest category. Seniority was assessed in terms of the number of years as professional researcher (1 = less than 5 years, 2 = 5–10 years, 3 = more than 10 years) and as member of the SIG 14 (0 = less than 1 year, 1 = 1 year, 2 = 2–4 years, 3 = more than 4 years). The professional qualification was based on the work position: PhD Student, researcher, assistant professor or professor. The attendance activity variable indicates how many times the participant had attended the SIG 14 conferences. The participation data were collected from the first five conferences that had been organised by the SIG 14 community (Turku 2002, Regensburg 2004, Heerlen, 2006, Jyväskylä, 2008, and Munich 2010). The attendance in conferences was counted so that 0 = “not present” and 1 = “present”, the values thus ranging from 0 to 5.
Table 1. Variables Collected in the Study. Network variables Attributive variables (at relational level) (at individual level) Collaboration (0–3) Seniority (1–3) Informal communication (0–3) Memberships (min = 0, max = 9) Relevance (0–3) Professional qualification (1–4) Attendance in SIG conferences (0–5) Research focus (categorical) h-index (min = 0, max = 53) Citation count (1–10) Professional years (1–3) SIG years at 2006 (0–3) Experts in Science 37
Procedure An online questionnaire was sent to the participants in 2006 to assess relations between the SIG 14 members. Additionally, subjects were asked about their research focus and demographic information, such as the length of their professional career and how long they had been members in the SIG 14 community. The participants’ scientific impact was gathered from the Google Scholar database. The citation variable was created for each member based on the year 2006 by using the Google Scholar database as such, and a second time based on the year 2012 by using the Publish and Perish software (Harzing, 2010) to do the citation count. The citations were classified into ten groups covering the number of citations from 0 to 13 000. In addition to the number of citations, the participants’ h-index was calculated from the 2012 data. To conclude, the data originates from the year 2006 (questionnaire including the network questions and personal attribute data, and the first citation index), the conference information from the years 2002–2010, and the citation count from the year 2012, including the h-index.
Data Analysis In SNA, density and centrality are the basic concepts. Density shows how many ties exist in the network compared to the maximum number of possible ties. So, the more relationships actors have with one another, the denser the network. The density measure is widely used to analyse the cohesiveness and interaction within and between subgroups, whereas centralisation refers to the overall compactness of the network. Stochastic modelling is used to find latent classes that are based on network ties, as it often is a priori unclear which individual attributes or combinations of these influence the relationship patterns. Grouping or clustering is identified so that the actors having a similar network position belong to the same latent class. The analysis is based on a model, which assumes that the probability distribution of the relation between two persons depends only on the latent classes to which they belong and that the relations are independent from each other, referring to these classes. The stochastic blockmodel has two parts, the division of the set of actors into latent classes and the probability distribution of the relations within and between these classes. In the present study, the BLOCKS program was used for analysis. BLOCKS is a Bayesian statistical method and part of the StOCNET program collection (Boer et al., 2007). The social network data gathered by the questionnaire were organised in three case by case matrices (collaboration, informal discussion, and relevance of informal discussion) in which the columns and rows were organised in equal order. In that way, the square matrix contains the information as self-report (in rows) and peer reports (in columns). The data can be treated either in an asymmetric (so that the row and column information may differ from each other) or in a symmetric way (so that they are the same, being symmetrised by using some criteria). For defining structural similarity, we used symmetric matrices, because the existence of a relation between two individuals in at least one direction is of relevance. For the analysis of expertise indicators, we used asymmetric matrices, because ingoing relationships and outgoing relationships have a different meaning. In addition, the data can be treated either in a dichotomous form (the tie is present or not) or in a weighted form (the strength of the tie is observed, in which a value for a link varies from 0 to 3). In our study, some variables (for example existence of a collaboration relation) were conceived as dichotomous variables, others (for example relevance of informal discussions) were conceived as weighted variables. The informal discussion matrix and the collaboration matrix were used to calculate the network positions and, moreover, to indicate centrality values of individual actors. The informal discussion relevance matrix was used as an indicator for centrality. The centrality 38 M. Rehrl et al.
measures (Freeman’s indegree values: The column sums of the network matrices) are understood as indicators of popularity in the scientific community network (Wasserman & Faust, 1994), whereas the stochastic analysis delivers a grouping variable for the study to evaluate similar network positions inside the scientific community. To conclude, three network variables were computed in the study: (1) number of collaboration partners (dichotomised Freeman’s indegree measure), (2) relevance of informal discussions reported by other community members (valued Freeman’s indegree measure), and (3) a grouping variable that indicates to which latent class the community members belong.
Results
Research Question (1): How is the Scientific Community Constructed? Density and Centrality of the Social Interaction. The informal discussion matrix and the collaboration matrix were added to create a sum matrix, which was used for subsequent analyses representing the social integration in form of informal discussion and collaboration. The density of the combined matrix is 16%. So, the interaction in this scientific community is rather sparse. The centralisation value for incoming ties (Freeman’s indegree measure) is 34%, which indicates that the network structure is only slightly centralised. Small communities are often denser than the bigger ones, especially regarding resource-demanding exchange, only for the simple reason that people have limitations in how many contacts they can maintain. However, the centralisation of the interaction can vary independent of the density. Communities may also be locally dense even when the network as a whole is sparse. Latent Network Structure. The network of ties is handled at a dyad level as a relationship of two actors. There are altogether 1326 dyads with no missing values in these. A symmetric and weighted sum matrix is used when analysing the data. (The maximum value was 6, the sum of 3 for collaboration and 3 for informal discussion.) The data set was symmetrised by using maximum values in the sum matrix. The amount of null dyads (0,0; no mutual relationship) was 1090, valued relationships were observed in the following way: (1,1) in 40 dyads, (2,2) in 53 dyads, (3,3) in 34 dyads, and (4,4) in 109 dyads. There were no (5,5) or (6,6) dyads, which would indicate the strongest possible relationship. Therefore, the number of different types of relationships in the data set is 5. The analysis was performed by the BLOCKS program that uses random simulations. In this case, the particular Monte Carlo approach is Gibbs sampling. The randomness implies that the results vary every time the program is performed. This property is utilised so that the same calculation can be done several times to see if the results are the same. Here, the computation has been done three times, which gives confidence for the results. To find out which number of classes would be best, the analysis has been calculated to all numbers in a plausible range, from 2 to 8. To decide which would be the optimal number of classes, two parameters were calculated, Iy and Hx. The parameter Iy varies between 0 and 1. It is 0, if the relation between two network members is fully determined by the two classes to which they belong. The larger the information set, the less the latent classes tell about the relations between the two members. The entropy of the empirical dyad distribution is what would be obtained for the information Iy in the observations if there were only one class, and this value (here .695) serves as reference for the information values obtained for more than one class. The parameter Hx tells about clarity of the block structure. It varies between 0 and 1. If it is 1, there is no block structure at all, and if it is 0 for each pair of members, it is certain whether they belong to the same latent class or not (Nowicki & Snijders, 2001). The values of the information Iy and the parameter Hx, expressing the clearness of the block structure for each class, are presented in table 2. Experts in Science 39
Table 2. Parameters Iy (Information) and Hx (Block Clearness) for the Class Structure, Separately Computed for 2- to 8-Class Solutions (N = Number of Classes).
N Iy Hx 2 .5697 .1790 3 .5363 .2624 4 .5220 .3353 5 .5062 .2162 6 .5045 .2154 7 .5039 .2153 8 .5040 .2152
Table 3. Density Values Inside and Between Latent Classes – Five-Class Solution Class 1 Class 2 Class 3 Class 4 Class 5 Class 1 (N = 6) 93% 12% 60% 41% 71% Class 2 (N = 26) 12% 2% 5% 5% 7% Class 3 (N = 7) 60% 5% 36% 6% 61% Class 4 (N = 9) 41% 4% 10% 67% 61% Class 5 (N = 4) 62% 10% 50% 50% 67%
The results show that the information Iy contained in the latent class structure (about the probability distribution of the relations) decreases when N goes from 2 to 7. In addition, the clearest class structure, as expressed by Hx, is obtained for the two-class solution. It is again better when N > 4. The two-class solution distinguishes (only) the active and passive SIG 14 members. If we were to take more than five classes into the analysis, there would be classes, which consist only of one actor. Therefore we begin the analysis with a five- class solution to get a more detailed picture of various structural positions in the network. The ties between the five classes in terms of the density are presented in table 3. The diagonal density values of table 3 indicate that classes 1, 4 and 5 have a large internal cohesion, which indicates that there are plenty of ties inside the class. In class 3 the internal cohesion is moderate and in class 2 very low. Very low density values show that the members of the class 2 are not connected to each other. Further, classes 1, 3 and 5 are closely connected with each other. Class 2 is only weakly tied to any other class, and it is also internally sparse, almost empty. In addition, there is a moderate connection between classes 4 and 5. Next we study the five-class solution to find out how the network positions are related to individuals’ attributive properties, such as seniority (professional years) of the members (table 4). The results of the attributive properties indicate differences between the classes. It is obvious that the way interaction is patterned in a scientific community cannot be explained by the measured attributive properties only. The networking connections rise partly from national collaborations and geographical neighbourhood so that the national
Table 4. Means of the Attributive Data (Standard Deviations in Brackets) – Five-Class Solution
Class 1 Class 2 Class 3 Class 4 Class 5 N = 6 N = 26 N = 7 N = 9 N = 4 4 males 10 males 7 males 2 males 3 males M (SD) M (SD) M (SD) M (SD) M (SD) Professional qualification (1–4) 3.7 (0.8) 2.5 (1.2) 3.9 (0.4) 1.8 (1.3) 3.5 (1.0) Professional years (1–3) 2.8 (0.4) 2.2 (0.8) 2.9 (0.4) 2.0 (0.7) 3.0 (0.0) SIG years at 2006 (0–3) 2.7 (0.5) 1.8 (0.7) 2.7 (0.5) 2.0 (0.5) 3.0 (0.0) Attendance in SIG 3.2 (1.7) 0.7 (1.0) 2.3 (1.7) 3.0 (1.9) 2.8 (2.2) conferences 2002–2010 40 M. Rehrl et al.
networks may form a basis for collaboration. This is especially true with class 4 members that come from the same country, except one member coming from elsewhere. However in most of the classes the members represent two or more countries. The class 2 representing loosely connected members, is internationally the most diversified of the five classes. Central network members can be found in three classes, classes 1, 3 and 5. These classes mainly consist of male professors, whereas females, PhD students and post-docs can mostly be found in classes 2 and 4. However there were some males, professors and senior researchers in the classes 2 and 4 as well. When we sought explanations for grouping, we noticed that it was mainly the theoretical orientation and research focus that differentiated members of the classes 1, 3, and 5. In class 1 there are researchers publishing in the fields of professional and vocational education, class 3 is an internationally heterogeneous group of popular scientists who focus on applying mainly socio-cultural theories on varying learning contexts. The members of class 5 have studied cognitive aspects of expertise. Class 4 includes scientists who have focused on workplace learning, networking, and collaborative learning. There were no clear joint themes among the researches of class 4. Class 2 consists of members who have only loose connections to the SIG 14 community; it is internationally diversified as well as with regard to the research topics. Class 5 members are visible and popular networkers of the community and they come from three countries of the SIG 14 community. To conclude, the most active members in SIG 14 community belong to the classes 1, 3, 4 and 5. The loosely connected scientists in class 2 have participated only seldom in the conferences and are only seldom reported to be sources for advice and knowledge exchange by other members of the community. They are not intensively connected to each other, but rather to the central actors of the field. In this way, the scientific network seems to have a core-periphery model (Crowston, Wei, Li,& Howison, 2006; Moody, 2004) where the most central persons work together and construct the core of the whole community whereas looser members make the periphery having ties toward the centre.
Research Questions (2–4): How Does the Network Position Predict Scientific Visibility? Latent Classes and Scientific Visibility (Research Question 2). Based on the density values between classes the highly overlapping classes 1, 3 and 5 were combined for further analysis. In the subsequent analysis the combined (new) class 1 (N = 17) represented highly networked senior researchers, class 2 (N = 26) consisted of loosely connected members, and class 3 (N = 9), the former class 4, was mainly built around one nation’s young researchers. The average number of citations (classified in ten groups) of the three classes in 2006 and 2012 are presented in figure 1. One-way ANOVA revealed a significant difference between the classes in 2006 citations, F(2, 49) = 8.23, p < .001. Bonferroni post hoc analyses showed that the only significant difference (p < .001) was between classes 1 and 2. In 2012 citations there was a significant difference between the classes, F(2, 49) = 17.19, p < .001. Post hoc analyses revealed that there were significant differences between class 1 and class 2 (p < .001), between class 1 and class 3 (p < .001) and between class 2 and class 3 (p < .05). The effect size (eta-squared) was 0.31. Repeated measures analysis of variance indicated a statistically significant main effect of time, F(1, 49) = 117.10, p < .001, and interaction effect of time and class, F(2, 49) = 7.76, p < .001. The number of citations increased in all groups, but the increase was stronger in the classes 1 and 3. Even if class 1 represented well-established senior members of the community and class 3 consisted of younger scholars, they both included active and well- networked members of the scientific community. Experts in Science 41
Figure 1. Classified Google Scholar citations at two measurement points (year 2006, year 2012). Three- class solution (N1 = 17, N2 = 26, N3 = 9).
Personal Variables (Attributes), Network Position and Scientific Visibility (Research Questions 3 and 4). In this study scientific visibility was measured longitudinally in terms of citations in the Scholar Google database. In addition, the number of citations and the h- index in the year 2012 were used as indicators of researchers’ scientific visibility. Researcher’s h-indexes in 2012 were significantly predicted by attributive data (seniority, professional qualification, number of memberships in scientific communities, attendance of SIG conferences) and by a person’s status in the social network of the scientific community (SIG14) measured in 2006. The network status variable consisted of the indegree values based on the question “With whom do you discuss your own research projects and outcomes?” (0 = never, 1 = once, 2 = several times, 3 = regularly). Only this variable, describing the communication activity within the network, was used in the regression analysis because the network analysis variables correlated highly (.85–.99) with each other. The final model based on the participants’ centrality within the discussion network in 2006, explained 41% of the variance of the h-index six years later (table 5). The only attributive variable, which remained a significant predictor after the network position variable was added in the model, was the variable describing participants’ professional qualification (that is whether the actor was a PhD student, a researcher, an assistant professor or a professor).
Table 5. Regression Model of Variables Assessed in 2006 Predicting the h-Index in 2012 Unstandardised Standardised Model t p coefficients coefficients B S.E. β (Constant) -1.134 2.862 -0.396 .694 Network status 0.385 0.108 0.417 3.553 .001 Professional qualification 3.085 1.003 0.361 3.074 .003 Note. Dependent variable: h-index. 42 M. Rehrl et al.
The results show that variables describing a subject’s network position and activity in scientific communities are the strongest predictors of further development of scientific visibility measured by the h-index.
Discussion The aim of this study was to describe researchers’ different network positions in a scientific community and to analyse how personal attributes on the one hand and network positions on the other hand predict the development of later scientific visibility. The scientific community studied was the Learning and Professional Development special interest group of the EARLI. The results of SNA indicated that the members of the SIG did not form a highly coherent group. The moderate density and centralisation values indicated that the members do have contacts with each other but they probably form several subgroups with diverse network positions. This was confirmed with the BLOCKS analysis, which classifies participants into latent classes according to the structural equivalence of their network positions. The five classes identified in the analysis were characterised mainly by the members’ scientific focus, their seniority, their nationality, and the density of network connections within the SIG community. Three of the classes represented established senior researchers focusing on different research topics and theoretical approaches. One of the classes consisted of active and well networked, mainly junior members of the community, and one represented loosely connected researchers who are members in the SIG but have relatively weak contacts within this community. Their main scientific focus obviously is in other research areas than those represented by the SIG. The results showed that the strength of the network position and the level of professional qualification were the strongest predictors of later scientific visibility measured in terms of the h-index of publications. Personal attributes were not as important predictors of later scientific success as variables describing the persons’ position in the scientific network. This study focused mainly on the collaboration and network connections within one special interest group of a bigger scientific association. For some people the SIG community is their main scientific community while for many this particular community is more peripheral in their scientific activity. Thus, the further scientific success should not only be predicted by the network position within the SIG community but also by membership in other scientific communities outside the SIG. The result of the study supports theoretical assumptions about the importance of personal network connections for scientific success (Gruber et al., 2008) as well as some earlier empirical results (White et al., 2004). What is important in these studies is the more detailed analysis of the nature of network connections and activity in scientific communities. The results indicate that a strong position in a local scientific institution is not a necessary or sufficient predictor of scientific visibility. This study has some methodological limitations, which have to be taken into account when interpreting the results. When the first data set was collected in 2006 there was no citation database available, which would have sufficiently covered the typical publications of the field. Google Scholar was the best option at that time but it was nevertheless far away from an optimal database. Later the coverage of Google Scholar has strongly developed and a part of the increase of citations is due to these changes in the database. When the 2006 data set was collected, the h-index was not very widely known and this information was not collected. Thus, the most relevant scientific visibility indicator was only available for the 2012 data. In spite of the fact that the h-index is a well-balanced indicator of scientific visibility and takes into account simultaneously individual papers’ number of citations and the number of frequently cited papers, it does not solve all the problems of citations counts. The h-index in particular is very sensitive to the differences of publication traditions in different sub-disciplines. Another limitation of the study is that the design does not allow for a study of causal relations. In the longitudinal design it was Experts in Science 43 possible to show that the network variables predicted later scientific visibility but it is not possible to conclude that a strong network position would be the cause of later scientific visibility. Other variables such as local financial conditions may enable or disable both, active participation in international networks and publishing in well-acknowledged international journals. Nevertheless the study clearly reveals that it is important for one’s scientific career to have good network connections. This is related to being visible in research communities, and it perhaps influences visibility. Both the quality of one’s scientific contributions and the participation in scientific networks contribute to the professional development. This is in particular true in research areas in which researchers from many countries contribute to the scientific advancement. Both the increasing internationalisation of academia and the availability of IT technologies that facilitate exchange of partners beyond geographical boundaries are factors that enable researchers to communicate and to participate actively in research communities. It might be good advice to Ph.D. supervisors to support the young researchers to join international research networks early in their career and to identify relevant partners in the networks who can support their academic development through collaboration and through critical feedback. It is not insignificant, to whom we are listening and who belongs to our reference group. We trust that the composition of the group of authors of this paper is a good example showing that such a strategy can yield interesting contributions both to the individual research profile and to the scientific development of research networks.
Acknowledgment This paper was written during a sabbatical stay of the last author as Visiting Professor at the Centre for Learning Research, University of Turku, Finland.
References van Aalst, J. (2010). Using Google Scholar to University of Chicago Press. estimate the impact of journal articles in Crowston, K., Wei, K., Li, Q., & Howison, J. education. Educational Researcher, 39, 387– (2006).Core and periphery in Free/Libre and 400. Open Source software team communications. Agnew, N. M., Ford, K. M., & Hayes, P. J. (1994). HICSS ‘06.Proceedings of the 39th Annual Expertise in context: Personally constructed, Hawaii International Conference on System socially selected and reality relevant? Sciences, 6 (no. 118.1). Washington: IEEE International Journal of Expert Systems, 7, 65– Computer Society. 88. Diem, A., & Wolter, S. C. (2011). The use of Bar-Ilan, J. (2008). Which h-index? A comparison of bibliometrics to measure research WoS, Scopus and Google Scholar. performance in education sciences. Aarau: Scientometrics, 74, 257–271. Swiss Coordination Centre for Research in Boer, P., Huisman, M., Snijders, T. A. B., Steglich, C. Education. E. G., Wichers, L. H. Y., & Zeggelink, E. P. H. Ericsson, K. A. (2009). Enhancing the development (2007). StOCNET: An open software system for of professional performance: Implications the advanced statistical analysis of social from the study of deliberate practice. In K. A. networks. Available from Ericsson (Ed.), Development of professional www.gmw.rug.nl/~stocnet/StOCNET.htm expertise: Toward measurement of expert (most recent access: May24th, 2013) performance and design of optimal learning Bornmann, L., & Daniel, H. D. (2007). What do we environments (pp. 405–431). New York: know about the h index? Journal of the Cambridge University Press. American Society for Information Science and Ericsson, K. A., Roring, R. W., & Nandagopal, K. Technology, 58, 1381–1385. (2007). Giftedness and evidence for Burt, R. S. (1987). Social contagion and innovation: reproducibly superior performance: An Cohesion versus structural equivalence. The account based on the expert performance American Journal of Sociology, 92, 1287–1335. framework. High Ability Studies, 18, 3–56. Carolan, B., & Natriello, G. (2005). Data mining Evans, T. S., Lambiotte, R., & Panzarasa, P. (2011). journals and books: Using the science of Community structure and patterns of networks to uncover the educational research scientific collaboration in business and community. Educational Researcher, 34(3), 23– management. Scientometrics, 89, 381–396. 33. Feltovich, P. J., Prietula, M. J., & Ericsson, K. A. Crane, D. (1972). Invisible colleges. Chicago: (2006). Studies of expertise from 44 M. Rehrl et al.
psychological perspectives. In K. A. Ericsson, governance of exchange relationships. N. Charness, P. J. Feltovich, & R. R. Hoffman Administrative Science Quarterly, 37, 76–104. (Eds.), The Cambridge handbook of expertise Lievrouw, L. A. (1989). The invisible college and expert performance (pp. 41–67). reconsidered. Bibliometrics and development Cambridge: Cambridge University Press. of scientific communication theory. Francis, J. R. (1989). The credibility and Communication Research, 16, 615–628. legitimation of science: A loss of faith in the Lievrouw, L. A. (1990). Reconciling structure and scientific narrative. Accountability in Research: process in the study of scholarly Policies and Quality Assurance, 1, 5–22. communication. In C. L. Borgman (Ed.), Frank, K. A. (1996). Mapping interactions within Scholarly communication and bibliometrics and between cohesive subgroups. Social (pp. 59–69). Newbury Park: Sage. Networks, 18, 93–119. Lomi, A., Snijders, T. A. B., Steglich, C. E. G., & Torló, Glänzel, W., & Moed, H. F. (2002). Journal impact V. J. (2011). Why are some more peer than measures in bibliometric research. others? Evidence from a longitudinal study of Scientometrics, 53, 171–193. social networks and individual academic Gruber, H., Lehtinen, E., Palonen, T., & Degner, S. performance. Social Science Research, 40, (2008). Persons in the shadow: Assessing the 1506–1520. social context of high abilities. Psychology Moody, J.(2004). The structure of a social science Science Quarterly, 50, 237–258. collaboration network. American Sociological Hansen, M. T. (1999). The search-transfer problem: Review, 69, 213–238. The role of weak ties in sharing knowledge Mulkay, M. J., Gilbert, G. N., & Woolgar, S. (1975). across organization subunits. Administrative Problem areas and research networks in Science Quarterly, 44, 82–111. science. Sociology,9, 187–204. Harzing, A.-W.(2010). The Publish or Perish book. Norris, M., & Oppenheim, C. (2007). Comparing Melbourne: Tarma. alternatives to the Web of Science for Hirsch, J. E. (2005). An index to quantify an coverage of the social sciences’ literature. individual’s scientific research output. Journal of Informetrics, 1, 161–169. Proceedings of the National Academy of Nowicki, K., & Snijders, T. A. B. (2001). Estimation Sciences of the United States of America, 102, and prediction for stochastic blockstructures. 16569–16572. Journal of the American Statistical Association, Kajikawa, Y., Ohno, J., Takeda, Y., Matsushima, K., & 96, 1077–1087. Komiyama, H. (2007). Creating an academic Palonen, T., & Lehtinen, E. (2001). How to illustrate landscape of sustainability science: An invisible scientific communities. Higher analysis of the citation network. Sustainability Education, 42, 493–514. Science, 2, 221–231. Price, D. J. de S. (1986). Little science, big science ... Kienle, A., & Wessner, M. (2006). The CSCL and beyond. New York: Columbia University community in its first decade: Development, Press. continuity, connectivity. International Journal Wasserman, S., & Faust, K. (1994). Social network on Computer-Supported Collaborative analysis. Methods and applications. Learning, 1, 9–33. Cambridge: Cambridge University Press. Larivière, V., Archambault, É., Gingras, Y., & White, H. D., Wellman, B., & Nazer, N. (2004). Does Vignola-Gagné, É. (2006). The place of serials citation reflect social structure? Longitudinal in referencing practices: Comparing natural evidence from the “Globenet” sciences and engineering with social interdisciplinary research group. Journal of sciences and humanities. Journal of the the American Society for Information Science American Society for Information Science and and Technology, 55, 111–126. Technology, 57, 997–1004. Zuccala, A. (2006). Modeling the invisible college. Larson, A. (1992). Network dyads in Journal of the American Society for Information entrepreneurial settings: A study of the Science and Technology,57, 152–168.
The Authors
Monika Rehrl (born 1977, doctoral student) has been assistant at the Department of Education in the University of Regensburg, Germany. Currently she is on parental leave and works to finish her doctoral thesis. Her main research topic concerns social network analysis in combination with expertise development and vocational learning processes.
Experts in Science 45
Tuire Palonen (Ph.D.) is Senior Research Fellow at the Centre for Learning Research and Teacher education at the University of Turku, Finland. She is also Adjunct professor for the University of Jyväskylä. During her career, she has been interested in expertise research and Social Network Analysis, focusing on the investigation of workplace learning and communication inside work organizations. This work is partly done by the Turku University spinoff company, Spindel, the partner of which she is. ([email protected] and [email protected])
Dr. Erno Lehtinen is a professor of education at the University of Turku. Since 2010 he has been an Academy Professor. He has worked as a teacher and researcher in several universities in Finland, other European countries and USA. Professor Lehtinen was the Vice-Rector of the University of Turku 2003-2010 and the President of the European Association for Research on Learning and Instruction (EARLI) 2001–2003. He has been adviser of many national and international organizations including EU, OECD, European Science Foundation, US National Science foundation. Currently he is Editor-in-Chief of the new open access journal of EARLI, Frontline Learning Research (www.fontlinelearningresearch. org). Lehtinen has published more than 300 scientific articles and books about theories of learning and expertise, mathematics education and educational technology.
Hans Gruber (born 1960) is Professor of Educational Science at the University of Regensburg (Germany) since 1998 and Senior Fellow at the Faculty of Education, University of Turku (Finland) since 2013. His main research interests lie in the fields of professional learning, expertise, workplace learning, social network analysis and higher education. He is member of the Review Board “Education Sciences” of the German Research Foundation (Deutsche Forschungs- gemeinschaft) and President-Elect of the “European Association for Research on Learning and Instruction” (EARLI) where he is also founding chair of the special interest group “Learning and Professional Development”. Besides he serves as reviewer for many international journals, book series and research organizations.
46 M. Rehrl et al.
Talent Development & Excellence Outstanding Human Behavior 47 Vol. 6, No. 1, 2014, 47–55 Brain Cancer, Meat Glue, and Shifting Models of Outstanding Human Behavior: Smart Contexts for the 21st Century Jenna McWilliams1* and Jonathan A. Plucker2
Abstract: This article draws on recent research in educational psychology, the learning sciences, literacy studies, and media studies to argue for an approach to talent identification and development that takes into account cultural shifts resulting from new media practices. Specifically, we will make the following arguments: That research in talent identification and development, having embraced the so-called ‘social turn’ (Gee, 2000; Latour, 1992) in social sciences research, must now take into account the ‘digital turn’ (Mills, 2010) that attempts to consider how new technologies mediate human behavior in new and important ways, as well as how new practices are emerging with and alongside these new technologies; that while an emphasis on individual talent development is essential, this emphasis must equip individuals with a disposition toward collaboration and collective meaning-making; and that new equity issues have emerged around talent identification and development as a result of the digital turn.
Keywords: talent development, technology, smart contexts
The Shifting Horizon of Research on Outstanding Human Behavior In 2012, 39-year-old digital artist Salvatore Iaconesi was diagnosed with brain cancer. His response was equal parts typical and unique. In blog posts, a Ted talk, and news articles, he described reacting as those who receive a cancer diagnosis commonly do: with shock, confusion, and fear. He described feeling depersonalized by a medical establishment that turned his very human, unique experience into an equation: “You have a disease because you have some symptoms, and there’s a diagnosis, and then there’s therapy.” Since Iaconesi describes himself as “engineer, artist, professor and hacker” (Iaconesi, 2013), his next steps – as outside of the norm as they were – were perhaps a matter of common sense: He hacked his own medical records and made them available to anyone who wanted to see them. He collected all of the files that detailed, described, and diagnosed his illness, decrypted them using specialized software, and translated them into a language that was readable by non-medical professionals. Then he posted everything online with a plea: Grab the information about my disease, if you want, and give me a CURE: create a video, an artwork, a map, a text, a poem, a game, or try to find a solution for my health problem. Artists, designers, hackers, scientists, doctors, photographers, videomakers, musicians, writers. Anyone can give me a CURE. (Iaconesi, 2012) Iaconesi, a well-known digital presence across multiple online and offline artist, programming, and technology-related communities, leveraged his status to make a public plea across several well-known digital media platforms. In response, he has received advice and support from more than 200,000 people – including more than 60 doctors. Iaconesi has used this guidance to establish a treatment plan that integrates a variety of surgical, oncological, homeopathic, and lifestyle-based strategies – because of the global
1* Corresponding author. Indiana University, School of Education, 201 N. Rose Ave, Bloomington, IN 47405, USA. Email: [email protected] 2 University of Connecticut, USA
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
48 J. McWilliams & J.A. Plucker reach of Iaconesi’s message, he explained, “[t]he solutions came from all over planet, spanning thousands of years of human history and traditions” (Torgovnick, 2013), and were very unlikely to have been offered had he decided to work only with his local cancer treatment team. Salvatore Iaconesi is what we might call a “talented” artist, especially if we take up the model of giftedness as potential that is developed and translated into achievement (Simonton, 1999, 2010; Subotnik, Olszewski-Kubilius, & Worrell, 2011). He is a faculty member at three major Italian universities, and in 2013 he received an Eisenhower Fellowship, which rewards individuals who have demonstrated impact on their field. The next step according to this model, of course, is eminence, and Iaconesi’s ability to attain this next step will likely be based in large part on the degree of success of his crowdsourced cure in addition to his ability to “contribut[e] in a transcendent way to making societal life better and more beautiful” (Subotnik et al., 2011, p. 7). Yet Iaconesi’s “open source cure” project, arguably the most important project of his entire career, can be considered the product of his talent only in the loosest sense. In fact, most of the creative work – the ‘talent’ – that has emerged through this project has come from others: Visual representations of Iaconesi’s brain have been developed by artist- participants; written testimonies offered by thousands of people; hundreds of poems crafted by sympathetic readers: None of this was created by Iaconesi himself. Iaconesi was the crucial factor in this creative explosion, however. Without his specific set of skills – skills that, importantly, crossed multiple domains – the resulting creative output would never have been possible. He did not generate his own cure, but his prominent position within multiple professional, creative, and socially networked communities (built, it must be said, on his own dedication to his work over many years) made the generation of his cure possible. Where, then, do we locate talent in Iaconesi’s story? And what about the accomplishments that Iaconesi’s project gave rise to, but that cannot, strictly speaking, be considered works of art? What about the collaborative efforts by physicians, oncologists, surgeons, and other medical professionals to pool resources and knowledge about the brain, its cancers, and Iaconesi’s cancer in particular? Or the computer science expertise – not artistic talent, but programming fluency – that made it possible for Iaconesi to ‘break into’ his medical records in the first place? If we can consider this an exemplar model of talent and achievement, then in what domain? What can Iaconesi’s experience teach us about the shifting landscape of “talent,” and about how we must shift our approaches to talent development? This article draws on recent research in educational psychology, the learning sciences, literacy studies, and media studies to argue for an approach to talent identification and development that takes into account cultural shifts resulting from new media practices. Specifically, we will make the following arguments: That research in talent identification and development, having embraced the so-called ‘social turn’ (Gee, 2000; Latour, 1992) in social sciences research, must now take into account the ‘digital turn’ (Mills, 2010) that attempts to consider how new technologies mediate human behavior in new and important ways, as well as how new practices are emerging with and alongside these new technologies.; that while an emphasis on individual talent development is essential, this emphasis must equip individuals with a disposition toward collaboration and collective meaning-making; and that new equity issues have emerged around talent identification and development as a result of the digital turn.
Accounting for the ‘Digital Turn’: Revisiting Smart People or Smart Contexts The story of Salvatore Iaconesi is both unique and increasingly common in a digitally mediated, distributed-intelligence social context. The technology theorist Clay Shirky (2010) argues that cheap and widely available software and digital tools provide people Outstanding Human Behavior 49 with the means; the intrinsic desire for connection and to be appreciated for one’s skills and contributions provides people with the motive; and digitally networked technologies provide people with the opportunity to make and distribute projects on a never-before- seen scale. Whereas the dominant model of genius has been, for at least the last 150 years, that of the solitary genius toiling alone, a culture of increasing collaboration and collective problem-solving is quickly displacing that model. Increasingly, scholarship in the social sciences has attempted to account for this shift – with scholarship on talent identification and development in tow. The change in conceptions of talent, however, have been largely confined to a refinement of the role of social context in defining and delimiting talent, creativity and genius, and less on a serious consideration of the role of digital technologies in shaping shifts in cultural norms about intelligence. The final decade of the 20th century saw a so-called social turn in scholarship on learning, cognition, and teaching (Gee, 2000; Latour, 1992), characterized by a shift away from individualistic notions of intellect and toward a view of knowledge as socially constructed and contested. Across the social sciences, this turn led to an increased focus on the role of context in shaping human activity. In educational research, the social turn has its most prominent roots in the work of Soviet theorists Vygostky (1978) and his student, Leont’ev (1978; 1989), whose emphasis on the dialectical relationship between individuals and cultural forces gave rise to a class of sociocultural theories whose aims are to situate cognition outside of individual minds, situating it instead across individuals and the cultural artifacts and tools with which they interact (Kaptelinin & Nardi, 2006; Wertsch, 1995). In their call for an increased focus on the role of context in talent identification and development, Barab and Plucker (2002) briefly describe dominant ideas within several major strands of sociocultural theory, using these to argue that any activity that is considered “talent” is essentially transactional in nature: It is the product of an individual who has been located within a context that offers opportunities for the individual to act in ways that can be appreciated as exceptional. The authors describe talent, then, as
a set of functional relations distributed across person and context, and through which the person-in- situation appears knowledgeably skillful. In other words, ability and talent arise in the dynamic transaction among the individual, the physical environment, and the sociocultural context. (p. 174)
In the last decade, this view of talent as situated and distributed has increasingly been taken up within the literature, although not without tensions. These tensions are exemplified in Subotnik et al’s (2011) recent exhaustive review of scholarship in this area. The authors note that changing social contexts alter how talent can be defined and cultivated – as, for example, in the emergence of new domains such as snowboarding or computer programming as well as in shifts in what might ‘count’ as giftedness in already- existing domains such as swimming. This suggests a view of talent as socially defined, even as the authors maintain a definition of giftedness as highly individualistic and isolable from social norms. This tension is at the root of a significant body of recent research in talent identification and development (see also Subotnik, Olszewski-Kubilius, & Worrell, 2012; Worrell, Olszewski-Kubilius, & Subotnik, 2012; and related commentaries). A number of scholars outside the field of gifted education accentuate the social in the development of talent (e.g., Govaerts, Kyndt, Dochy, & Baert, 2011; Kim & Hannafin, 2011; Sadler, 2009; Zheng, Young, Wagner, & Brewer, 2009), and some theoretical developments over the past decade suggest that researchers within the field are also moving in this direction (e.g., Dai & Renzulli, 2008; Renzulli, 2002). Perhaps the most relevant theoretical development in this vein is the Actiotope Model, which specifically posits ways in which various levels of groups and the individual interact and mutually adapt to develop talent (Ziegler, 2005; Ziegler, Stoeger, & Grassinger, 2011; Ziegler, Stoeger, & Vialle, 2012). The growing acceptance of the role of the social in delimiting and determining the emergence, identification, and development of talent has played a significant and important role in moving the field forward. 50 J. McWilliams & J.A. Plucker
It is time now for the field of giftedness research and talent development to account for the “digital turn” (Given, 2006; Mills, 2010; Uricchio, 2009) in the social sciences. This turn attempts to account for shifts in valued cultural practices that have emerged around and through digitally networked technologies. Increasingly in education, science and technology, the arts, and the workplace, individuals are being called upon to both interpret and represent ideas in multiple modes (Jewitt & Kress, 2003); to follow and participate in communication threads that cross multiple media platforms (Hull & Katz, 2006; Jenkins, 2006; Jenkins, Ford, & Green, 2012; Lan, 2013); and to work collaboratively to complete personally and socially meaningful projects (Jenkins, Purushotma, Weigel, Clinton, & Robinson, 2009). Success in these areas requires an ability to navigate communities and information sources that rely heavily on text-, image-, and video-based communication formats. These formats are characterized by a high degree of persistence, searchability, replicability, and scalability (boyd, 2008) and call for new modes of thought in order to effectively navigate, manipulate, and circulate ideas and work through these platforms. From this perspective, literacy – and, we argue, talent – is dependent on what Lankshear and Knobel (2006) call a combination of “new technical stuff” and “new ethos stuff.” The new technical stuff is comprised of the specific skill sets that enable support facility with new technologies – and an ability to adopt and make effective use of a new piece of software, computer or cellphone interface, video game or console, and so on. The new ethos stuff features a shifting mindset about what constitutes knowledge, participation, and valuable activity. For those who have adopted a “new ethos” mindset, expertise and authority are viewed as distributed across people and technologies, texts are not stable but flexible and manipulable, and contributions develop social value as they become circulated widely. Taken together, the technical and social practices that comprise fluency with new technologies have been labeled multiliteracies or multimodal literacy (Cazden et al., 1996; Cope & Kalantzis, 2000; Luke, 2000), new media literacies (Jenkins et al., 2009), or computational literacy (DiSessa, 2001; Wing, 2006).
New Dispositions, Transforming Domains: Collaboration, Cooperation, and Reading with Mouse in Hand It is not simply that new combinations of technical and social skills are required for success within various domains, however; the emergence of these new skills are simultaneously giving rise to new domains and shifting the very notion of what counts as a domain. Certainly, as Subotnik et al. (2011) note, it is important to account for and establish criteria for talent in new domains that are emerging as a result of the emergence of digitally networked technologies; but these shifts are not contained neatly within domains: These new technologies are leading to a sea change in what it means to learn, work, and achieve across all areas of public and private life. As Subotnik et al. (2011) point out, an important issue in talent identification and development is the emergence of new domains; many of these domains are linked to the invention and application of new technologies. In fact, the issue is even more complicated than this, since it is not simply that new domains are emerging around new technologies, but that technologies are changing what counts as talent and, perhaps, even eminence in nearly all domains. Indeed, new collaborative projects and collective knowledge-building have begun to shift what domains even are. Consider the domain of cooking. Certainly, new technologies – better cookware, more precise ovens, and so on – have led to some significant changes in how chefs prepare cuisine. The bigger change, however, is in how world-class chefs think about food, where they draw their inspirations, and what ingredients they use. Recent advances in molecular gastronomy – the study of the physical and chemical transformation of food through cooking – have led to complicated taxonomies of cuisine and allow chefs to work, with increasing precision, at the level of the chemical reactions of ingredients (McGrane, 2007). Outstanding Human Behavior 51
Increased access to global food sources has led chefs to experiment with a wider variety of raw materials (or, conversely, to focus on locally produced ingredients), increased their ability to communicate with other chefs, allowed them to visit kitchens around the world and has made it possible for chefs to build their brand. Examples abound in the culinary world. Paul Liebrandt, the subject of a recent documentary (A Matter of Taste: Serving Up Paul Liebrandt), is known as a talented young chef, the youngest ever to earn a 3-star rating from the New York Times (Moskin, 2009). His newest endeavor, the New York-based restaurant Corton, maintains its own 3-star rating from the New York Times through the creative combination of haute cuisine staples with a variety of medium- and low-brow inspirations from around the world. A recent review waxed eloquent about Corton’s “cotton candy sushi,…tuiles that taste like deep-fried fruit roll-ups; kaffir lime crisps recalling Trix cereal (but in a good way) and a pungent mornay sachet garnished with micro red shiso” (Sutton, 2013). Liebrandt’s particular talent is in his ability to balance innovation with flavor – a balance that draws on a vast array of ingredients and techniques. Wylie Dufresne, another world-class chef, is known for his creativity with new culinary technologies: liquid nitrogen, a vacuum chamber machine, and transglutaminase – also known as ‘meat glue.’ Using these and similar technologies, Dufresne creates counterintuitive combinations: shrimp spaghetti, cylinders of steak, peanut butter noodles. As Liebrandt noted in a recent New York Times interview, what makes a chef world-class is the ability to synthesize an increasingly lengthy – and increasingly technology-laden – culinary history, since “[t]oday’s chefs must absorb everything that’s gone before”(Moskin, 2009). At this rate, there’s no telling what tomorrow’s world-class chef will look like. Twenty years ago, a world-class chef was x; today it is y. Tomorrow it may be z. It is not only that valued practices within domains are shifting, but also that we are seeing a shift in what counts as a domain. Salvatore Iaconesi, in his efforts to cure his brain cancer, has undoubtedly accomplished something of tremendous cultural value – but in what domain? Several visual representations of his tumor have been developed, some quite elegant; does that make his an accomplishment of art? With help from colleagues, Iaconesi hacked into his own medical records – hacked, in effect, his own brain. Does this make his an accomplishment of computer programming? Hundreds of thousands of personal writings – poetry, testimonies, words of support – have been generated by visitors to Iaconesi’s site. Does this make his an accomplishment of the written word? Iaconesi’s goal – and his astonishing accomplishment – is stated in large bold letters at the top of his website: “We can transform the meaning of the word "cure". We can transform the role of knowledge. We can be human.” Iaconesi describes himself as an artist and hacker; his work bleeds and seeps across domains, and through them into other domains as well. There is no domain that can contain Iaconesi’s accomplishment; it is precisely the cross-disciplinarity, the collaborative effort, the distribution of knowledge across hundreds of thousands of people, that is his accomplishment. Increasingly, it is the spirit of collaboration – paired with what Santo (2011) has labeled “hacker literacy” and what McWilliams and Clinton (2013) label “reading with mouse in hand” – that helps translate potential into achievement, particularly in technology-rich domains. When people view all information as “hackable,” new projects and new possibilities emerge. To date, there are few systematic efforts to identify and develop a disposition toward tinkering with and modifying information. At the same time, although developing these individual talents is important, so is fostering a spirit of collaboration and hacker literacy to enable individuals to develop collaborative achievements. The creative cognition work of Ward and colleagues (Ward, 2007; Ward, Smith, & Finke, 1999) hints at possible interventions, as does the emphasis on creativity within frameworks for teaching 21st century skills (Partnership for 21st Century Skills, 2013) and Renzulli’s recent 52 J. McWilliams & J.A. Plucker work on talent development and social capital (e.g., Renzulli & D’Souza, in press). But the research base is surprisingly thin, especially regarding definition and evaluation of these skills and dispositions (see National Research Council, 2012).
The ‘New Hidden Curriculum’: Talent Development for Equity Jenkins et al. (2009), describing the social skills and cultural competencies that comprise the “new media literacies,” argue that these practices make up a ‘new hidden curriculum’ that shapes young people’s participation in educational, cultural, workplace, and civic activity; they call for a deeper consideration of how best to support learners in accessing this hidden curriculum. We believe this must be extended to a consideration of how best to identify and develop talent among learners. Since many of the skills and competencies that make up the new media literacies may not be practiced or encouraged in some formal classroom settings, many learners who show promise especially in new media-related domains may be overlooked for selection into gifted programs at their schools. This raises the spectre of excellence gaps, differences in the outcomes for advanced students based on demographic characteristics (Plucker, Burroughs, & Song, 2010; Plucker, Hardesty, & Burroughs, 2013; Rutkowski, Rutkowski, & Plucker, 2012). Excellence gaps are, essentially, an indicator of how communities balance equity and excellence in education and social services, as they represent differences in academic success between privileged and less privileged groups of students. For example, most countries have lower rates of academic excellence among poor students than wealthier students, and gaps can been seen across countries based on gender or immigrant status (Rutkowski et al., 2012). The United States has significant (and growing) racial excellence gaps, with students of Asian and European descent scoring at advanced levels on national tests at much higher percentages than African-American or Hispanic students. As a case in point, in elementary school mathematics, 19% of Asian-American students scored advanced on the major national achievement test in 2011, compared to 9% of White American students. Yet only 2% of Hispanic and 1% of Black students scored advanced on the same test (Plucker et al., 2013). These gaps have grown considerably over the past 20 years, in contrast to progress made at shrinking gaps at lower achievement levels. Returning to the point above about new media literacy, if such huge excellence gaps exist in many countries on skills and competencies that are addressed in most formal classroom settings, we would expect excellence gaps in non-emphasized areas like new media literacy and other 21st century skills to be even larger. Our concern here is that excellence gaps in skills and competencies necessary for success in coming years will become the domain of already-privileged groups of students, exacerbating existing excellence gaps and creating a permanent talent underclass. It is important, too, to consider the models we have chosen to discuss in this article: Salvatore Iaconesi, Paul Liebrandt, and Wylie Dufresne. In many ways, they represent a significant equity issue that new technologies have so far not resolved: In a world in which in theory, nearly everybody has the motive, means, and opportunity to develop large- scale creative and intellectual projects, the most public and celebrated of these have a white, well-educated male at the center. The online, user-generated encyclopedia Wikipedia, for example, may be one of the most widespread collaborative intellectual projects of the last decade. A small group of feminist educators has decided to combat one problematic aspect of the Wikipedia project – an absence both of content focusing on the accomplishments and lives of women and of female editors contributing to the site. Through a distributed online course, these faculty members have developed the “wikistorming project” that prepares students to contribute content about and by women (http://femtechnet.newschool.edu/wikistorming/). This project has been met with suspicion and fear by many Wikipedians (Wikipedia talk: WikiProject Feminism, 2014). Outstanding Human Behavior 53
The issue – for Wikipedians as well as for scholars of talent and creativity – is an epistemological one: What ‘counts’ as knowledge, as intellect, as genius, tends to align very closely to the kinds of knowledge, intellect, and genius that have been promoted by a Eurocentric, masculinist and rationalist pedagogical and theoretical framework (Collins, 2003; Ellsworth, 1989). As the field advances, as it comes to account for the social turn and the digital turn, it would also do well to embrace an epistemological turn that recognizes and advances a variety of models of talent and creativity.
Conclusion As of this writing, Salvatore Iaconesi is still engaging with his cancer, still working toward a cure, still asking his distributed community to help him transform what counts as knowledge, what counts as a cure, what counts as human. The implications of his project – for him, for future cancer patients, for all of us – have not yet fully emerged. Yet what is clear from his story is that new models of talent, of domain, of intelligence, are needed to account for the remarkable collaborative effort to eradicate a single tumor in the head of a single individual. As research advances, it must continue to develop and test these models, and to help to shift and refine frameworks that attempt to theorize, capture, and design for learning across a range of social contexts. This article draws primarily on popular media and limited empirical accounts of talent and gifted behavior, and as such is intended to focus more on the “whys” and less on the “hows” of an embrace of the digital turn. An important next phase is for empirical work in this area that can help detail strategies both accounting for digital and new media literacies in identifying talent and nurturing these literacies in talent development programs.
Authors’ Note The authors appreciated the feedback of the editors and reviewers, who provided several excellent suggestions for improving the manuscript. The authors are also grateful for the input of Donald Wallace, whose insights on the role of talent and creativity in the domain of cooking were invaluable.
References Barab, S. A., & Plucker, J. A. (2002). Smart people or empowering? Working through the repressive smart contexts? Cognition, ability, and talent myths of critical pedagogy. Harvard development in an age of situated Educational Review, 59, 297–325. approaches to knowing and learning. Gee, J. P. (2000). The new literacy studies: From Educational Psychologist, 37, 165–182. ‘socially situated’ to the work of the social. In boyd, d. m. (2008). Taken out of context: American D. Barton, M. Hamilton, & R. Ivanic (Eds.), teen sociality in networked publics. Ann Arbor, Situated literacies: Reading and writing in MI: ProQuest. context (pp. 16). London: Routledge. Cazden, C., Cope, B., Fairclough, N., Gee, J., Given, J. (2006). Narrating the digital turn: Data Kalantzis, M., Kress, G., . . . Nakata, M. (1996). deluge, technomethodology, and other likely A pedagogy of multiliteracies: Designing tales. Qualitative Sociology Review, 2(1), 54–65. social futures. Harvard Educational Review, Hull, G. A, & Katz, M.-L. (2006). Crafting an agentive 66(1), 60–92. self: Case studies of digital storytelling. Collins, P. H. (2003). Toward an Afrocentric feminist Research in the Teaching of English, 43–81. epistemology. Turning points in qualitative Iaconesi, S. (2012). La mia cura open source / my research: Tying knots in a handkerchief, 47–72. open source cure. Retrieved July 2, 2013, from Cope, B., & Kalantzis, M. (2000). Multiliteracies: Lit http://opensourcecureforcancer.com/ learning. Florence, KY: Psychology Press. Iaconesi, S. (2013). Ted Fellows: Salvatore Iaconesi. DiSessa, A. A. (2001). Changing minds: Computers, Retrieved July 2, 2013, from learning, and literacy. Cambridge, MA: The http://fellows.ted.com/profiles/salvatore- MIT Press. iaconesi Ellsworth, E. (1989). Why doesn’t this feel Jenkins, H. (2006). Convergence culture: Where old 54 J. McWilliams & J.A. Plucker
and new media collide. New York: NYU press. Talent on the sidelines: Excellence gaps and Jenkins, H., Ford, S., & Green, J. (2012). Spreadable the persistence of America’s talent media: Creating value and meaning in a underclass. Storrs, CT: Center for Education networked culture. New York: NYU Press. Policy Analysis, University of Connecticut. Jenkins, H., Purushotma, R., Weigel, M., Clinton, K., Retrieved from: http://cepa.uconn.edu & Robinson, A. J. (2009). Confronting the Rutkowski, D., Rutkowski, L., & Plucker, J. A. (2012). challenges of participatory culture: Media Trends in education excellence gaps: A 12- education for the 21st century: Cambridge, MA: year international perspective via the The MIT Press. multilevel model for change. High Ability Jewitt, C., & Kress, G. R. (2003). Multimodal literacy. Studies, 23, 143–166. DOI: New York: P. Lang. 10.1080/13598139.2012.735414. Kaptelinin, V., & Nardi, B. A. (2006). Acting with Santo, R. (2011). Hacker literacies: synthesizing technology. Cambridge, MA: The MIT Press. critical and participatory media literacy Lan, C.-F. (2013). Democratic education in the new frameworks. International Journal of Learning, media era: Toward a framework of democratic 3(3), 1–5. media literacy. A Publication of the Ohio Shirky, C. (2010). Cognitive surplus: Creativity and Council for the Social Studies, 50(1), 51–62. generosity in a connected age. London: Lankshear, C., & Knobel, M. (2006). Blogging as Penguin. participation: The active sociality of a new Simonton, D. K. (1999). Talent and its development: literacy. American Educational Research An emergenic and epigenetic model. Association, San Francisco, CA, 11. Psychological Review, 106(3), 22. Latour, B. (1992). One more turn after the social Simonton, D. K. (2010). Creativity in highly eminent turn: Easing science studies into the non- individuals. In J. C. Kaufman & R. J. Sternberg modern world. In E. McMullin (Ed.), The (Eds.), The Cambridge handbook of creativity social dimensions of science (pp. 272–292). (pp. 174–188). New York: Cambridge South Bend, IN: Notre Dame University Press. University Press. Leont’ev, A. (1978). Activity, consciousness, and Subotnik, R. F., Olszewski-Kubilius, P., & Worrell, F. personality. Englewood Cliffs, NJ: Prentice- C. (2011). Rethinking giftedness and gifted Hall. education: A proposed direction forward Leont’ev, A. (1989). The problem of activity in the based on psychological science. history of Soviet psychology. Journal of Psychological Science in the Public Interest, Russian and East European Psychology, 27(1), 12(1), 3–54. 22–39. Sutton, R. (2013). Four-star Corton serves sublime Luke, C. (2000). Cyber-schooling and cotton candy sushi. Bloomberg. Retrieved technological change: Multiliteracies for new from http://www.bloomberg.com/news/2013- times. In B. Cope & M. Kalantzis (Eds.), 05-15/four-star-corton-serves-sublime- Multiliteracies: Lit learning (pp. 69–91). New cotton-candy-sushi-dine.html York: Routledge. Torgovnick, K. (2013, June 14, 2013). Why I open- McGrane, S. (2007). The father of molecular sourced cures to my cancer: Salvatore gastronomy whips up a new formula. Wired. Iaconesi at TEDGlobal 2013. Retrieved from Retrieved from Wired Magazine: TechBiz http://blog.ted.com/2013/06/14/why-i- website: http://www.wired.com/techbiz/ opensourced-cures-for-my-cancer-salvatore- people/magazine/15-08/ps_foodchemist iaconesi-at-tedglobal-2013/ McWilliams, J., & Clinton, K. (2013). Conclusion: Uricchio, W. (2009). Moving beyond the artefact. In Reimagining and reinventing the English M. van den Boomen (Ed.), Digital material: classroom for the digital age. In H. Jenkins & Tracing new media in everyday life and W. Kelley (Eds.), Reading in a participatory technology (Vol. 2, pp. 135–146). Amsterdam: culture: Remixing Moby-Dick in the English Amsterdam University Press. classroom. New York: Teachers College Press. Vygotsky, L. (1978). Mind in society. Cambridge, Mills, K. A. (2010). A review of the ‘digital turn’ in MA: Harvard University Press. the new literacy studies. Review of Educational Wertsch, J. V. (1995). The need for action in Research, 80, 246–271. sociocultural research. In J. V. Wertsch, P. del Moskin, J. (2009). Paul Liebrand – At home, at last. Río, & A. Alvarez (Eds.), Sociocultural studies New York Times. Retrieved from of mind (pp. 56–74). New York: Cambridge http://www.nytimes.com/2009/04/22/dining/ University Press. 22lieb.html?pagewanted=all Wikipedia talk: WikiProject Feminism [online Plucker, J. A., Burroughs, N., & Song, R. (2010). Mind discussion forum]. (2014). Retrieved from the (other) gap! The growing excellence gap in http://en.wikipedia.org/wiki/Wikipedia_talk: K-12 education. Bloomington, IN: Center for WikiProject_Feminism#Yikes.2C_outside_gro Evaluation and Education Policy, Indiana up_planning_to_edit_Wikipedia_.22en_mass University. Retrieved from e.22 http://ceep.indiana.edu/mindthegap/ Wing, J. M. (2006). Computational thinking. Plucker, J. A., Hardesty, J., & Burroughs, N. (2013). Communications of the ACM, 49(3), 33–35. Outstanding Human Behavior 55
The Authors
Jenna McWilliams is a doctoral candidate in the Learning Sciences Program at Indiana University, focusing on applying issues of transgender identities and gender diversity, transmedia studies, and queer and trans* theory in work with elementary school students. Jenna’s interest in creativity, talent development, and excellence are tied to questions of social justice and supporting new media literacy skills, and particularly to the challenges of supporting LGBTQ learners in and outside of formal school systems.
Jonathan Plucker is the Raymond Neag Professor of Educational Leadership and Professor of Educational Psychology at University of Connecticut’s Neag School of Education. His research interests, shared in over 200 publications and supported by over $30 million in external funding, focus on talent development, creativity and intelligence, and education policy.
56 J. McWilliams & J.A. Plucker
Talent Development & Excellence Persons in the Shadow 57 Vol. 6, No. 1, 2014, 57–70 “Persons in the Shadow” Brought to Light: Parents, Teachers, and Mentors – How Guidance Works in the Acquisition of Musical Skills Andreas C. Lehmann1* and Flemming Kristensen1
Abstract: Biographies of famous musicians abound with references to innate dispositions and more or less proven anecdotal accounts, but little is said about the early social environment that was necessary to support the development of high level performers. Literature on skill acquisition and documented evidence of prodigies and high level performers supports the notion of necessary support. Gruber, Lehtinen, Palonen, and Degner’s (2008) concept of “persons in the shadow” fills the void of theorising by emphasising the importance of social agents. The present paper describes how such “persons in the shadow” might be relevant in the domain of music where training often starts early and is even more dependent on the positive responses and decisions made by the social environment. Based on the extant literature, we argue that further research ought to show that musicians’ careers are fostered by the minimising of adverse influences or the random effects of chance through constant external monitoring of the child’s progress and motivation.
Keywords: practice, skill acquisition, expert performance, music, social agents
According to his early biographer John Mainwaring, the composer Georg Friedrich Händel (1685–1759) had a difficult childhood regarding his musical activities: “The boy’s early interest in music was at first frowned upon by his father; he was denied access to musical instruments and encouraged to study law. According to Mainwaring, he practised secretly on a clavichord in the attic” (Hicks, 2013). A famous painting by Margaret Dicksee of young Händel’s family discovering the child in solitary practice in his night-gown with candlelight has become popular through the reprint of this painting in children’s books like “Pictures from the lives of the great composers for children” (Tapper, 1889). The remarkable fact here is that the child seems rather independent, self-taught, self- motivated, and maybe even self-regulated. Although this quaint anecdote about an established successful composer is uncorroborated, it raises several issues. First, it can be interpreted as a projection of nineteenth century ideas regarding the unstoppable genius who follows her or his genetic dispositions despite adverse environmental circumstances. Here, we touch upon the question of what motivates highly gifted children. Winner’s (1996, p. 4) characterisation of such children as being “precocious”, having “an insistence on marching to their own drummer,” and displaying a “rage to master” offers tentative answers to this question. Second, regardless of any controversies concerning the origins and manifestations of talents or gifts, it certainly appears that even great musicians had and still have to practice. The same can safely be assumed for other domains of expertise (Ericsson, Charness, Feltovich, & Hoffman, 2006). Lastly, it obliquely features the social environment which has been shown by much research to be of eminent importance for the development of children. In Händel’s case, the environment at the same time inhibits and also discovers the innocent young musician. Recent attempts in expertise research to study and understand the mechanisms of goal- directed, structured, deliberate practice have shed light on the importance of training
1 Hochschule für Musik, Würzburg, Germany * Corresponding autor. Hochschule für Musik, Hofstallstr. 6-8, D-97070 Würzburg, Germany. Email: [email protected]
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
58 A. C. Lehmann & F. Kristensen activities in various domains (Ericsson et al., 2006). Ericsson, Krampe, and Tesch-Römer’s (1993) groundbreaking paper in the music domain showed that the highest achieving group of young violinists studied had spent significantly more hours in solitary practice than a somewhat lower achieving group that in turn had practiced more than the lowest ranked group of violinists. The lifetime practice durations of the highest group of aspiring musicians were similar in amount and accumulation rate to those of current professional orchestra musicians. Those results have since been replicated in different domains, reviewed, and discussed extensively (Ericsson, Roring, & Nandagopal, 2007a, 2007b; Shavinina, 2009). The narrow definition of “deliberate practice” adopted by Ericsson and collaborators states that it is a “structured activity, often designed by teachers or coaches with the explicit goal of increasing an individual’s current level of performance. In contrast to work and play, it requires the generation of specific goals for improvement and the monitoring of various aspects of performance. Furthermore, deliberate practice involves trying to exceed one’s previous limits, which requires full concentration and effort. Consequently, it is only possible to engage in these activities for a limited amount of time until rest and recuperation are needed” (Ericsson & Lehmann, 1999, p. 695).1 Do musicians design those activities and persist by themselves or does their social environment play a crucial role? Several studies have shown that effort and enjoyment in practice activities are negatively correlated and that the most effortful activities are considered the most relevant for improving one’s skills (Ericsson et al., 1993; Hyllegard & Bories, 2008; Lehmann, 2002). Very rarely do we receive insights on how effort and enjoyment are negotiated or managed in families where discipline and working habits are a part of everyday life and culture (e.g. Chua, 2011, for a detailed account from an Asian family). Here, the social environment will most likely be necessary to provide positive reinforcements, supporting domain related activities, and exerting a certain amount of pressure to ensure sustained engagement in practice activities. Although training activities pervade every domain of expertise, this paper will use examples mostly from the (classical) music domain because the authors are highly familiar with those. Furthermore, systematic instruction and training in this area goes back several hundred years as documented by tutorials, treatises, and teaching materials at least from the 17th century onwards. It is clear that some of the mechanisms, especially environmental influences on the design and support of practice activities, have parallels in other domains. Furthermore, music experts in the classical music domain usually start early, similar to some athletic disciplines such as gymnastics or ballet dancing. Accordingly, practice regimes have to start often before regular formal schooling begins for the young performers. While careers in sports and dancing are relatively short, musical careers can extend into old age, making sustainable skill development from the onset extremely important. In light of the large historical increases in human performance in various domains of expertise which cannot be attributed to evolutionary changes, we have to instead assume changes in training and practice, albeit the influence of the social environment on aspiring experts (Ericsson & Crutcher, 1990; Lehmann, 2006; Lehmann & Ericsson, 1998). Pieces of music that were deemed unplayable at their times of composition and changing world records in sports bear witness to those historical changes in performances that plausibly have been mediated by cultural and social forces. The mere fact that prodigious performance in any domain emerges following societal demands or fashions (e.g. novel sports disciplines; or see Kopiez, 2011, for an example of 19th century child music virtuosi) suggests a powerful guidance of parents, teachers, and coaches.
The Concept of “Persons in the Shadow” If training begins at a young age, we can either assume that the budding expert designs his or her own practice due to some innate mechanisms without the help of the environment, or we can search for relevant input from the environment. The former Persons in the Shadow 59 hypothesis is rather implausible given what we know about the acquisition of psycho- motor skills (Rosenbaum, Augustyn, Cohen, & Jax, 2006) and about the lack of self- regulation of young children in general learning contexts (Schunk & Zimmerman, 1998). Gruson (1988) found that adult expert musicians instructed themselves and thought aloud when practicing their instrument, i.e. engaged in task-regulatory speech, while novices did not or to a lesser extent. Also, the knowledge in domains of expertise is culture- specific and highly structured so that corresponding innate mechanisms appear unlikely as a valid source of behaviour regulation. While children do come equipped to learn a language in the interaction with their environment, they probably do not come pre-wired for training chess, ballet, gymnastics or the violin. The same reasoning applies to the social environment: While caregivers have predispositions for teaching their preverbal infants how to speak and act socially (intuitive parenting, cf. Papousek & Papousek, 1995), only few probably have the skill and motivation to teach their children chess, ballet, gymnastics or the violin. Thus, regardless of how important we view the influence of innate dispositions for a particular domain, the question of how children are trained and motivated to train remains largely open. It is here that the social environment of the child becomes important. A loosely defined but important concept in this context is the “person in the shadow”, a terminology coined by Gruber, Lehtinen, Palonen, and Degner (2008). “Persons in the shadow” are social agents who act as facilitators, and whose importance for expert careers may have been underestimated in the current discussions surrounding exceptional and high abilities (Gruber et al., 2008, p. 239). Most musicians’ resumes and websites proudly mention the famous performers whose master classes have been attended; audiences applaud the performer or athlete and his or her “talent”. However, little is said about the early teachers and supporters who prepared the ground for higher levels of performance. In a similar vein, Bloom (2002, p. 468) states with regard to sports: “Many individuals, however, fail to consider the role that the coach, teacher, or mentor plays in helping the athlete achieve a high level of success.” According to Gruber et al. (2008, p. 240) the social context for the emergence of high abilities has been acknowledged in three distinct ways: “(1) distinctive family background, (2) education and training, and (3) socio-cultural context. The last two of these are not explained at all by innate talents, but rather by nurturing skills along with practice in the context.” The authors claim (p. 241) that the role of those “persons in the shadow” has to be described domain-specifically – similar to what has been said about the activities that constitute “deliberate practice” in a given domain (Ericsson & Lehmann, 1996). Gruber et al. (2008) go on to describe three case studies with adults in which they identify the relevant persons in the shadow in the domain of acquiring expert skills as a jazz music expert, in human resource consultancy, and in science (biomedicine). In all three instances, there were social agents who facilitated acquisition of expertise in systematic ways. The author concluded that “both the analysis of (1) individual strengths and of regular patterns of (deliberate) practice, and (2) the formation of one’s position in the social networks are required. The connecting entity between both parts of high ability are ‘persons in the shadow’, i.e. other parties who direct the individual’s development, design and monitor practice activities, facilitate the acquisition and application of knowledge and skills, and so on” (Gruber et al., 2008, p. 254). However, none of their examples concerned children/adolescents or a domain with extremely early start such as classical music performance.
Current Models of Giftedness Do Not Deny Social Influences Published models of giftedness and talent all include aspects of the environmental or social influences in some form without using the term “persons in the shadow”. For example, in his regularly updated model of giftedness and talent, Gagné (2004) posits “environmental catalysts” in which individuals (parents, family, peers, teachers, mentors) exert an influence on the developmental process among other environmental factors that turn natural abilities (called “gifts”) into competencies (called “talents”). “Family 60 A. C. Lehmann & F. Kristensen environment and climate” are mentioned in Heller (2001) as well as the “socio-cultural environment” in Sternberg (2003). In the Actiotope Model of Giftedness, Ziegler and Stoeger (2008) claim that high achieving children differ from lower achieving children in their learning orientation and use of their subjective action spaces. In contrast to trait-oriented models of giftedness, the learner attempts to expand his or her action space in a given domain. Since this model is difficult to validate through observation, the authors use self-reports of learners’ epistemic beliefs to measure their construct. At this point, “persons in the shadow” were not explicitly mentioned. However, more recently Ziegler and Alan (2011) have started to use an “educational capital” approach to explain differences between successful and less successful soccer players, moving their giftedness concept toward a sociological framework. Young soccer players who made it into a professional team had less economic capital but benefitted from their social capital by gaining access to training facilities and encountering coaches who supported them. This view is not entirely new: Lin (1999) reviewed the literature on social capital, which can generally be regarded as a neo- Marxian perspective made popular through the work of the French cultural sociologist Bourdieu. In essence, Lin (1999, p. 31) posits four beneficial aspects of social capital, namely (1) useful information about opportunities and choices, (2) influence on agents and decision processes (“putting in a word”), (3) certifications of the individual’s social credentials (“standing behind”), and finally (4) reinforcement of identity and recognition. Access to expert teachers and coaches have been viewed as a necessary condition in expert skill acquisition (Ericsson et al., 1993), but the social capital concept goes beyond the single force of individual teachers or coaches. It is almost thirty years since Bloom’s “talent project” (1985) investigated the lives of talented individuals in careers ranging from concert pianists to researchers in the field of neurology. He supposedly said in an interview that “We were looking for exceptional kids and what we found were exceptional conditions” (quoted in Sosniak, 2006, p. 289). If all models are compatible with the influence of social others, the question is how such influences are exerted and ultimately find their indirect effect in elite performers’ quality and quantity of training with subsequent exceptional performance.
Social Influence at the Start of Practice and Training Most children like to run and throw balls, bang around on noise-producing objects or sit down and interact with others on various types of games. The social environment watches the child act and searches for early signs of interest or ability – whatever this may be in a given historical and geographical context. It then assigns the behaviours to fields that constitute communities of practice which afford models for development, resources of support, and standards for different levels of performance (Sosniak, 2006). In this, the child is most likely seen through the eye of the adult who is projecting his or her own biographical or knowledge background onto the child. Musically interested parents see senseless banging on a pot as a precursor of outstanding rhythmic skills (maybe a drummer in the making), long fingers as suitable for playing the piano (as composer/pianist Fanny Mendelssohn’s mother surmised), or early singing attempts as precocious signs of general musicality (Sloboda & Howe, 1991). Athletically inclined parents will see jumping and running activities of their children as promising entry-points into the domain, and a competitive spirit as a guarantee for success, etc. Early starting ages have proven useful in some domains of elite performance (e.g. for playing the violin or the piano; cf. results by Ericsson et al., 1993) but the results are not unequivocal for other musical instruments, especially bigger ones such as tuba, double bass, and church organ that are generally associated with later starting ages (Jørgensen, 2001). Unfortunately, the early start also has a downside in that it favours early bloomers and shuts out late bloomers (see Wattie, Cobley, & Baker, 2008, for what we know about relative age effects); in youth sports the early bloomers might in turn suffer from too early Persons in the Shadow 61 specialisations in terms of injuries, disappointment and consequent withdrawal from sports leaving a lot of potential untapped (Gould, 2009). As a consequence, Balyi and Hamilton (2004) designed a sustainable model for long-term athletic development (LTAD) that instead looks at short-term successes concerning trainability during childhood and adolescence. Their model distinguishes between early and late specialising within different sport disciplines. “For late specialisation sports, specialisation prior to age ten is not recommended since this contributes to early athlete burn-out, drop-out and retirement from training and competition” (Balyi & Hamilton, 2004, n. p.). However, the authors do concede that the challenge for early specialisation sports such as figure skating, table tennis or gymnastics the structuring of what they call the “FUNdamental” stage, when 6 to 9 year olds learn all fundamental overall movement skills and the “learning to train” stage when 9 to 12 year olds learn all fundamental and overall sports skills. Those two stages might have to “amalgamate” into a single stage occurring much earlier. It is probably in the very beginning that caregivers exert an enormous influence. In their four-phase model of interest development, Hidi and Renninger’s (2006) theorise how the child’s initial situational interest and maintained situational interest evolves into an emerging individual interest and well-developed individual interest (p. 113). The situational interest is triggered and maintained bottom-up “through meaningful tasks and/or personal involvement” (p. 114), the individual interest can be understood as a top- down stable set of “positive feelings, stored knowledge, and stored value” (p. 114). Although “a well-developed individual interest is typically but exclusively self- generated”, it may “benefit from external support”. Following McPherson, Davidson, and Faulkner (2012) we would argue that the more the environment pays attention and supports (reinforces) the situational interest the more likely it could become an individual interest. More in-depth analyses are clearly necessary, for example to explain why children lose interest in an activity despite receiving adequate external support. Most biographies of famous musicians and athletes abound of anecdotal evidence that would support Hidi and Renninger’s model. How does the child’s interest remain? Shavinina (1999, 2007) considers a unique type of representation as the essence of giftedness. According to her, gifted persons develop particular objectivisations of the world, especially through intense training during sensitive phases. Those early acquired objectivisations allow gifted persons to predict domain-specific stimuli (such as ball trajectories in fast-paced sports, minute intonation or timing differences in music making), which even some domain experts cannot do despite large amounts of practice. In a nutshell, gifted persons see things that other people do not. This may speak for an early start, since Penhune (2011; Bailey & Penhune, 2012) offer a neuropsychological explanation supporting that a late start in the domain does not necessarily lead to similar results as an early start with the same amount of practice. This idea is consistent with reviews of cognitive, physiological, and psycho-motor adaptations of experts to their respective domains (Ericsson & Crutcher, 1990; Ericsson & Lehmann, 1996; Ericsson et al., 2007a; Gruber, Jansen, Marienhagen, & Altenmüller, 2010), especially when psychomotor skills are involved. Children from musical homes will typically view their musical activities as being a perfectly natural part of their lives – so will their parents who “discover” their children’s proclivities. In turn, such discoveries will positively forge the child’s musical self-concept and make its participation outside of the home far more likely, e.g. in school teams or choirs (Sichivitsa, 2007). Conversely, children from non-musically inclined households will have to make a musical impact on someone outside the home to receive support (Sloboda & Howe, 1991). Presumably the same would be true for sports, when parents act as models with regard to sport activities, leading to more active children compared to non-sporting families (Fredricks & Eccles, 2004). Hence, level of early performance and surrounding will interact and aptitude or interest in a domain may be co-constructed in predictable ways. 62 A. C. Lehmann & F. Kristensen
In her three-year longitudinal study Olbertz (2009) followed three aspiring music prodigies who met strict criteria of giftedness: a high achieving violinist, a child composer, and one who is more abstractly involved with music and views himself as a composer. The author found all three to have been “discovered” by their environment. As long as they were able to maintain their special status in the eye of the beholder, they were considered prodigious. However, when the children did not meet the rising expectations of their social environment, they were no longer considered musically gifted, the parents’ support vanished and so did the child’s specialness. Kopiez and Lehmann (in press) reviewed reports on three composing prodigies from the early 20th century. The prodigies’ parents were highly involved, made large sacrifices to foster their child’s development and persuaded the environment to share in their efforts. Being a prodigy has been shown to be no sure predictor of later career success (Simonton, 1991). Theoretical phase models generally posit playful periods that precede or surround the start of structured instruction in the early years (Bloom, 1985; Ericsson et al., 1993; Manturzewska, 1990). Children will initiate or be enticed in a skill domain by their social environment; statements such as “come, play a game of chess with me, grandpa”, “John is going to soccer practice, I want to go too” show emerging interest in participation. At some point the hitherto haphazard training becomes more deliberate, structured, and goal-centred. Children will then be told to practice certain amounts per day or attend training sessions regularly. This constitutes the start of a sort of apprenticeship into what Lave and Wenger (1991) have called communities of practice. From a legitimate peripheral participation they will be continuously introduced into the domain. Initially, young musicians and athletes train for relatively short periods of time, often with intermitting bouts of informal playful activities in the domain. The reason is that early stages of any skill acquisition will be effortful and characterised by strong cognitive involvement (Fitts & Posner, 1967). The teachers in early phases of musicians’ training are often child-centred and emotionally warm as Bastian (1989) found out among participants of a national German music competition (“Jugend Musiziert”). It is possible that specialist teachers for young musicians can prove to be particularly beneficial. The famous violin teacher Saßmannshaus (1993) emphasises the importance of children having a specialised master-teacher from the onset of instrumental lessons and disregards the necessity of them having to show great gifts before the age of around six. Examples of such master teachers in the area of violin are Leopold von Auer, Carl Flesch, Yuri Yankelvitch, Dorothy Delay, who not only taught conservatory students: 50% of their pupils were between the age of six and eighteen years. Interestingly, 18 of the 21 families in Bloom’s (1985) study did know of their teacher before lessons commenced, which may reflect a greater amount of cultural (educational) capital or investigative intensity by the parents of high achievers than they are initially given credit for. Research that shows how teachers come into the lives of young musicians and their families is currently lacking, but would answer many questions regarding access to expert teachers.
Social Influence on Later Stages of Skill Acquisition Over time instruction becomes more focused and leads to measurable accumulation of solitary practice during the middle or developmental years, depending on the child’s own interest and a teacher’s or coach’s demands. Ericsson et al. (1993) and Sloboda, Davison, Howe, and Moore (1996) found that daily practice durations differed with level of proficiency. Some participants were apparently more interested, more perfectionistic or in some way more driven (intrinsically or extrinsically) and invested longer hours, resulting in larger amounts of accumulated solitary practice. Anecdotal evidence from the former boxer Thomas Hearns illustrates the point of intrinsic interest in sports (cit. in Bloom, 2002, p. 475): “I learned to fight. I worked and studied it. If I got beat or did something sloppy in the gym, I’d go home and work on it until I got it right. Man, it was hard work but I didn’t want to be just good, I wanted to be the best.” Consistently, Sloboda et al. (1996) found that children who abandoned playing their instruments tended to be those who had Persons in the Shadow 63 practiced the least. However, those who practiced most were also engaged more in informal playing activities (self-guided activities unrelated to teacher-set goals) with their instruments. Could this be a symptom of a welcoming and accommodating home environment where music making is given space and valued? With time, practice durations increase, especially during specialisation and investment stages when a person has opted to become committed part-time or even full-time to the development of skills (Abbott & Collins, 2004). Common practice durations in music are not only dependent on the stage of learning but also on the particular instrument, as is the case for training durations in different athletic disciplines. Jørgensen (1998, 2002) surveyed college-age music students and found weekly practice durations for string instruments of 23 hours, for pianists of 20 hours, woodwind instruments of 18 hours, brass of 13 hours and singers of roughly 11 hours. These times are subject to change depending on impending competitions or exams. Sosniak (1985) found excessive practicing up to 50 hours a week among young concert pianists. Next, we will explore the sources of direction someone might receive to structure their practice.
Structuring Practice and Training The French composer and piano teacher Francois Couperin (1668-1733) advises not allowing children access to the instrument in order to prevent them to undo what he had accomplished. This anecdotal evidence suggests that children are largely unable to structure their own learning in absence of a teacher. This underscores Lave and Wenger’s (1991) concept of apprenticeship where learners have to go through stages in their respective fields. Coaches and teachers would seem to be the obvious others to structure deliberate practice activities. McPherson et al.’s (2012) book is to date probably the most authoritative and illuminating description of what happens or doesn’t happen in children’s musical development (and practice). The data base of the book consists of a number of much cited studies of the first two authors. Pitts, Davidson, and McPherson (2000) found out, that when young beginners were left alone, they hardly planned their practice and ended their practice sessions in rather unstructured ways. Renwick and McPherson (2002) discovered large differences in effectiveness which was also dependent on the young musician’s interest in the specific piece of music – self-selected music received much more effort than teacher-selected music. Very often, practice was sub-optimal in terms of setting and strategy. For example, ineffective playing through the piece or exercise was found to account for 90% of practice time which could in the long run become a critical determinant of lack of progress (McPherson et al., 2012). In essence, at least for the music domain, it is clear that self- organised solitary practice by beginners does not qualify as deliberate practice. Of course, with school-age children there might be some positive transfer from strategies learned in formal educational settings which affect all children in similar ways. In brief, students have to be taught metacognitive skills and self-regulation in order to practice effectively (Lehmann, 1997; McPherson et al., 2012; McPherson & Zimmerman, 2002). One is tempted to assume that students who receive more emotional and structural support at home and especially those students whose parents are able to give qualified hints or model the correct behaviour may develop more effective practice habits earlier. In fact, Davidson and co-workers (Davidson, Howe, Moore, & Sloboda, 1996; Davidson, Sloboda, & Howe, 1996) used retrospective interviews in a large study to assess parental influence on the performance of young instrumentalists of differing levels of achievement. They found that parents of stronger performing children tended to sit in on lessons more regularly, helped with practice or were generally interested in music listening and were more supportive than parents of the weaker children (similar things apply in sports, cf. de Lench, 2006). Moore, Burland, and Davidson (2003) found with a large sample that the variables (1) parental involvement in lessons over the first years on the main instrument, (2) rating of quality of the first teacher as a player/performer, (3) age at which lessons began, and (4) rating of the friendliness of the first teacher on the first instrument could 64 A. C. Lehmann & F. Kristensen be used to classify children into three predicted performance levels with an overall correct classification of 54.5%; those who gave up playing their instruments were even predicted with a 70% hit rate. These findings are confirmed by a study on historical piano prodigies who all had a “live-in teacher” (or at least frequent lessons), supervised practice, and an early start (Lehmann, 1997). Although interesting, these findings do not contain enough detail to reveal the microstructure, decisions and negotiations that happen in the home environment when it comes to practice. One might have to look for a more complex family culture or “habitus” as has been shown in an interview study regarding children’s sports participation (Wheeler, 2011). Sometimes, young musicians and athletes have to overcome motivational problems in order to start practicing/training. Given that ultimate long-term goals may be in itself rewarding (e.g. receiving a medal at Olympic Games) the daily practice/training has to be done whether or not one is eager to do it. Although the literature on motivation is vast and will not be considered here in detail, some aspects will be mentioned that concern the assistance of “persons in the shadow”. Szymanski, Beckmann, Elbe, and Müller (2004) investigated the development of volition in teenage athletes from a specialist boarding school compared to those attending a regular school. Volition is the cognitive process by which a person makes a conscious decision and subsequently follows a corresponding course of action. Thus, committing to practicing in the face of more appealing alternatives or despite adverse circumstances (fatigue, illness or pain) depends on volitional processes. The concept of volition is strongly associated with that of self-regulation. Szymanski and co-workers found that volitional (self-determining) strategies showed more improvement in boarding school students, suggesting that the closed environment with highly structured routines and peers of like interests had a positive influence. Students apparently learned to ward off distractions and train despite adverse circumstances (one could say the same about young Händel, see opening of this paper). Consistently, Roth (2011) found out in a diary study with music students that more proficient students were better able to practice when they did not really feel like practicing, thus implying stronger volitional skills. The later years of skill development are characterised by work with elite coaches or teachers, complete commitment on the part of the athlete or musician to competing and reaching the highest goals. Practice is structured by those elite coaches and peers and the public acts as social facilitators for high, self-regulated performance. Csikszentmihalyi, Rathunde, and Whalen (1993) postulate shared characteristics of master teachers: They were themselves enthusiastic about what they were doing and encouraged the students to excel; they created a positive learning environment by finding the right balance between boredom and frustration;2 they were genuinely interested in the learner as a whole, reassuring kindly when the need occurred (which is what Bloom, Durand-Bush, Schinke, & Salmela, 1998, call “mentoring”). All this opens up opportunities for intrinsically rewarding experiences for the learner, moments of “flow” that will reinforce the learner’s efforts regarding the domain. These memorable moments, often after stretches of hard work will compensate for those more tedious, effortful bouts of practice. There are certainly parallels between the successful music teachers and athletic coaches: “The stages of development of an individual require coaches to assume different roles. Whether introducing a child to a sport and fostering interest in that sport of developing a more rigorous practice routine, the elite coach will be encouraging, challenging, and understanding with the athletes. Talent development can occur only through deliberate practice. The elite coach understands how to stimulate athletes to participate in deliberate practice. In competition, the coach must maintain emotional control, develop a positive relationship with officials, and use time-outs and intermissions strategically.” (Bloom, 2002, p. 466) Hardly any study has addressed the triad of teacher/trainer and parents of successful musicians. In a large survey study Creech (2009) found typical patterns of interactions in what she calls teacher-parent-pupil trios. Which ones might prove more beneficial than Persons in the Shadow 65 others remains to be explored and could be dependent on background variables such as the parents’ aspirations or the teacher’s professional experience.
Examples of “Persons in the Shadow” Next, we will briefly outline a few examples of how persons (parents, teachers, peers, mentors) in the shadow can be relevant for achieving high levels of performance. Gruber et al. (2008) distinguished different types of such persons, i.e. the “supportive teacher and facilitator” (“bright person”) and the “anti-pedagogical motivator” (“dark person”). The latter was characterised by lack of social grace, use of non-pedagogical means of instruction and motivation and so on. Lehmann, Ericsson, and Hetzer (2002) undertook a study of 21 composers who were born within ten years of Wolfgang Amadeus Mozart (1756-1791) and had at least one work published in the anthology “The symphony, 1720-1840”. In order to assess the influence of prodigy status and educational background on later fame, fame was measured objectively through reliable bibliometric indices. The authors found that early start of training was associated with an earlier debut as composer as well as larger life-time output, and quality of instruction (one-on-one tuition) and having a musical family background correlated reliably with being a prodigy. None of the members of the comparison group were home-schooled in musical (performance and composition) and academic subjects like Mozart; none had received opportunities to travel beyond their immediate vicinity to meet leading musicians (e.g. J. C. Bach) or visit hot spots of innovation (e.g. Italy). In Mozart’s case, early start of training was initiated, taught, and supervised rigorously by the professional father, who also acted as a manager. The members of the comparison group attended church-run schools and often started composition lessons only after having learnt to play an instrument. Mentors and gatekeepers might also hold a secret to success of young performers. A case in point is the coloured violin prodigy of African descent, George Bridgetower, who established himself firmly in the London cultural scene at the end of the 18th century. His father, Friedrich Augustus, had been a servant close to the prince of Esterhaza (Hungary) where composer Joseph Haydn worked as a court composer. Haydn presumably trained George and kept up with his progress later in London. Termed “the African prince”, Friedrich’s “attire and demeanour, and his cultivated manners and charm, quickly attracted the attention of London’s aristocracy and helped to focus attention on his son” (p. 71). Wright (1980, p. 68) summarises: “In addition to his [George’s] innate ability, four factors seem to have contributed to his success: (1) he possessed an attractive, scheming father who brought his son to the attention of the English aristocracy; (2) he gained the unwavering financial support of that aristocracy; (3) for his day he possessed an exceptional liberal-arts education – a factor that often facilitated the rise up the social ladder in Georgian England; and (4) he won the patronage and friendship of George, Prince of Wales, later George IV of England (1762-1830).” George Bridgetower became a renowned musician of his time. The dark-person in the shadow is difficult to find, but occasionally even successful musicians will mention such forces. German star violinist David Garrett complained bitterly about this father who pushed him tremendously and made him practice many hours, even at young ages (Rothenbaum, 2013). Biographical information on Michael Jackson typically mentions his father’s overly rigorous training, physical abuse and perfectionism (Campbell, 1995). Informal conversations by the first author with career musicians have surfaced any possible sort of experienced abuse, including excoriating lessons, physical abuse, public humiliations of the student, neglect, etc. The latter examples are challenging, because they raise the question of how to ensure the child’s motivation and cooperation in accordance with accepted rules regarding children’s rights and welfare (e.g. the UNESCO child’s right charter). Of course children can be forced into anything as we know from tragic and sad instances of child soldiers 66 A. C. Lehmann & F. Kristensen and child athletes. While parents of highly domain involved children might be more accepting of pain (Ackermann & Driscoll, 2013) and maybe less lenient when it comes to practice (Chua, 2011) – maybe due to their personal experiences – there needs to be a societal consensus for what is allowed and what is not. Although “anti-heroes” are less often talked about, their influence might be strong (even beneficial in the short-term) and
the number of unreported such cases is open to speculation.
Nothing Left to Chance: A Theoretical Consideration While the opening anecdote on Händel suggests that gifted children are discovered by chance and cannot be stopped regardless of their surrounding circumstances, we tend to think that this picture is misleading. In terms of the development of particularly high levels of skills, the aspects of chance, good luck, fate and serendipity are often ascribed such a significant role that one may almost assume that skill acquirement is left to powers beyond our control, as is the case with the inheritance of our genetic makeup. But in fact, “persons in the shadow” surrounding the child probably tend to minimise chance through their behaviours, careful considerations and planning, and through strategic use of their knowledge and networks. Being born into a musical family is chance, but receiving early direct instruction, watching parents model domain-specific behaviour, and receiving reinforcement (Hoover-Dempsey & Sandler, 1995) is no accident. More important is most likely the level of intensity that parents or other social agents (grandparents, siblings, peers, neighbours, etc.) strive for or themselves are able to display in the way they support, organise, and guide their child. Such parental intensity in the gifted and talented arena is probably most noticeable at times of change or struggle, for example during the process of changing of teachers or sports teams. Finding the “right” teacher or team can be fraught with difficulties and uncertainty for both child and parents, and the likelihood of chance impacting negatively on this change may be greatly dependent on how much effort parents invest in the search for the new teacher as well as how they communicate with their child in an effort to stabilise a potentially volatile situation. An inquisitive, conscientious, and reflective parent is likely to ponder issues regarding the teacher’s reputation, experience, lesson-repertoire, etc., while another may simply accept the first teacher available. The same is probably true when parents or teachers attempt to enforce practice discipline “day in, day out” and monitor progress against some standard (maybe their own biography). This continuous “staying on the ball” demands tremendous energy of the parents and only really ceases when the young musician becomes independent. In this way, parents of talented teenagers invest large amounts of resources, such as time, money, and energy, into supporting their children. McPherson et al. (2012) discuss chance in their study of over 150 young Australian musicians stating that “negative casual influences frequently turned out to be the direct outcomes of poor planning, bad decisions, inappropriate behaviours, [...]”. Similarly, they link cases of successful musicians back to „serendipitous alignments“ (also referred to as “syzygies”) of fortunate situations that provided an ideal environment for development. They also succinctly characterise the impression on an uninitiated observer regarding the development of expert level musicians: “If this journey is ‘seemingly effortless’ then it is because the confluence of these factors deceive the casual observer as they so often do: levels of parental support, the absence of conflict [...]” (McPherson et al., 2012, p. 109). Similarly, Csikszentmihalyi et al. (1993, p. 174) found that parents set high standards, encouraged effective use of time, provided places in the house for undisturbed work, enabled lessons and all necessary materials, and they provided challenging opportunities. If this level of commitment and preparedness of social agents to sacrifice their own time and money, and in doing so not leaving the musical education of the child to chance, is indicative of later success, then we can ask how such investment may be scientifically studied. And how can we assess teacher behaviours outside the lesson, such as scheduling extra lessons before competitions or concerts, accompanying a musician or Persons in the Shadow 67 athlete to a competition in the role of a mentor etc.? This type of infrequent behaviour is difficult to quantify in retrospective interviews that often form the basis of research on expert performers. Clearly, more detailed research needs to be carried out in order to explain the exact effects of those “persons in the shadow”. In light of the present paper, we are not surprised that athletes often come from the homes of athletes and genealogies of musicians are well-known in music history. Many of the crucial ingredients for success that other families have to tediously acquire are already in place in the social (cultural) and physical environments of musicians and sportspeople. Regardless whether a family is “musical” or “non-musical”, “sporty” or inactive, the final questions remain: Do the social agents want to make an investment? And if so, with what intensity, and which means do they have at their disposition?
Notes 1 Note that deliberate practice in music is embedded in other types of less effortful and relevant activities. Measuring solitary practice in classical music thus ought to include whatever deliberate practice is undertaken, but solitary practice is not identical with deliberate practice. 2 We could state in Vygotskyian terms that they were able to find and fill the learner’s zone of proximal development (cf. Gholson, 1998, for a brilliant analysis of the elite violin teacher Dorothy DeLay’s instruction).
References Abbott, A., & Collins, D. (2004). Eliminating the Wellesly: Branden. dichotomy between theory and practice in Chua, A. (2011). Battle hymn of the tiger mother. talent identification and development. Journal New York: Penguin. of Sports Sciences, 22, 395–408. Creech, A. (2009). Teacher-pupil-parent triads: A Ackermann, B., & Driscoll, T. (2013). Attitudes and typology of interpersonal interaction in the practices of parents of teenage musicians to context of learning a musical instrument. health issues related to playing an instrument: Musicae Scientiae, 13, 387–413. A pilot study. Medical Problems of Performing Csikszentmihalyi, M., Rathunde, K., & Whalen S. Artists, 28(1), 24–27. (1993). Talented teenagers. Cambridge: Bailey, J., & Penhune, V. B. (2012). A sensitive period Cambridge University Press. for musical training: Contributions of age of Davidson, J. W., Howe, M. J. A., Moore, D., & onset and cognitive abilities. Annals of the Sloboda, J. A. (1996). The role of parental New York Academy of the Sciences, 1252, 163– influences in the development of musical 170. performance. British Journal of Developmental Balyi, I., & Hamilton A. (2004). Long-term athlete Psychology, 14, 399–412. development: Trainability in childhood and Davidson, J. W., Sloboda, J. A., & Howe, M. J. A. adolescence. Windows of opportunity. Optimal (1996). The role of parents and teachers in the trainability. Victoria: National Coaching success and failure of instrumental learners. Institute British Columbia & Advanced Bulletin of the Council for Research in Music Training and Performance. Education, 127, 40–44. Bastian, H. G. (1989). Leben für Musik. Eine De Lench, B. (2006). The home team advantage: Biographiestudie über musikalische (Hoch-) The critical role of mothers in youth sports. Begabungen. Mainz: Schott. New York: Harper & Collins. Bloom, B. S. (1985). Developing talent in young Ericsson, K. A., Charness, N., Feltovich, P. J., & people. New York: Ballentine. Hoffman, R. R. (Eds.). (2006). The Cambridge Bloom, G. (2002). The role of the elite coach in the handbook of expertise and expert development of talent. In J. Silva & D. E. performance. Cambridge: Cambridge Stevens (Eds.), Psychological foundations of University Press. sports (pp. 466–483). Boston: Allyn & Bacon. Ericsson, K. A., & Crutcher, R. J. (1990). The nature Bloom, G. A., Durand-Bush, N., Schinke, N. J., & of exceptional performance. In P. B. Baltes, D. Salmela, J. H. (1998). The importance of Featherman, & R. Lerner (Eds.), Life-span mentoring in the development of coaches development and behavior (Vol. 10, pp. 187– and athletes. International Journal of Sport 217). Hillsdale: Erlbaum. Psychology, 29, 267–281. Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. Campbell, L. (1995). Michael Jackson: King of pop. (1993). The role of deliberate practice in the 68 A. C. Lehmann & F. Kristensen
acquisition of expert performance. Hyllegard, R., & Bories, T. (2009). Deliberate Psychological Review, 100, 363–406. practice theory: Perceived relevance, effort, Ericsson, K. A., & Lehmann, A. C. (1996). Expert and inherent enjoyment of music practice: and exceptional performance: Evidence for Study II. Perceptual and Motor Skills, 109, 431– maximal adaptations to task constraints. 440. doi: 10.2466/pms.109.2.431-440. Annual Review of Psychology, 47, 273–305. Jørgensen, H. (1998). Tid til øving? [Time for Ericsson, K. A., & Lehmann, A. C. (1999). Expertise. practice]. Oslo: Norges Musikhøgskole. In M. A. Runco & S. Pritzker (Eds.), Jørgensen, H. (2001). Instrumental learning: Is an Encyclopedia of creativity (Vol. 1, pp. 695–707). early start a key to success? British Journal of San Diego: Academic Press. Music Education, 18, 227–239. Ericsson, K. A., Roring, R. K., & Nandagopal, K. Jørgensen, H. (2002). Instrumental performance (2007a). Giftedness and evidence for expertise and amount of practice among reproducibly superior performance: An instrumental students in a conservatoire. account based on the expert performance Music Education Research, 4, 105–119. framework. High Ability Studies, 18, 3–56. Kopiez, R. (2011). The musical child prodigy Ericsson, K. A., Roring, R. W., & Nandagopal, K. (wunderkind) in music history: A (2007b). Misunderstandings, agreements, and historiometric analysis. In I. Deliège & J. W. disagreements: Toward a cumulative science Davidson (Eds.), Music and the mind. Essays in of reproducibly superior aspects of honour of John Sloboda (pp. 225–236). Oxford: giftedness. High Ability Studies, 18, 97–115. Oxford University Press. Fitts, P. M., & Posner, M. I. (1967). Human Kopiez, R., & Lehmann, A. C. (in press). performance. Belmont: Brooks & Cole. Musicological reports on early 20th-century Fredricks, J. A., & Eccles, J. S. (2004). Parental musical prodigies: The beginnings of an influences on youth involvement in sports. In objective assessment. In G. McPherson (Ed.), M. R. Weiss (Ed.), Developmental sport and Prodigies. Oxford: Oxford University Press. exercise psychology: A lifespan perspective Lave, J., & Wenger, E. (1991). Situated learning: (pp. 145–164). Morgantown: Fitness Legitimate peripheral participation. Information Technology. Cambridge: Cambridge University Press. Gagné, F. (2004). Transforming gifts into talents: Lehmann, A. C. (1997). Acquisition of expertise in The DMGT as a developmental theory. High music: Efficiency of deliberate practice as a Ability Studies, 15, 119–147. moderating variable in accounting for sub- Gholson, S. A. (1998). Proximal positioning: A expert performance. In I. Deliege & J. Sloboda strategy of practice in violin pedagogy. (Eds.), Perception and cognition of music (pp. Journal of Research in Music Education, 46, 165–190). London: Psychology Press. 535–545. Lehmann, A. C. (2002). Effort and enjoyment in Gould, D. (2009). The professionalization of youth deliberate practice: A research note. In I. M. sports: It’s time to act [editorial]. Clinical Hanken, S. G. Nielsen, & M. Nerland (Eds.), Journal of Sports Medicine, 19(2), 81–82. Research in and for music education. Festschrift Gruber, H., Jansen, P., Marienhagen, J., & for Harald Jørgensen (pp. 153–166). Oslo: Altenmüller, E. (2010). Adaptations during the Norwegian Academy of Music. acquisition of expertise. Talent Development Lehmann, A. C. (2006). Historical increases in and Excellence, 2, 3–15. expert music performance skills: Optimizing Gruber, H., Lehtinen, E., Palonen, T., & Degner, S. instruments, playing techniques, and training. (2008). Persons in the shadow: Assessing the In E. Altenmüller, M. Wiesendanger, & J. social context of high abilities. Psychology Kesselring (Eds.), Music, motor control, and Science Quarterly, 50, 237–258. the brain (pp. 3–22). Oxford: Oxford Gruson, L. M. (1988). Rehearsal skill and musical University Press. competence: Does practice make perfect? In Lehmann, A. C., & Ericsson, K. A. (1998). The J. A. Sloboda (Ed.), Generative processes in historical development of domains of music (pp. 91–112). Oxford: Clarendon. expertise: Performance standards and Heller, K. A. (2001). Projektziele, Untersuchungs- innovations in music. In A. Steptoe (Ed.), ergebnisse und praktische Konsequenzen. In Genius and the mind: Studies of creativity and K. A. Heller (Ed.), Hochbegabung im Kindes- temperament in the historical record (pp. 64– und Jugendalter [giftedness during childhood 97). Oxford: Oxford University Press. and youth] (pp. 21–40). Göttingen: Hogrefe. Lehmann, A. C., Ericsson, K. A., & Hetzer, J. (2002). Hicks, A. (2013). Handel, George Frideric. Grove How different was Mozart’s music education Music Online. Oxford Music Online. Oxford and training? A historical analysis comparing University Press. Retrieved from the music development of Mozart to that of his www.oxfordmusiconline.com, December 6, contemporaries. In K. Stevens, D., Burnham, G. 2013. E. McPherson, E. Schubert, & J. Renwick Hidi, S., & Renninger, A. (2006). The four-phase (Eds.), Proceedings of the 7th International model of interest development. Educational Conference on Music Perception and Psychologist, 41, 111–127. Cognition, Sydney, 2002 (pp. 426–429). Sydney: Hoover-Dempsey, K., & Sandler, H. (1995). Parental Causal Productions. [CD-ROM] involvement in children’s education: Why Lin, N. (1999). Building a network theory of social does it make a difference? Teacher College capital. Connections, 22(1), 28–51. Record, 97, 311–331. Manturzewska, M. (1990). A biographical study of Persons in the Shadow 69
the life-span development of performing of the child prodigy phenomenon: Sensitive musicians. Psychology of Music, 18, 112–129. periods and cognitive experience. Gifted McPherson, G. E., Davidson, J. W., & Faulkner, R. Child Quarterly, 43, 25–38. (2012). Music in our lives: Rethinking musical Shavinina, L. V. (2007). On the advancement of the ability, development & identity. Oxford: Oxford expert performance approach via a deep University Press. understanding of giftedness (commentary on McPherson, G. E., & Zimmerman, B. J. (2002). Self- Ericsson et al.). High Ability Studies, 18, 79–82. regulation of musical learning: A social Shavinina L. V. (Ed.). (2009). The international cognitive perspective. In R. Colwell & C. handbook on giftedness. Amsterdam: Richardson (Eds.), The new handbook of Springer. research on music teaching and learning (pp. Sichivitsa, V. (2007). The influences of parents, 327–347). New York: Oxford University Press. teachers, peers and other factors on students’ Moore, D. G., Burland, K., & Davidson, J. W. (2003). motivation in music. Research Studies in Music The social context of musical success: A Education, 29(1), 55–68. developmental account. British Journal of Simonton, D. K. (1991). Emergence and realization Psychology, 94, 529–549. of genius: The lives and works of 120 classical Olbertz, F. (2009). Musikalische Hochbegabung. composers. Journal of Personality and Social Frühe Erscheinungsformen und Psychology, 61, 829–840. Einflussfaktoren anhand von drei Fallstudien Sloboda, J. A., Davidson, J. W., Howe, M. J. A., & [Three case studies of musical prodigies. Moore, D. M. (1996). The role of practice in the Early signs and influences]. Münster: Lit. development of expert musical performance. Papousek, H., & Papousek, M. (1995). Intuitive British Journal of Psychology, 87, 287–309. parenting. In M. H. Bornstein (Ed.), Handbook Sloboda, J. A., & Howe, M. J. A. (1991). Biographical of parenting (Vol. 2, pp. 117–136). Hillsdale: precursors of musical excellence: An Erlbaum. interview study. Psychology of Music, 19(3), 3– Penhune, V. B. (2011). Sensitive periods in human 21. development: Evidence from musical training. Sosniak, L. A. (1985). Learning to be a concert Cortex, 47, 1126–1137. doi: 10.1016/j.cortex. pianist. In B. S. Bloom (Ed.), Developing talents 2011.05.010. in young people (pp. 19–67). New York: Pitts, S., Davidson, J., & McPherson, G. E. (2000). Ballantine. Developing effective practice strategies: Sosniak, L. A. (2006). Retrospective interviews in Case studies of three young instrumentalists. the study of expertise and expert Music Education Research, 2, 45–56. performance. In K. A. Ericsson, N. Charness, P. Renwick, J., & McPherson, G. E. (2002). Interest and J. Feltovich, & R. R. Hoffman (Eds.), The choice: Student-selected repertoire and its Cambridge handbook of expertise and expert effect on practising behaviour. British Journal performance (pp. 287–302). Cambridge: of Music Education, 19, 173–188. Cambridge University Press. Rosenbaum, D. A., Augustyn, J. S., Cohen, R. G., & Sternberg, R. J. (2003). WICS as a model of Jax, S. A. (2006). Perceptual-motor expertise. giftedness. High Ability Studies, 14, 109–137. In K. A. Ericsson, N. Charness, P. J. Feltovich & Szymanski, B., Beckmann, J., Elbe, M., & Müller, D. R. R. Hoffman (Eds.), The Cambridge (2004). Wie entwickelt sich die Volition bei handbook of expertise and expert Talenten einer Eliteschule des Sports [How performance (pp. 287–302). Cambridge: volition develops in talented teenagers in a Cambridge University Press. specialist school]. Zeitschrift für Sport- Roth, B., & Sokolowski, K. (2011). Die Bedeutung psychologie, 11, 103–111. von Motivation und Volition beim Üben eines Tapper, T. (1889). Pictures from the lives of the Musikinstrumentes: Was unterscheidet das great composers for children. Philadelphia: Üben unter Lust und Unlust? [Importance of Presser. motivation and volition when practicing a Wattie, N., Cobley, N., & Baker, J. (2008). Towards a musical instrument: What distinguishes unified understanding of relative age effects. between practicing with aversion or zest?]. In Journal of Sports Sciences, 26, 1403–1409. doi: B. Clausen (Ed.), Vergleich in der 10.1080/02640410802233034 musikpädagogischen Forschung (pp. 113–143). Wheeler, S. (2011). The significance of family Essen: Blaue Eule. culture for sports participation. International Rothenbaum, J. (2013). David Garrett: Die exklusive Review for the Sociology of Sport, 47, 235–252. Biografie. München: mvg. Winner, E. (1996). The rage to master: The decisive Saßmannshaus, K. (1993). Hochschullehrer und case for talent in the visual arts. In K. A. Kinder oder Warum der erste Lehrer auch Ericsson (Ed.), The road to excellence: The der beste sein muß [College teachers and acquisition of expert performance in the arts children. Why the first teacher has to beb the and sciences, sports and games (pp. 271– best one]. In H. G. Bastian (Ed.), 301). Hillsdale: Erlbaum. Begabungsforschung und Begabtenförderung Wright, J. R. B. (1980). George Polgreen in der Musik (pp. 75–77). Mainz: Schott. Bridgetower: An African prodigy in England Schunk, D. H., & Zimmerman, B. J. (Eds.). (1998). 1789-99. The Musical Quarterly, 66(1), 65–82. Self-regulated learning. From teaching to self- Ziegler, A. & Alan, M. (2011). Bildungskapital. Eine reflective learning. New York: Guilford. ergänzende Perspektive auf die Entwicklung Shavinina, L. V. (1999). The psychological essence von Leistungsexzellenz [Educational capital: 70 A. C. Lehmann & F. Kristensen
A supplementary perspective on Ziegler, A., & Stoeger, H. (2008). A learning development of excellence]. News & Science oriented subjective action space as an Begabungsförderung und Begabungsfor- indicator of giftedness. Psychology Science schung, no. 2/2011, 25–28. Quarterly, 50(2), 222-236.
The Authors
Dr. Andreas C. Lehmann is professor of Systematic Musicology and Music Psychology at the Hochschule für Musik Würzburg. His main research interests concern musical expertise skill acquisition, competency measurement, and sociological issues surrounding amateur music making. He is associate editor of Musicae Scientiae and has published internationally in the field of music psychology and music education.
Flemming Kristensen (BMus Hons; M.A.) studied piano (1999–2002) under Katherine Austin at The University of Waikato, New Zealand. After completing a Diploma of Education (2004), he taught music and German at secondary school level. In 2008 he moved to Germany to pursue his studies in the areas of instrumental pedagogy and musicology. His main area of interest, and current Phd research topic, focuses on the influence of environmental factors on the development of musical skills in young people.
Talent Development & Excellence Centres of Excellence 71 Vol. 6, No. 1, 2014, 71–93 The Organisational Embedding Of Expertise: Centres of Excellence Harald A. Mieg*
Abstract: Centres of excellence are institutions (within the hierarchy of a firm or the national system of research and education) that concentrate expertise and/or train the top experts. We find “centres of excellence”, for instance, within universities, governmental institutions or teaching hospitals. To date, research on centres of excellence has focused on multinational companies and hospitals. This paper introduces research on embedded expertise in the case of centres of excellence; it integrates and generalises findings from research on excellence within three domains: (1) elite sport; (2) the institutionalisation of environmental science expertise in Switzerland; (3) top inventors. The core part of the paper is conceptual, defining institutional levels of embedded expertise (individuals, teams, organisations, and society) and different logics for the selection of excellence (market, hierarchy, and network). From this empirical and conceptual base, the paper draws lessons for centres of excellence (e.g., take into account individual life plans; include options for excellence through transfer) and reviews their various strategies (from exclusivity to talent recycling). The discussion deals with the labelling of centres of excellence. Centres of excellence are not only organisational forms of embedded expertise: in many cases, they have to signal their “excellence” to their environments or audiences.
Keywords: centres of excellence, embedded expertise, excellence, professionalism, socialization, out-sourcing
“No man is an island” (John Donne) – what holds for humans in general is true for experts in particular: the development of excellence and specialised skills requires societal institutions such as schools, universities and training centres. Centres of excellence have therefore been created in order to concentrate leading experts or the most promising students. We find centres of excellence within teaching hospitals, universities, multinational institutions, etc. The titles of these centres might differ according to the domain or discipline, ranging from the Reinsch Pierce Family Center for Breast Health (a Virginia Hospital Center of Excellence) to the “The Jane Goodall Center for Excellence in Environmental Studies” (associated with Connecticut State University); and the US Ski and Snowboard Association’s Center of Excellence, to the NATO “Cold Weather Operations Centre of Excellence” (Bodø, Norway). From highly specialised service centres to national elite research institutions, the guiding idea remains the same: to concentrate top experts – either to offer elite professional services or to create a place where the “diamonds” of a field get the final polish. Of course, as in any field of public and commercial interests, there are free-riding institutions that simply copy the brand, without providing any substantial added value. A prominent, integrative definition of a centre of excellence comes from Frost, Birkinshaw and Ensign (2002), who reviewed the literature on multinational companies: “We define center of excellence as an organizational unit that embodies a set of capabilities that has been explicitly recognized by the firm as an important source of value creation, with the intention that these capabilities be leveraged by and/or disseminated to other parts of the firm.” (p. 997) In the same context, Reger & Zafrane-Bravo (2002) proposed to distinguish three types of centres of excellence or definitions, respectively: in a very narrow sense, centres of excellence embody a particular competence in a multinational company; in a broader
* Humboldt-Universität zu Berlin, Geographisches Institut, Unter den Linden 6, D-10099 Berlin, Germany. Email: [email protected]
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
72 H. A. Mieg sense, they must also be recognised as centres of excellence within the firms; in the broadest sense, centres of excellence serve a specific function within the multinational company. Centres of excellence in hospitals belong to the third category, and represent specialised services. The general question of this article is: How can we understand centres of excellence as an organisational form of embedded expertise? What can we learn about embedded expertise in general? The definitions cited above focus on centres of excellence within companies. For this article, I adapt the definition to organisational forms beyond the economic realm: Centres of excellence are institutions (within the hierarchy of a firm or the national system of research and education) that concentrate expertise and/or train top experts. This definition helps address not only embedded expertise within companies but also organisational forms such as the US Ski and Snowboard Association’s Center of Excellence or the NATO “Cold Weather Operations Centre of Excellence”. The analysis of centres of excellences in terms of embedded expertise has implications for researching and managing centres of excellence within differing spheres. Figure 1 sketches the plan for unfolding and analysing the phenomenon of embedded expertise, which is used in this paper to arrive at concepts for understanding centres of excellence. The first step consists of finding representative groups of experts. The core criterion to apply is central to the psychology of expertise: excellence (Ericsson, 1996). Experts – as the exceptional members of their domains – are easily identified in the fields of sports and music, as competitions occur on a regular basis. I use the example of athletes and their organisational contexts. In many other contexts of professional work, experts are identified by their qualifications, e.g. in medicine or engineering. Then professionalism – as a second factor of expertise – comes into play (Mieg, 2009). My example examines environmental professionals and their organisations. In addition, I will cover top inventors as a third group of experts; this is a very heterogeneous group of experts, with a kind of expertise that is difficult to explain via the concepts of excellence or professionalism (Mieg, Bedenk, Braun, & Neyer, 2012). However, inventors – or research engineers – seem indispensable to the firms’ innovation processes. In contrast to managers (a group with equal relevance for companies), the integration of inventors within teams seems particularly critical for firms.
Figure 1. Plan for unfolding the phenomenon of embedded expertise. Centres of Excellence 73
The second step is to define organisational forms. If we consider, on the one hand, society as the highest level of embedding expertise and, on the other hand, individual experts as the foundation level, then we can attempt to define intermediate levels or structures of embedded expertise. I will argue that at least two such levels are relevant: teams (defined by face-to-face interaction) and organisations (defined by formal interaction via roles). After determining the organisational forms of embedded expertise, our third step will concern selection processes: we need to understand and define the different ways in which individual experts are allocated or re-allocated to organisations and teams. Organisational forms represent the structural component of embedding expertise, whereas selection represents the process component; together, they complete the conceptual part of understanding embedded expertise. This paper contains five parts. The first part will introduce the three domains – the groups of experts on which I will focus. The second part will introduce the organisational forms and selection processes. The third part will revise empirical findings with regard to embedded expertise and centres of excellence in the three focus domains, including Individual- vs. organisational planning The issue of domain specificity, core expertise and transfer Dichotomies of developing embedded expertise The findings reveal the general problem of developing expertise individually vs. at a team level. Embedded expertise means both integrating excellent individuals within some kind of organisation, and achieving top performance at an integrated organisational level that cannot be explained by attribution to single individuals (e.g., success of teams). The fourth part presents implications for centres of excellence, reflecting the discussion of in- sourcing vs. out-sourcing of expertise (“make” or “buy”), which is well known in human resource management (Belcourt, 2006). The fifth and last part of this paper revisits our general question: How can we understand centres of excellence as an organisational form of embedded expertise? And what can we learn about embedded expertise in general? This section discusses two general assumptions regarding expertise and organisations, on which my review of centres of excellence is based. First, assumed homogeneity of expertise: The development of excellence (top expertise) is structurally equivalent in all domains. This assumption is fundamental to research on expert performance in general, as promoted by Ericsson (1996, 1998, 2006). Second, the assumed homogeneity of organisation: Centres of excellence from different domains share the same organisational logic. A general stake for the assumption of homogeneity of organisation is, for instance, put forward by Jaques (1976, 1988), based on the idea that any organisation has to coordinate the work of people. The discussion will lead us to the question: who defines and claims excellence?
Three Focus Domains: Elite Sport – Environmental Expertise – Top Inventors Table 1 provides an overview of the three domains chosen. The typical pathways to each domain differ entirely. Professional sport requires early commitment and sometimes a very early specialisation. In contrast, environmental expertise increasingly requires an academic specialisation; such experts often do not start their careers before the age of 30, and will continue to work as long as their intellectual capabilities allow it; this is similar to the medical profession. The role of an inventor is described as a passion, or even obsession (Mieg, 2010a), that can emerge early, and seems to become evident between the ages of 10 and 25. The biographical decision concerns the kind of professional activity, for instance engineering or natural sciences. It is similar to a passion for music that does not necessarily result in a professional career. For instance, Konrad Adenauer, the first post-war West German Chancellor, was a passionate hobby inventor, holding 74 H. A. Mieg
Table 1. Characteristics of the Three Chosen Domains of Excellence Environmental Elite sport Top inventors expertise Entry Childhood Via higher education Around puberty (10–25)
Attribution of Individual focus (plus Academic focus Commercial focus expertise nations)
Organizational 1. Clubs (and their 1. NGOs 1. Patent offices forms associations); 2. Companies 2. Companies 2. Schools (in the 3. Professions 3. National innovation framework of the 4. Laws, regulations systems national education (“regime”) 4. Networks system); 5. Universities (and 3. National regimes (as schools) in the GDR); 4. Science institutes
Centres of National training Swiss Federal Institute Some R&D divisions; Excellence centres (“Bundes- of Technology; Expert Fraunhofer-Institute, (examples) leistungszentren”); societies Technical universities Olympic training (“Fachvereine”) centres (“Olympiastütz- punkte”)
Empirical base Deutsche Switzerland (Mieg, Mieg (2010), Mieg, Sporthochschule Köln 2002, 2008a) Bedenk, Braun & Neyer (German Sport (2012) University Cologne)
Theory Deliberate practice Professionalisation Possibility filter (Ericsson, Krampe & (Abbott, 1988; (Weber, 2006; Mieg, Tesch-Römer, 1993) Freidson, 2001; Mieg, 2010a) 2008b) three patents; many of his patent applications, however, were not granted. In the following, I will introduce the types of expertise and experts, and the organisational forms involved in the three domains.
The Experts Although there are some differences between team and individual sports, all share a clear focus on the attribution of expertise. I have chosen the example of elite sport because it provides a perfect case for the study of achieving excellence through deliberate practice (Ericsson, Krampe, & Tesch-Römer, 1993; Hodges, Starkes ,& MacMahon, 2006). However, we should not forget that any organisational embedding of athletes involves a series of further experts such as coaches, referees and specialists from science and management. Moreover, consistent and rigorous institutionalisation can increase performance in sports at a national level. For many years, the GDR (German Democratic Republic, 1948–1989), despite being a relatively small state, consistently ranked highly in Olympic games, behind only the Soviet Union and the USA. A similar pattern is observed in the international success of Russian chess grandmasters, following a national initiative by the Soviet regime during the 1920s (Hallman, 2003). In contrast to sports, the attribution of environmental expertise – my second domain – has an academic focus, in which academic research and higher education are seen as the main pathways to obtaining expertise in the domain. Moreover, environmental expertise is linked to a professional activity. Accordingly, the standard approach to understanding Centres of Excellence 75 the formation of expertise within such fields is the theory of 75rofessionalization (Freidson, 2001; Abbott, 1988). The core idea is the formation of a professional group (occupation, profession) concerned with solving their clients’ problems related to environmental issues. During the years 1997 to 2001, I conducted two national surveys on the 75rofessionalization of environmental expertise in Switzerland (de Sombre, Woschnack, Näf, & Mieg, 2002; Mieg, 2002, 2008b). For the year 2000, we estimated there were about 9000 professional environmental experts in Switzerland. In inventions, the focus of the attribution of expertise is on companies. Companies can be considered as resource pools that combine human and capital resources in order to finance inventions (Penrose, 2009/1959) – and usually include inventors. In a narrow sense, inventors are people who hold a patent. In a very broad sense, inventors are creative people within technological or similar fields. Broader definitions of inventors are very much in use; however, for reasons of clarity, I will only use the narrow definition. There are three different categories of inventors (Mieg, Bedenk, Braun, & Neyer, 2012). The most common category comprises those employed as engineers or scientists in industrial research and development divisions. Often, they do not consider themselves to be inventors. The second category is independent inventors; in general, they try to sell inventions. Most of the very famous inventors, such as Thomas Alva Edison or Artur Fischer, belong to the third, rare category: inventor-entrepreneurs, who establish their own companies. Inventors consider themselves as creative people. Accordingly, inventors are often seen as representing a form of creativity (Weisberg, 2006). However, there is very limited psychological research with inventors. Creativity seems to be a necessary – but not sufficient – criterion for inventiveness (Mieg et al., 2012). A further necessary characteristic is “focus”: successful inventors are completely focused on their particular idea (Mieg, 2010a). The most accurate theory I know comes from Robert J. Weber, a psychologist concerned with inventions (e.g., Weber, 1996). He proposed a “possibility filter” (Weber, 2006; Mieg, 2010a): an inventor scans any information from any domain from the perspective of his/her guiding invention. Inventors try to make a particular goal (to fly, etc.) technologically possible, and are completely focused on this task.
Organisational Forms As table 1 shows, there is a high degree of institutionalisation – a variety of organisational forms – in all three domains, although environmental expert services is a relatively new domain. The most common forms are sport clubs in the case of athletes, or companies in environmental experts and top inventors. Very commonly, environmental experts also work with NGOs (non-governmental organisations); for inventors, patent offices play an important role. All three domains are also institutionalised at the national level, and the domain of environmental expertise is particularly driven by the local- to global-scale policy framework. At a national level, inventions are regarded as results and elements of national innovation systems (cf. OECD, 1999) that combine all productive components within a nation, such as companies, universities and regulatory frameworks. As I did not conduct any empirical research on sport, my reference for sport research has been the German Sport University in Cologne, which is a central part of the institutionalisation of sport in Germany. When looking for centres of excellence, we easily find them in sports: For example, Germany has specialised Bundesleistungszentren – national training centres for top performers within a discipline. In addition, there are Olympiastützpunkte – training centres for federal states (Länder), which focus on Olympic disciplines. As to invention, we would regard some industrial R&D divisions as being centres of excellence. The theme of centres of excellence within multinational companies is a widely researched field (e.g., Frost et al., 2002). Further candidates for centres of excellence in invention would be university departments and, in Germany, also the so-called Fraunhofer Institutes – that is, research institutes jointly financed by industry and the state. 76 H. A. Mieg
Centres of excellence are less obvious in the case of the institutionalisation of environmental expertise in Switzerland. Some university departments, such as the Department of Environmental System Science at the Swiss Federal Institute of Technology (Mieg, Hansmann, & Frischknecht, 2012), might claim to be centres of excellence. For a closer look, some so-called Fachvereine – expert societies – might also qualify as centres of excellence. There are many associations within the environmental domain in Switzerland – political, professional, industrial, etc. In contrast to the many interests of the other associations, Fachvereine have a pure interest in advancing best practice in their field, combining science, practice and norming; examples include the Swiss Water Association (VSA), representing “the aggregation of the Swiss professionals for water protection” (Verband Schweizer Abwasser- und Gewässerschutzfachleute, 2012).
The Organisational Embedding Of Expertise: Concepts This second part elaborates concepts required for an understanding of embedded expertise. The structural component comprises four hierarchical levels, ranging from individuals as the least integrated organisational form, to the level of society as the most integrated organisational form. The process component addresses changes in the allocation of experts to organisational forms: here, we will focus on specific selection process, e.g. those driven by markets.
Structural Component: Four Levels Generalising from the experience in selected fields of expertise, I propose to distinguish four institutional levels (see figure 2). The basic level consists of individuals, whereas the highest integrating level is society. This societal level represents the highest self- regulating organisational body – in most cases, a nation. In addition, I propose to distinguish two further, mediating institutional levels or organisational forms: organisations and teams. Both forms incorporate a certain division of labour; however, between the two forms there is division between personal/impersonal management. Teams have a size that allows for management by personal, face-to-face interaction. The organisations I refer to are too large to know every member personally: in organisations, the division of labour is impersonal, and is organised by roles and functions. Centres of excellence may take both forms, organisations or teams.
Society
Organisations
Teams
Individuals
Figure 2. Four levels of embedding expertise. Centres of Excellence 77
The four institutional levels are conceived of as a hierarchy: to some extent, any given level directs the level that is immediately subordinate. In addition, as excellent individuals are a scarce and prestigious good, any level of our model also makes direct reference to individuals. As to sports, many studies attempted to find out effects of measures at the national level on the performance of individual athletes – triggered via intermediate organisational forms. For instance, several international studies compared systems of talent-spotting in sports. Besides population size and available national resources measured as GDP (Emrich et al., 2008), the degree of coordinated national planning seems to be a factor in success (Rütten, Ziemainz, & Röger, 2005). This planning factor explains the particular success of China and Australia in many disciplines (Rütten et al.). Table 2 shows the characteristics of the four institutional levels. As we see, teams have a group size of about 5 to 50 people; typical examples are soccer teams or research groups. In our model, organisations have more than 500 members, requiring formal, impersonal regulation, with typical examples being sports clubs or hospitals. Also, the typical time horizon differs between teams and organisations. Teams have shorter time horizons, ranging from 1 to about 5 years, whereas organizations have a longer lifetime, and serve to continue a particular form of the social division of labour. Societies, as the upper integrative form, encompass at least three generations of individuals. In the context of developing excellence, a society should be large enough to provide a sufficient genetic pool to find talent, for instance athletes with world-class potential; in this context, a population of 2 mio is simply a guess. At any level, we see specific types of experts who can gain excellence in their own way. In organisations, we have managers; at the team level, the experts are the team coaches (in sports) or professors (in university-based science). If we want to identify experts at the highest level, politicians would be the best candidates. However, in our context, the focus is on individuals as high performers, such as athletes, or a domain expert in environmental issues.
Table 2. Institutional Component of the Embedding of Expertise Individuals Teams Organisations Society Contribution Talent, Division of Hierarchical Institutional Skills labour (face-to- division of framework face) labour
Typical expert Athlete, Coach, Manager, Politician (at the highest Environmental Professor, Director level) expert, Team leader Inventor
Examples Soccer team, Sports club, Research group; Hospital, Planning firm University
Typical # 1 5–50 > 500 > 2 mio members
Time horizon Variable 1–5 years > 5 years > 50 years
Example theory 2 Factors (Mieg, Scholl (1999), Jaques (1976, Campbell (1960, 2009); Scholl & Riedel 1988); resource 1987); political deliberate (2010); social theory (Penrose, economy (e.g., practice psychology of 2009/1959) Acemoglu & (Ericsson, small groups Robinson, 2012) Krampe & (Levine & Tesch-Römer, Moreland, 1990) 1993) 78 H. A. Mieg
For any level, we find specific theoretical approaches that may help to conceptualise and explain the effects of embedding expertise. 1. At the societal level, the task of fostering excellence is one of identifying specific potentials, and providing the means of schooling, training and career support. This looks like a planning problem; however, there are two important unknown factors: the changing genetic pool in a society, and the criteria for achieving excellence in the context of global competition. Therefore, the political optimisation of any framework of embedding excellence has dimensions of both randomness and creativity. This situation is described by Campbell’s (1960, 1987) evolutionary theory of blind variation and selective retention. Open societies leave open the question of which forms of excellence to foster via institutional means, and whether to invest public resources in excellence at all. Campbell defined three structural elements (1960, p. 381): first, a “mechanism for introducing variation” (in the political sphere: parties and political programmes); second, a “consistent selection process” (elections); third, a “mechanism for preserving and reproducing the selected variations” (political decisions, e.g. installing national centres of excellence). These “mechanisms” must be linked to institution-building within a society, as described by political economy (e.g., Acemoglu & Robinson, 2012). 2. In our context, the main characteristic of organisations is their formal, impersonal hierarchy. Jaques’ (1976, 1988) work on the requisite organisation provides both a theory of excellent managers and an approach for the human development of high potentials within any organisation. The theory of the excellent manager is based on the idea of an ongoing cognitive adaption to higher levels of organisational complexity. One core determinant is time: the higher the level of organisational complexity, the longer the time horizon involved. For instance, a local shop has to plan its activity (personnel, trading stock, liquidity, etc.) on a timescale of days to months; in comparison, the strategic expansion of a multinational company is a project that may take years. Accordingly, the human development approach is based – roughly speaking – on providing the trainee with opportunities to improve his/her time-based decision-making. An alternative view of organisation is provided by the resource approach (e.g., Penrose, 2009/1959): organisations such as companies can be considered as pools of more or less impersonal resources, of which the organisation can make varying use. Expertise is then an organisational resource that can, if appropriate, be outsourced (Mieg, 2007). 3. In our context, teams are defined by their personal division of labour. A key role for the success of a team lies with the person responsible for the team – the manager or coach. Clear evidence comes from innovation research by Scholl (1999, 2004), who distinguished between restrictive and promotive control. Restrictive control describes a form of exerting power when the will of the team manager prevails against the interests of the individual team members. In contrast, we could speak of promotive control, which is when the team manager exerts influence on the members in line with their interests. Scholl (1999, 2004) demonstrated that restrictive control – in contrast to promotive control – has negative impacts on innovation processes. Restrictive control “induces information pathologies that in turn lower the effectiveness of joint action” (1999, p. 101; see also Scholl & Riedel, 2010). I would argue that we also find the effect of restrictive vs. promotive control in sports, and firms providing environmental expertise.1 More generally, teams are well researched in social psychology, as reviewed by Levine and Moreland (1990). 4. Individual experts and the issue of fostering expertise: Our model of embedded expertise, as presented in figure 2, includes two forms of experts. At higher levels, we have some kind of managerial structure; however, it is the high performers at the basic level who must deliver excellent results – either individually or as a team. This dichotomy of expertise is described by my model of two factors of expertise (Mieg, 2009), the first factor being expertise, the second professionalism. Excellence refers Centres of Excellence 79
to top performance in a domain, and becomes particularly obvious in established disciplines within sports or science (cf. Ericsson, 1996). Professionalism refers to the managerial capabilities within the particular domain. If we focus on the individual expert, isolated from his/her organisational embedding, the best-researched and most cited theoretical approach is based on deliberate practice (Ericsson et al., 1993), which suggests that: any domain requires approximately ten years of intense training with the goal of continuous improvement in order become an expert.
Process Component: Selection Based on Networks, Hierarchies or Markets The relationship between individual expert and organisational form may change. Teams in professional sports such as soccer are constantly reshuffled; new “experts” replace old ones. Sometimes, one’s expert role within an organisation changes: an athlete may become coach; a specialized staff member may become a director of his/her department. These changes in the allocation of experts to organisational forms happen quite often and are triggered by selection processes to find out: which expert is best for this job? A first approach is given by Ericsson’s concept of the representative task. He argues that superior expert performance “is a reliable phenomenon that can in many instances be captured by representative tasks under controlled laboratory conditions” (Ericsson, 1996, p. 7). Such tasks can be easily defined in athletics: to run faster or jump higher than other athletes under defined conditions (distance, wind conditions, starting procedure, etc.). However, very often, excellence can only be decided by the outcomes of matches, for instance in tennis or chess. We then formulate championships and a ranking system to integrate results from a series of matches. An even more difficult system of athletic valuation is found in team sports such as soccer: how to define or detect individual excellence in cases where overall performance is measured at the team level? In these cases, a derived measure comes into play: the market price for transferring athletes. In practice, the best predictor of champions in high-level team events in soccer, such as World and European Championships, has been the market valuations of the teams (Gerhards, Mutz & Wagner, 2012). Last, but not least, it seems impossible to identify representative tasks in professional domains such as health care or environmental services. In such domains, we might find tasks that define a necessary standard (performing an appendectomy; conducting an environmental impact assessment), which should be mastered without any error but seem insufficient to measure excellence. To arrive at a more systematic approach to valuation of embedded expertise, I refer to the distinction between hierarchy, market and network, as it has become a standard of governance research since Powell (1990). I use this distinction to introduce different logics or types of processes for selecting expertise. Market refers to more or less competitive price building, based on demands and supply. Price is the core means of communication and selection in market relations. Athletes may have a market price to transfer their services to another team, as have trading experts in investment banking. Hierarchy refers to work-on-command in structured employment relationships. Here, valuation and selection are linked to plans, targets and derived work profiles that define the selection criteria to employ experts and evaluate their work. Hospitals represent a perfect case of hierarchical selection and evaluation processes, with their elaborated division of expert labour. A third logic of the organisation of work is networks, constituting reciprocal relationships of independent partners (see table 3). In the context of regulating expertise, the main networks are professions (Freidson, 2001; Abbott, 1988); they represent the self- organisation of experts of a domain. As I argued elsewhere, professions monopolise the definition of the standards by which expert performance is valued (Mieg, 2010a). For instance, there might be great differentials in the price of appendix surgery, which is sometimes regulated by the state. Nevertheless, the medical criteria for a standard appendix procedure are always defined by the medical profession. Professions in which
80 H. A. Mieg
Table 3. Process Component of the Embedding of Expertise: Logics of Valuation and Selection Market Hierarchy Network Basis of valuation and Prices, salaries Plans, evaluation Professional selection standards and awards
Main source of valuation The public Institutions (state, The profession (for defining “the expert”) (consumers, market organisations…) participants….) performance is also subject to public opinion organise internal competitions for special awards in order to demonstrate their claim on valuation issues and to define valuation systems. Examples include the Pritzker Prize as a surrogate “architectural Nobel Prize”; or the annual Art Directors Club awards in the field of advertising.
Findings with Relevance to the Embedding of Expertise In the following, I present various types of findings from research on embedded expertise and the assessment of excellence. I refer to the three introduced domains of athletes, environmental experts and inventors. I discuss findings for which we have strong empirical evidence in one of these domains, and reflect them in the context of the other two domains. The implications for centres of excellence will be discussed in the next chapter.
Individual- vs. Organisational Planning Excellence in sports is often limited to an age-window somewhere between 15 and 30, depending on discipline. That means that a career as an elite athlete can only be pursued for a limited time, and generally offers no clear occupational perspective after the end of a competitive career. In open, capitalist societies, the decision to enter sport professionally has to be deliberated by the individual and their families. Specific life stages, such as the end of high school or university education or starting a family, might also effectively end a sporting career due to changing life plans. It is a common finding in German individual sports that success at younger ages is not predictive of top performance as a senior athlete (cf. Vaeyens, Güllich, Warr, & Philippaerts, 2009).2 One explanation (but not the only one possible) is some sort of demotivation resulting from juvenile training. The German system of selection is defined by early onset of selection and specialisation, as well as high quantity of training (cf. Emrich et al., 2008). The situation is different in less developed countries or those under totalitarian regimes. Here, sporting success provides opportunities for individual reward, but is also a core political tool, used to bolster domestic support and also to increase international prestige. This was particularly true of the former USSR as well as the GDR (German Democratic Republic). Both nation states considered sports a “weapon” to enhance their international reputation, and installed career structures for athletes, often linked to military service. Of course, many nations invest heavily in their sport systems, especially when hosting events such as the Olympic Games: the distinction is whether or not young talents are pressured by the state to follow a career as an athlete. A related phenomenon is sport as an opportunity for vertical social mobility among immigrants or children from lower socioeconomic backgrounds. In almost all large European countries, soccer is integrative in providing children from low-income families a pathway to prosperity. There is evidence for conflict or specific interaction of interests between top inventors and the companies they work for. Data on the mobility of inventors in Europe indicate that top inventors often change companies within a certain time period (Hoisl, 2007). I have interpreted this finding as representing a search by such employees for the perfect work Centres of Excellence 81 environment (Mieg, 2010). In some companies, more than 50 percent of patents are held by only a few inventors (Huber, 1998; Narin & Breitzman, 1995). These inventors thus have the power to negotiate their working conditions. The decisive point is generally not salary but the quality of the opportunities for research and development. Top inventors seek to realise their dream of creative and stimulating work. We have no similar phenomena in the field of environmental expertise. To be professionally engaged in environmental issues involves a life-long perspective. In this domain, we find an above-average retention rate of over 60% (cf. Brunner, Frischknecht, Hansmann, & Mieg, 2010). Even in leadership positions, the experts’ commitment to core environmental concerns remains very strong and influences their professional work (Mieg, Hansmann, & Frischknecht, 2012). In sectors that are generally unrelated to environmental tasks, e.g. public health, environmental experts found ways to re-define their jobs, thus functioning as pioneers for environmental concerns within those sectors (Mieg et al., 2012).
The Issue of Domain Specificity, Core Expertise and Transfer Domain specificity is a general finding from research on expertise (Ericsson, Charness, Feltovich, & Hoffman, 2006): excellence in one domain, e.g. physics, cannot be transferred to another domain such as medicine or education. This requires, on the one hand, very early specialisation for training in sport or music; on the other hand, it can involve ineptness in foreign domains. A recent study of former Olympic athletes showed that 50,000 of them currently live below the national poverty line (Wippert, 2011). If we define domains by means of their “physical” borders, then inventors are no “classical” domain. For inventors, we do not find any “physical” domain specificity; instead, invention is a purely domain-crossing activity (cf. Lemelson-MIT Program, 2003; Mieg, 2010a). Successful inventors do cross the borders between physics, medicine and education. This is true for all types of inventors, although research on independent inventors shows that specialisation pays off (Lettl, Rost, & von Wartburg, 2009). What we did find, however, are constraints imposed by different logics, such as implied by the field of technology vs. market-oriented behaviour. In general, inventors consider themselves as serving the long-term development of technology (Mieg, 2010a). The logic is to define a need and a possibility (to fly), and to achieve this via a functioning device (an airplane). Only a few inventors are market-oriented inventor-entrepreneurs (Mieg, Bedenk, Braun, & Neyer, 2012): they know the customers and markets, and develop products that can be sold. The logic of the market is different from that of technological development; customers’ demands may seem sub-optimal from a technological point of view, but nevertheless determine commercial success. Moreover, time constraints and deadlines play an important role in markets. Many inventors simply ignore time constraints or time altogether; such inventions will be ready “tomorrow”, even when this may take years. That is the reason why most employed inventors do not want to become independent or even entrepreneurs (Kassicieh, Radosevich, & Banbury, 1997), and why approximately 70% of independent inventors cannot live from selling their inventions (Mieg, Hoffmann, & Spars, 2010). What is the basic, core expertise of inventors? Inventors have to be creative. However, creativity is not confined to inventors, but seems to be a general human capability; neither does it appear to be a factor in the success of an invention (Mieg et al., 2012). I propose to define the core inventors’ expertise via a general physical-functional understanding or cognitive skill. This is not linked to any specific technology or domain. Similar findings were reported in sports: although early specialisation seems indispensable in some disciplines such as figure skating, the basis of expertise of elite athletes seems to be a general sporting ability in juvenile ages (Vaeyens et al., 2009). This insight is the basis for the new practice of talent recycling in UK sports, focusing “on the systematic search for additional or re-assigned talents at a fairly late stage” (Vaeyens et al., p. 1375). 82 H. A. Mieg
In my research with environmental experts, I tested whether we can find such a core expertise factor that explains excellence within a domain. Using data from more than 3,400 environmental experts who described their careers and personal capabilities, I could discriminate empirically two factors of expertise: excellence and professionalism (Mieg, 2009). As figure 3 shows, excellence depends on domain-specific academic education and on deliberate practice (as proposed by Ericsson). Professionalism depends on “key competencies”, meaning general, transferable skills for learning to learn (cf. Rychen & Salganik, 2001), and professional commitment to one’s domain. I also identified an interaction between domains and the two factors: Excellence plays a role in well-established domains, whereas professionalism seems important in new or changing domains. Professionalism in the form of active engagement within a domain (by defining standards, establishing professional schools, political lobbying for a domain…) seems necessary to build up the structures required to develop excellence, for instance in centres of excellence.
Dichotomies of Developing Embedded Expertise When it comes to finding experts for centres of excellence, we are faced with dichotomous decisions, the most important one being between selection of excellent personnel and socialisation. As introduced, we have different forms of selection and valuation, based on: market value (such as in top investment banking professionals), a hierarchy value (top employees) or a network value (Nobel Prize in sciences). An alternative to selection is socialisation, meaning to develop excellence within the centre. Here, again, we have several approaches to training internal talent (cf. figure 4): a general approach (often referring to educate a “personality” or “character”), specialisation (to train a football player for the central-defender position) or transfer (to retrain an elite defender as a midfield player). Very often, these options define a continuum, from general training to specialisation, and later transfer. However, this sequence is not immutable.
Figure 3. Two factors of expertise and their determinants (Mieg, 2009).
Figure 4. Dichotomies of developing embedded expertise. Centres of Excellence 83
Selection and socialisation strategies can be combined, e.g. by selecting excellent youngsters in order to form them as excellent senior professionals. However, there seem to be preferred combinations. Socialisation fits well with hierarchical forms of organization and valuation. For instance, Lundequist and Waxell (2010) studied the funding of research centres of excellence in Sweden. The “policy rhetoric” in Sweden favoured new science/industry collaborations. However, in order to speed up administrative processes, funding was administered via well-established channels and did not arrive at the “right” sort of institutions: funding did not go to new institutions or young universities demonstrating strong industrial collaboration, but rather to “old universities” that were already funded by the state and often showed little inclination to collaborate with industry. In this case, the national administration (hierarchical form of organization and valuation) preferred socialisation in terms of developing expertise at the bottom of the hierarchy (old universities). Conversely, socialisation is not as welcome in market-oriented organizations. For instance, Ambos and Reitsperger (2004) reported that German multinational companies with centres of excellence abroad abstain from socialisation in their centres. A second dichotomy is that between individual and team structures. In some domains, excellence and success is a matter of team performance. This not only applies to team sports but also to research and development or to investment banking. It is a truism that an excellent team is not simply the aggregation of excellent individuals. In general, teams need a leader or even a coach. Both teams and individuals can be subject to selection and socialisation. As with individuals, we can select or “socialise” excellent teams. A difficult but common situation is the need to select among elite individuals to produce a team that is subsequently capable of delivering excellence. In hospitals, universities or multinational companies, teams are part of an organisational hierarchy. There might therefore be an interaction or conflict between the individual orientation towards the valuation by peers, and the needs of a successful team for individual cooperation in joint, internal tasks. The third dichotomy refers to the two factors of expertise (Mieg, 2009). Excellence can be identified and fostered once relevant performance standards are established within a domain. Professionalism comes into play when the standards have to be managed or defined, or when domains have to be institutionalised. Engagement for a team – for instance as a faculty dean – may seem to be an additional motivation of elder, established individuals. This derived type of managerial task can become the subject of formalisation and institutionalisation, and thus turns into a domain with its own standards and excellence. This is the case for sports coaches (with centres of excellence for sport coaches). The dichotomy of excellence vs. professionalism becomes relevant to founding a company: Do you focus on single elite-performers (excellence) or a team of professionals (professionalism)? Baron and Hannan (2002) studied the long-term success of Silicon Valley start-ups: Companies based on professional teams, e.g. “classical” engineering or planning firms, showed the highest survival rates. However, once established, start-ups organized around single top-performers (excellence “stars”) turned out to be much more successful in terms of market capitalization.
Implications for Centres of Excellence In this section, I will show some implications for centres of excellence from our review of research on embedded expertise. I will start with the question: Who claims to be or to have a „centre of excellence”? I will then discuss three general lessons we can draw for centres of excellence. Reflecting the first two parts, I will sketch several strategies that we identify for centres of excellence.
84 H. A. Mieg
Table 4. Where Do We Find “Centres of Excellence”? Domains # % Countries # % 1 Universities 178 31 USA 328 57 2 Government 88 15 Australia 55 9 3 Research 70 12 International 39 7 4 Business 48 8 Canada 38 7 5 Hospitals 47 8 UK 24 4 6 Education 32 6 EU level 10 2 7 Military 22 4 Finland 8 1 8 Job Service 20 4 India 6 1 9 Social Media / Forum 16 3 Ireland 6 1 10 Sports 13 2 Germany 5 1 11 Multinational Companies 9 2 12 Foundations 5 1 Diverse 6 1 Diverse 50 9 Unclear 28 5 Unclear 11 2 Base 580 100 580 100 Note. Google-search, 695 entries3
Who Claims to Be a Centre of Excellence? Table 4 shows the results of an Internet study on the use of the term “centres of excellence.” We find that almost half of the centres of excellence have Internet representation among universities, at the governmental level and in research. We also see the use of the term „centres of excellence” for purely business purposes such as selling cars or furniture. Only 2% of the identified centres are associated with sports development, and several are explicitly linked to environmental issues, such as the Syracuse Center of Excellence in Environmental and Energy Systems. In terms of the host countries, there is complete dominance by the USA. The use of the term „centres of excellence” is also used at international levels, etc., such as in NATO, and has also diffused among the English-speaking countries. The many examples from Finland might be simply due to the Centres of Excellence Programme of the Finish Academy of Sciences, and can also be seen in the context of high levels of investment in the Finish national innovation system. What we do not see are the many “centres d’excellence” in the French-speaking world, for instance in Paris, nor equivalent institutions outside of the English-speaking world. Table 4 shows domains where a certain public communication of centres of excellence is vital, such as in research or education. However, the scientific literature indicates a strong line of research and discussion with regard to centres of excellence in multinational companies (Frost et al., 2002) as well as a cluster of case studies of hospitals. For instance, evaluation studies on centres of excellence in hospitals confirmed both increased patient satisfaction (Anderson et al., 2002) and higher quality and successful outcomes of medical procedures (Henry et al., 2009). Whereas the role of hospitals is also reflected by table 4, centres of excellence in multinational companies seem to be underrepresented. This may be due to their mainly internal function (cf. Reger & Zafrane-Bravo, 2002). Thus, we should keep in mind, that “centres of excellence” are not simply a case of embedded expertise but also of marketing some form of exclusivity.
General Lessons for Centres of Excellence In the following, I draw some lessons for centres of excellence in general, based on the findings with relevance to the embedding of expertise. I will integrate and consolidate them with what we know from research on centres of excellence in multinational companies. Centres of Excellence 85
Lesson 1: Take into account individual life plans! Working for a centre of excellence is a temporary commitment. This has become clear in the case of excellence in sports, and seems relevant to many other domains. If you want to attract excellent individuals, you should show and enable them to visualize their perspectives beyond the timeframe of this commitment. Ulbrich (2010) reported that experts did not wish to move into a centre of excellence; similarly, those hired for the centre of excellence did not want to move to further positions outside the centre, thus restraining the necessary turnover of the centre. To consider individual life plans might have helped, as in the case of National Centers of Excellence in Women’s Health, which struggled with the difficulty of “diminishing time available to women to participate in mentoring and leadership programs” (Morahan et al., 2001, p. 19). Lesson 2: Include options for excellence through transfer! Lesson 2 draws from research on top inventors: we never know which foreign method or piece of information from another domain might help increase excellence within the home domain. We should always be aware of the possibility of leveraging: top skills in one domain might be used to foster excellence in another domain. This is how Gardner (1998) described Freud’s high writing skills as a key for his seminal work in psychoanalysis. Moore and Birkinshaw (1998) consider centres of excellence in general as an opportunity to leverage knowledge within a multinational firm. Transfer is not a specific topic in the literature on centres of excellence. However, we read of lessons and postulations in that direction, such as the request for “diversity” (Morahan et al., 2001) or “interdisciplinarity” (Frey, 2004). Lesson 3: Combine practice in the centre of excellence with research on what you are doing. This last lesson is connected to the two preceding ones: scientific reflection provides the standards of our work. As shown (Mieg, Hansmann, & Frischknecht, 2012), standards represent formal social capital; they support communication and the transfer of skills. To define standards is particularly important in new or changing domains: if you do not establish or influence the relevant standards, then potential competitors will. Research on a centre of excellence always includes the observation of what familiar centres or individual leaders are doing, based on the idea of “comparing with the best” (Frey, 2004). Scientific reflection in centres of excellence includes evaluation studies (e.g., Anderson et al., 2002; Henry et al., 2009), comparative analyses of success factors (e.g., Frost et al., 2002) or studies on organisational processes (e.g., Paim et al., 2009; Reger & Zafrane- Bravo, 2002).
Strategies for Centres of Excellence Table 5 provides an overview of seven strategies for centres of excellence. The first two strategies are very general, focusing either on socialisation (i.e., investing in internal development of the centre) or on selection (via competition). Strategies three to seven focus on different phases of the development of expertise, from children to over-matured experts. All strategies refer to the attraction or selection of individuals, but can also be used for selecting or forming elite teams. Many centres must attract not only experts but also customers, clients or patients. In these cases (e.g., medical centres of excellence), an exclusivity strategy means not only ensuring high standards among the experts employed (e.g., top medical specialists) but also signals a high-quality service to customers (e.g., patients). This also explains the high numbers of centres of excellence among universities and hospitals (table 4). Some strategies may require considerable scientific support, such as in the case of total screening4 or talent recycling. In other strategies, such as “Cutting Diamonds” or the “Harnack” principle, professional selection criteria prevail (e.g., talent in sports, scientific merits). The “Harnack” principle guided the installation of national research centres in Germany (the predecessor of the present-day Max Planck Society): to provide the top expert with all the necessary resources, and allow the experts to define their research 86 H. A. Mieg
Table 5. Strategies for Centres of Excellence Strategy Description Sort of Levels Valuation & Domains Expertise (figure 2, Selection (examples) table 2) (table 3) Exclusivity Provide high Social- Organisations, All types Universities (facilities, quality, restrict isation all levels Government status) admission Hospitals Education
Competition Competitive Selection All levels All types Sports admission Research process Government
Total Test a complete Children Society, Scientific Sports screening young cohort of Individuals Research your population Military
Cutting Pick out high Novices Organisations, Professional Sports diamonds potentials at a Teams, Society Multinational very early stage companies Education Relative Promote those Advanced Organisations Market Business singularity who are distinct
“Harnack” Employ the best Top Society, Professional Research (simply the individual, experts Organisations Business best) provide full task- Hospitals autonomy
Talent Reuse experts (Over) All levels Scientific, Sports recycling from other matured Network Government domains (leveraging) programme and goals. This seems also a risky but – in case of success – a very powerful strategy for founding innovative technology firms (Baron & Hannan, 2002). A less risky strategy for commercial centres of excellence is to promote distinctiveness, for instance in car repair or banking. Table 5 also relates levels of embedded expertise and example domains (as in table 4) to strategies. We find that almost all strategies are applied in sports. Many strategies seem suitable for directing governmental funding in research, as in the case of the Australian Research Council Centre of Excellence for Coral Reef Studies. However, it should be noted: The relationships in table 5 are only draft proposals, and have a conceptual status: they are intended to direct empirical research on centres of excellence.
Discussion: Who Defines Excellence? My paper on expertise in the context of centres of excellence was intended as a review. The guiding questions were: How can we understand centres of excellence as an organisational form of embedded expertise? What can we learn about embedded expertise in general? Due to the lack of material in the research literature, the review has become a conceptual paper, connecting research on expertise to that on organisational theory. For the discussion, I will review my approach with regard to the guiding questions, the underlying assumptions and the choice of domains. We will see that much of the discussion leads to the question: Who defines excellence? Centres of Excellence 87
Centres of Excellence and What We Can Learn About Embedded Expertise in General How did the analyses and concepts in the previous chapters contribute to an understanding of centres excellence as an organisational form of embedded expertise? I would like to emphasize three points: First, the analyses have increased the range of relevant organisational forms to be studied. The common organisational form for research on embedded expertise is the company, the reason being the amount of management research already undertaken. As shown, there are at least two further organisational levels: those of national regulations or the team (figure 2). As demonstrated, both levels are highly relevant to both elite sports and top inventors. Secondly, the focus on domains of centres of excellence has been enlarged. The scientific literature on centres of excellence is dominated by studies on hospitals and multinational companies. My analysis of embedded expertise used alternative domains: elite sport, top inventors and environmental professionals. Finally, looking at self-indications as “centres of excellence”, universities, governmental institutions and commercial centres came into play. Thirdly, not only excellence but also professionalism has been considered as a form of organised expertise. The difference becomes relevant when measures for identifying excellence are lacking. For instance, cutting diamonds (table 5) is a matter of professional experience with regard to novices. Criteria for categorising diamonds often refer more to personal characteristics such as the motivation of the novice and family background than initial aptitude. The following lessons may be drawn regarding the study of embedded expertise: First, the study of centres of excellence involves a re-emphasis on the individual expert, i.e. human capital. Institutions of all organisational forms take hold on the individual expert (figure 2). Second, the relationship between domain specificity of expertise and transfer of expertise is still under discussion. The assumption that, as experts get older, their expertise becomes increasingly specialised, seems to be overly restrictive, otherwise talent recycling would not be successful. So the question remains: Given a domain, what is the core expertise of successful experts? Third, centres of excellence face the same “make-or-buy” dichotomy as large companies – in our terms: selection vs. socialisation. Thus, the discussion on outsourcing within the managerial literature (e.g., Belcourt, 2006) can be transferred to the study of embedded expertise (Mieg, 2007). There are, of course, limitations to the study of centres of excellence as a form of embedded expertise, as presented in the previous chapters. First of all, the dynamics of these centres can in no way be reduced to selection processes. We would need to take into account, for instance, industrial or regional transformation processes (e.g., Harvey, 2011) that change the socio-political and commercial environment of centres of expertise. Secondly, centres of expertise contain more expert roles than considered by table 2 (cf. Mieg, 2001, 2006). In addition to operating specialists (scientists, athletes, lawyers, etc.), we have coaches and managers as well as supporting specialists. For instance, in innovation research, Hauschildt and Kirchmann (2002) suggested that any innovation requires – besides the inventing engineers – several expert promoters in order to generate the necessary micro-political and technological support within a company. Last but not least, any successful centre of excellence requires strong leadership (cf. Gundermann, 2006). This again relates the study of centres of excellence to the general issue of management (as conceived by Jaques, 1988). 88 H. A. Mieg
Reviewing the Assumptions My explanation of centres of excellence rests on two general assumptions regarding expertise and organising: 1) Assumed homogeneity of expertise: The development of excellence (top expertise) is structurally equivalent in all domains. 2) Assumed homogeneity of organisation: Centres of excellence in different domains share the same organisational logic. The assumption of homogeneity of expertise can be contested. Shanteau (1992) distinguished two classes of domains, one with generally reliable expert judgments (e.g., physics), the other with only contestable expert judgments (e.g., courts). As already introduced (figure 3), in my own research on the still unresolved field of environmental expertise, I found an interaction between the two factors of expertise (excellence, professionalism) and the domains, depending on the degree of institutionalisation of a domain (Mieg, 2009): domain-specific “excellence” is a model for developing expertise particularly within domains with established standards (e.g., environmental impact assessment); in domains with unclear or new best practice, then, “professionalism” (based on general competences) plays the key role. These domain differences may also be relevant to centres of excellence for such domains. We can argue, however, that although it is difficult to define a clear measure for the degree of expertise in any domain, it does not seem to be a problem to identify the top performers (Hoffman, Shadbolt, Burton, & Klein, 1995). Similarly, we can contest the assumption of the homogeneity of organisation. As shown by table 4, centres of excellence may serve very different purposes; for instance, high- quality research, educating elites or simply increasing sales. It might be inappropriate to define these all as expert organisations, as they take very different forms. We can suspect that an independent law firm or a medical practice operate on a different logic than expert divisions of companies, as do hybrid organisations such as hospitals or universities. However, there is limited research in that field, let alone with regard to centres of excellence. I assume that expert organisations such as law firms are more focused on the organisation of professionalism than excellence. We must leave this topic for future research.
Labelling “Centres of Excellence” Depending on the Domain A further challenge arises from the findings in table 4. My initial set of domains (sports, environmental expertise, top inventors) does not match the distribution of “centres of excellence”, particularly with regard to sports. A solution might be to distinguish between institutions that are called “centres of excellence” and those institutions that promote excellence under different titles, especially in sports. Then, however, we are faced with another problem: to explain why some domains or institutions have an interest in defining a „centre of excellence” whereas others do not. For the further discussion of this point, I refer to the three sources of valuation: market – hierarchy – network. To start with, from a market-based perspective, we should ask: who should be attracted by a „centre of excellence”? We see a clear customer-orientation in case of the “business” centre of excellence. Similarly, hospitals and the education domain are interested in attracting “customers” (patients, students). In the case of universities and research, we can suspect that experts and public funding should also be attracted. However, this market- based pattern of explanation does not completely function for the many centres of excellence in the governmental and military domains. From a hierarchical point of view, the definition of a centre of excellence is connected with the allocation of authority. Centres of excellence are invested with some authority or are considered as authorities – this might explain the many centres of excellence in the military and governmental domains. Hierarchical valuation might also be the starting Centres of Excellence 89 point for an “attribution cascade” of excellence: those (individuals, institutions) who occupy a position of “excellence” receive the lion’s share of attention and positive evaluations. This might explain, to some extent, the very unequal distribution of patent applications among employed inventors: a few inventors often hold more than half of a company’s patents (Narin & Breitzman, 1995; Huber, 1998). Thus, centres of excellence might also profit from such an attribution cascade by attracting high potentials. From a network point of view, we see a very important source for valuation and selection: professional peers. As argued elsewhere (Mieg, 2010b), in many domains where judgment is uncertain and professional skills are complex and require long education, the evaluation of performance is a matter of the particular profession. In some domains, the evaluation monopoly is the last stronghold of professions: scientists want to see other scientists promoted (dissertation, professorship) mainly via scientific criteria; similarly, core medical performance (e.g., clinical outcomes) is subject to peer review within the medical profession. Thus, centres of excellence will also be subject to peer review, for instance in universities or hospitals. This professional evaluation seems particularly important in hybrid “expert” organisations, such as hospitals, where career managerial staff rarely share the same professional background as their core clinical personnel. We see that centres of excellence are not only organisational forms of embedded expertise: in many cases, they have to signal their “excellence” to their environments or audiences. As in the study of expertise, we should be aware of differences between the domains involved. These differences refer not only to the question of whether excellence within a specific domain is measurable; they also question whether the organisational logic – embedded in teams, companies, expert organisations or social media projects – is the same across domains such as sport, scientific research or public health.
Notes 1 German sports research has repeatedly applied the upper echelon approach (Wulf & Hungenberg, 2006; Neubauer, 2009). This concept (Hambrick & Mason, 1984) explains the organisational outcomes as depending on the personal characteristics of top management. Such characteristics are: age, education, career experiences, socioeconomic background, etc. Hambrick and Mason intended to explain the behaviour of the top management of companies and the resulting success of a company. I would argue that if personal characteristic of managers influence organisational outcomes, this influence should be much more significant in managing teams, whether as a coach or project leader. 2 This does not generally hold in team sports. For instance, in handball, there is a clear correlation between juvenile training intensity/success and professional success (Fasold, Heinen, & Gobel, 2011). 3 The Google-search was conducted on 29 June 2012 at 17:13 (MET), search string: “centre OR centres OR center OR centers of excellence”. Thus, we did not include any centres “for” excellence. Categorization by country was conducted by country domain if explicit; otherwise, by registered street address, if available. Domains were categorized according to where the centre of excellence is institutionally located, “research” referring to independent research centres, “university” to university-based centres of excellence, “government” to explicitly government-linked centres of excellence (e.g., within ministries, etc.) and “education” to centres with a focus on educative programs. For the analysis, results from Wiki (7), News sites (99), N/A (7) and Search (2) were neglected. Total n = 695 results, n = 580 for the final analysis. I thank Fritz-Julius Grafe for conducting the Google-search. 4 Total screening was, for instance, the basis for the extraordinary success of physical education in the former German Democratic Republic. Post-1970, every 6th young boy 90 H. A. Mieg
and every 18th young girl had to start training in one of the specialised GDR national sports training centres (so to say: Centres of excellence), which formed the basis of a system of sports schools, sports research institutes and competitions (Teichler & Reinartz, 1999).
Acknowledgement I thank Wolfgang Scholl for his comments on an earlier version of this paper.
References Abbott, A. (1988). The system of professions. sports advancement in Germany: Review and Chicago: The University of Chicago Press. perspectives]. Leistungssport, 38(1), 1–17. Acemoglu, D., & Robinson, J. A. (2012). Why nations Ericsson, K. A. (Ed.). (1996). The road to excellence: fail: The origins of power, prosperity, and The acquisition of expert performance in the poverty. New York: Crown Business. arts and sciences, sports, and games. Mahwah, Ambos, B., & Reitsperger, W. D. (2004). Offshore NJ: Erlbaum. centers of excellence: Social control and Ericsson, K. A. (1998). The scientific study of success. Management International Review, expert levels of performance: General 44(2), 51–65. implications for optimal learning and Anderson, R. T., Weisman, C. S., Hudson Scholle, S., creativity. High Ability Studies, 9(1), 75–100. Henderson, J. T., Oldendick, R., & Camacho, F. Ericsson, K. A. (2006). An introduction to “The (2002). Evaluation of the quality of care in the Cambridge handbook of expertise and clinical care centers of the National Centers expert performance”: Its development, of Excellence in Women’s Health. Women’s organization, and content. In K. A. Ericsson, N. Health Issues, 12(6), 309–326. Charness, P. Feltovich, & R. R. Hoffman (Eds.), Baron, J., & Hannan, M. (2002). Organizational The Cambridge handbook of expertise and blueprints for success in high-tech start-ups. expert performance (pp. 3–19). Cambridge, California Management Review, 44(3), 8–36. UK: Cambridge University Press. Belcourt, M. (2006). Outsourcing: The benefits and Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. risks. Human Resources Management Review, (1993). The role of deliberate practice in the 16(2), 269–279. doi: 10.1016/j.hrmr.2006. acquisition of expert performance. 03.011 Psychological Review, 100(3), 363–406. Brunner, S. H., Frischknecht, P., Hansmann, R., & Ericsson, K. A., Charness, N., Feltovich, P., & Mieg, H. A. (2010). Environmental Sciences Hoffman, R. R. (Eds.). (2006). The Cambridge education under the microscope: Do graduates handbook of expertise and expert promote a societal change towards performance. Cambridge, UK: Cambridge sustainability? Retrieved from Swiss Federal University Press. Institute of Technology Zurich, Department of Fasold, F., Heinen, T., & Goebel, R. (2011). Zum Environmental Sciences: http://www.env.ethz. Stand der Handballnachwuchsförderung in ch/docs/survey/2010spec_EnvSci_underthe Deutschland: eine Analyse ausgewählter microscope.pdf Effekte für den männlichen Bereich [Youth Campbell, D. T. (1960). Blind variation and development training for handball in selective retention in creative thought as in Germany: An analysis of selected effects in other knowledge processes. Psychological males]. Leistungssport, 41(4), 28–32. Review, 67(6), 380–400. Freidson, E. (2001). Professionalism: The third logic. Campbell, D. T. (1987). Selection theory and the Cambridge, UK: Polity. sociology of scientific validity. In W. Callebaut Frey, D. (2004, July). Leiter der Bayerischen & R. Pinxten (Eds.), Evolutionary epistemology Eliteakademie im Gesprach mit Marion Glück- (pp. 139–158). Dordrecht, The Netherlands: D. Levi [Director of the Bavarian Elite Academy, Reidel. interview with Marion Glück-Levi][interview de Sombre, S., Woschnack, U., Näf, M., & Mieg, H. A. transcript]. Retrieved from Bayerischer (2002). Professionelle Umwelt-Tätigkeiten in Rundfunk: http://www.br-online.de/alpha/ der Schweiz 2001: Bericht zur Befragung Herbst forum/vor0407/20040721.shtml. 2001 [Professional environmental services in Frost, T. S., Birkinshaw, J. M., & Ensign, P. C. (2002). Switzerland: Report of the 2001 survey]. Bern: Centers of excellence in multinational Schweizerischer Verband der corporations. Strategic Management Journal, Umweltfachleute SVU. (available online via 23(11), 997–1018. doi: 10.1002/smj.273 www.mieg.ethz.ch/docs) Gardner, H. (1998). Extraordinary minds. Portraits of Emrich, E., Pitsch, W., Güllich, A., Klein, M., exceptional individuals and an examination of Fröhlich, M., Flatau, J., … & Anthes, E. (2008). our extraordinariness. London: Phoenix. Spitzenförderung in Deutschland: Gerhards, J., Mutz, M., & Wagner, G. G. (2012). Die Bestandsaufnahme und Perspektiven [Elite Berechnung des Siegers [Calculating the Centres of Excellence 91
winner]. Frankfurter Allgemeine Zeitung. Levine, J. M., & Moreland, R. L. (1990). Progress in Retrieved from http://www.faz.net/aktuell/ small group research. Annual Review of feuilleton/geisteswissenschaften/fussball- Psychology, 41, 585–634. doi: em-2012-die-berechnung-des-siegers- 10.1146/annurev.ps.41.020190.003101 11775281.html Lundequist, P., & Waxell, A. (2010). Regionalizing Gunderman, R. B. (2006). Achieving excellence in “Mode 2”? The adoption of centers of medical education. Berlin: Springer. excellence in Swedish research policy. Hallman, J. C. (2003). The Chess artist. New York: Geografiska Annaler Series B Human Thomas Dunne. Geography, 92(3), 263–279. Hambrick, D. C., & Mason, P. A. (1984). Upper Mieg, H. A. (2001). The social psychology of echelons: The organization as a reflection of expertise: Case studies in research, its top managers. Academy of Management professional domains, and expert roles. Review, 9(2), 193–206. Mahwah, NJ: Lawrence Erlbaum Associates. Harvey, D. (2011). Roepke Lecture in Economic Mieg, H. A. (2002). The use of abstract knowledge Geography: Crisis, geographic disruptions in professional competition: A study on the and the uneven development of political Swiss market for professional environmental responses. Economic Geography, 87(1), 1–22. services. Schweizerische Zeitschrift für Hauschildt, J., & Kirchmann, E. (2002). Teamwork Soziologie/Swiss Journal of Sociology, 28(1), for innovation: The ‘troika’ of promoters. R&D 27–45. Management, 31(1), 41–49. Mieg, H. A. (2006). Social and sociological factors Henry, G. D., Kansal, N. S., Callaway, M., Grigsby, T., in the development of expertise. In K. A. Henderson, J., Noble, J., … & Mook, T. M. Ericsson, N. Charness, P. Feltovich, & R. R. (2009). Centers of excellence concept and Hoffman (Eds.), The Cambridge handbook of penile prostheses: An outcome analysis. The expertise and expert performance (pp. 743– Journal of Urology, 181(3), 1264–1268. 760). Cambridge, UK: Cambridge University Hodges, N. J., Starkes, J. L., & MacMahon, C. (2006) Press. Expert performance in sport: A cognitive Mieg, H. A. (2007). Experts in context: perspective. In K. A. Ericsson, N. Charness, P. Understanding the effects of outsourcing Feltovich, & R. R. Hoffman (Eds.), The expertise. In K. Mosier & U. Fischer, (Eds.), Cambridge handbook of expertise and expert NDM 8: Eighth international conference on performance (pp. 471–488). Cambridge, UK: naturalistic decision making: proceedings. San Cambridge University Press. Francisco, CA: San Francisco State University. Hoffman, R. R., Shadbolt, N. R., Burton, A. M., & Mieg, H. A. (2008a). Professionalisation. In F. Klein, G. (1995). Eliciting knowledge from Rauner & R. Maclean (Eds.), Handbook of experts: A methodological analysis. technical and vocational education research Organizational Behavior and Human Decision (pp. 502–508). Dordrecht: Springer. Processes, 62(2), 129–158. Mieg, H. A. (2008b). Professionalization and Hoisl, K. (2007). Tracing mobile inventors: The professional identities of environmental causality between inventor mobility and experts: The Case of Switzerland. Journal of inventor productivity. Research Policy, 36(5), Integrative Environmental Sciences, 5(1), 41– 619–636. 51. doi: 10.1080/15693430701859653 Huber, J. C. (1998). Invention and inventivity is a Mieg, H. A. (2009). Two factors of expertise? random, Poisson process: A potential guide to Excellence and professionalism of analysis of general creativity. Creativity environmental experts. High Ability Studies, Research Journal, 11(3), 231–241. 20(1), 91–115. doi: 10.1080/135981309028604 Jaques, E. (1976). A general theory of bureaucracy. 32. Aldershot: Gregg Revivals. Mieg, H. A. (2010a). Focused cognition: Information Jaques, E. (1988). Requisite organization. Arlington: integration and complex problem solving by Cason Hall & Co. Publishers. top inventors. In K. L. Mosier & U. M. Fischer Kassicieh, S. K., Radosevich, H. R., & Banbury, C. M. (Eds.), Informed by knowledge: Expert (1997). Using attitudinal, situational, and performance in complex situations (pp. 41–54). personal characteristics variables to predict London: Taylor & Francis. future entrepreneurs from national laboratory Mieg, H. A. (2010b). Professionalisierung: eine inventors. IEEE Transactions on Engineering dreifache Autonomieregulation Management, 44(3), 248–257. [Professionalisation: A threefold regulation of Lemelson-MIT Program (2003, August). The autonomy]. In K. von Schlieffen (Ed.), architecture of invention [workshop report]. Professionalisierung und Mediation (pp. 15– Retrieved from Massachusetts Institute of 26). München, Germany: C.H. Beck. Technology, School of Engineering: Mieg, H. A., Bedenk, S., Braun, A., & Neyer, F. J. http://web.mit.edu/INVENT/n-pressreleases/ (2012). How emotional stability and openness downloads/architecture.pdf. to experience support invention: A study with Lettl, C., Rost, K., & von Wartburg, I. (2009). Why are German independent inventors. Creativity some independent inventors ‘heroes’ and Research Journal, 24(2–3), 200–207. doi: others ‘hobbyists’? The moderating role of 10.1080/10400419.2012.677341 technological diversity and specialization. Mieg, H. A., Hansmann, R., & Frischknecht, P. M. Research Policy, 38(2), 243–254. (2012). National sustainability outreach 92 H. A. Mieg
assessment based on human and social Rychen, D. S., & Salganik, L. H. (Eds.). (2001). capital: The case of Environmental Sciences Defining and selecting key competencies. in Switzerland. Sustainability, 4(1), 17–41. Ashland, OH: Hogrefe. doi:10.3390/su4010017 Scholl, W. (1999). Restrictive control and Mieg, H. A., Hoffmann, C., & Spars, G. (2010). information pathologies in organizations. Evaluierung der volkswirtschaftlichen Journal of Social Issues, 55(1), 101–118. Bedeutung von Einzelerfindungen und deren Scholl, W. (2004). Innovation und Information: Wie Umsetzungspotential am Standort Berlin. Studie in Unternehmen neues Wissen produziert wird im Auftrag der Senatsverwaltung für Wirtschaft, [Innovation and information: How enterprises Technologie und Frauen, Bericht [Evaluation of produce new knowledge]. Göttingen, the economic significance of inventions by Germany: Hogrefe. private inventors and their market potential Scholl, W., & Riedel, E. (2010). Crossing power in Berlin. Study for the Berlin Senate level and power use: Differential effects on Administration, report]. Retrieved from performance and learning. Social Influence, http://www.berlin.de/imperia/md/content/ 5(1), 40–58. senwirtschaft/innovationspolitik/bedeutung_ Shanteau, J. (1992). The psychology of experts. In einzelerfindungen.pdf G. Wright & F. Bolger (Eds.), Expertise and Moore, K., & Birkinshaw, J. M. (1998). Managing decision support (pp. 11–23). New York: knowledge in global service firms: Centers of Plenum. excellence. Academy of Management Teichler, H. J., & Reinartz, K. (1999). Das Executive, 12(4), 81–92. Leistungssportsystem der DDR in den 80er Morahan, P. S., Voytko, M. L., Abbuhl, S., Means, L. J., Jahren und im Prozeß der Wende [The Wara, D. W., Thorson, J., & Cotsonas, C. E. competitive sports system of the GDR in the (2001). Ensuring the success of women 1980s and subsequent to German faculty at AMCs: Lessons learned from the reunification]. Schorndorf: Verlag Karl national centers of excellence in women’s Hofmann. health. Academic Medicine, 76(1), 19–31. Ulbrich, F. (2010). Deploying centres of excellence Narin F., & Breitzman, A. (1995). Inventive in government agencies. Electronic productivity. Research Policy, 24(4), 507–519. Government, an International Journal, 7(4), Neubauer, D. (2009). Die strategische 362–379. Zusammensetzung von Aufsichtsrat und Vaeyens, R., Güllich, A., Warr, C. R., & Philippaerts, Vorstand professioneller Fußballvereine in R. (2009). Talent identification and promotion Deutschland [The strategic composition of programmes of Olympic athletes. Journal of supervisory and managerial boards in Sports Sciences, 27(13), 1367–1380. German professional soccer clubs]. Verband Schweizer Abwasser- und Norderstedt, Germany: Books on Demand Gewässerschutzfachleute (2012). Swiss water GmbH. association. Retrieved from: http://www.vsa. OECD Organisation for Economic Co-operation ch/en/about-vsa/ and Development (1999). Managing National Weber, R. J. (1996). Toward a language of invention Innovation Systems. Paris: OECD. and synthetic thinking. Creativity Research Paim, R., Nunes, V., Pinho, B., Santoro, F., Cappelli, Journal, 9(4), 353–364. C., & Araujo Baião, F. (2009, March). Weber, R. J. (2006, July). The Wright Brothers and Structuring a process management center of the heuristics of invention. Paper presented at excellence. Paper presented at the ACM the conference “Expertise in context”, Symposium on Applied Computing, Waikiki, Humboldt-University, Berlin. Hawaii. doi: 10.1145/1529282.1529342 Weisberg, R. W. (2006). Creativity: Understanding Penrose, E. T. (2009/1959). The theory of the growth innovation in problem solving, science, of the firm (4th ed.). New York: John Wiley. invention, and the arts. Hoboken, NJ: Wiley. Powell, W. W. (1990). Neither market nor hierarchy: Wippert, P.-M. (2011). Kritische Lebensereignisse in network forms of organizations. In B. M. Staw Hochleistungsbiographien: Untersuchungen an & L. L. Cummings (Eds.), Research in Spitzensportlern, Tänzern und Musikern Organizational Behavior (Vol. 12, pp. 295–336). [Critical life-events in high-performance Greenwich, CT: JAI. biographies: Studies of elite athletes, dancers Reger, G., & Zafrane-Bravo, C.-E. (2002, August). and musicians]. Lengerich, Germany: Pabst. Managerial implications of the research on Wulf, T., & Hungenberg, H. (2006). Erfolg von centers of excellence: A conceptual view. Fußball-Bundesligavereinen: eine empirische Paper presented at the Engineering Analyse des Beitrags von Mannschaft, Trainer Management Conference (IEMC ’02), und Sportmanager [Success of Bundesliga Cambridge. doi: 10.1109/IEMC.2002.1038403 soccer clubs: An empirical analysis of Rütten, A., Ziemainz, H., & Röger, U. (2005). impacts by team, trainer and manager]. Qualitätsgesichertes System der Talentsuche, - Retrieved from Institut für auswahl und -förderung [Quality-based Unternehmensplanung IUP: http://www.iup- system of searching, selecting and advancing online.org/download/IUP AP 06-01 Erfolg von talent in sports]. Köln, Germany: Sport und Fuball-Bundesligavereinen. pdf Buch Strauß. Centres of Excellence 93
The Author
Prof. Dr. Harald A. Mieg has conducted research on expertise and professionalization in inventors as well as in the context of urban and environmental planning. Currently, he is responsible for the implementation of undergraduate research at the University of Applied Sciences, Potsdam. Mieg is affiliated with the Swiss Federal Institute of Technology and Humboldt- Universität zu Berlin.
94 H. A. Mieg
Talent Development & Excellence Notes on the Achievement of Authoritative Knowledge 95 Vol. 6, No. 1, 2014, 95–132 Technology and Social Interaction: Notes on the Achievement of Authoritative Knowledge in Complex Settings Brigitte Jordan*
Abstract: Within any particular social situation a multitude of ways of knowing exist, but some carry more weight than others. Some kinds of knowledge are discredited and devalued, while others become socially sanctioned, consequential, “official,” and are accepted as grounds for legitimate inference and action. In this paper I explore the role of technology in the constitution of such authoritative knowledge by drawing on videotaped data from two complex, high-technology work settings: an American obstetrics ward and an airlines operations room. Videotapes were analyzed using methods of Interaction Analysis, a microanalysis of participants’ activities in relation to each other, the physical space in which they operate, and the artifacts and technologies which play a role in getting their business accomplished. I use these cases as a means to illustrate some of the linguistic, interactional, and artifactually- based mechanisms by which, in high technology settings, authoritative knowledge comes to be distributed, displayed and used. An understanding of these mechanisms is crucial for the design of collaborative working and learning environments that are conducive to getting necessary business done in an efficient way while, at the same time, empowering their users.
Keywords: authoritative knowledge (AK), conversation analysis (CA), video-based interaction analysis, birth knowledge, airlines operations
Within any particular social situation a multitude of ways of knowing exist, but some carry more weight than others. Some kinds of knowledge become discredited and devalued, while others become socially sanctioned, consequential, even “official,” and are accepted as grounds for legitimate inference and action. In this paper, I explore the role of technology and social interaction in the constitution and display of such authoritative knowledge by drawing on videotaped data from two complex, high-technology work settings: an American obstetrics ward where a baby is delivered and an airline’s operations room where a plane switch is orchestrated. I will argue that the “ownership” of the artifacts necessary to accomplish the work simultaneously defines and displays who should be seen as possessing authoritative knowledge and, consequently, legitimate decision-making power. I have chosen these situations not because of a special interest in American obstetrics or in airlines’ operations, but rather because these two cases provide particularly telling examples of work settings where the business at hand is collaboratively accomplished and technologically mediated. Furthermore, I have good video data for both of them, which are essential for doing the kind of close analysis that I hope will make my point. My argument thus does not hinge on whether American births generally look like the one I describe; nor am I making a case here that distributed access to the artifacts of work is typical for airlines’ operations rooms or even for communication and control centers. The conclusions I draw apply to American hospital births and airlines operations rooms only to whatever extent particular births and particular operations rooms partake of the social and material features outlined below. Where there is a different social organization and
* Institute for Research on Learning, 2550 Hanover Street, Palo Alto, CA 94304, USA. Email: [email protected]
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online) 2014 International Research Association for Talent Development and Excellence http://www.iratde.org
96 B. Jordan different distribution of technological resources, different characteristics will prevail. Nevertheless, this analysis is at least suggestive for work settings that share the technological, social-interactional, spatial, and organizational characteristics of the cases described here. In my first example, a woman laboring in a high-technology hospital is ready to push her baby out. However, what her body tells her, what she knows (and displays) by virtue of her bodily experience, has no status in this setting. What counts is the technologically and procedurally based knowledge of the physician, which is inaccessible to the woman, but without which the birth literally is not allowed to proceed. Competing kinds of knowledge held by the woman and other participants in the scene are jointly suppressed and managed. In this case and others like it, authoritative knowledge and attendant decision making is hierarchically distributed. In my second example, I describe ongoing work activities in an airline’s operations room. Here, access to and familiarity with the crucial technologies is distributed across participants. The knowledge required to get the work done is continuously jointly produced and is displayed for inspection and appropriation by whoever may need it to further the collective work. The routine decisions required in this setting emerge through mutual consultation. They are produced collaboratively and with multiple inputs, in unremarkable fashion. I will argue that in this case and in cases like it authoritative knowledge is horizontally distributed. One of the aims of this report is to elaborate the notion of authoritative knowledge introduced in a series of earlier publications (Irwin & Jordan, 1987; Jordan, 1977, 1987a, 1989, 1993; Suchman & Jordan, 1988).
Authoritative Knowledge For any particular domain several knowledge systems exist, some of which, by consensus, come to carry more weight than others, either because they explain the state of the world better for the purposes at hand (“efficacy”) or because they are associated with a stronger power base (“structural superiority”), and usually both. Sometimes equally legitimate, parallel knowledge systems exist and people move easily between them, using them sequentially or in parallel fashion for particular purposes. But frequently, one kind of knowledge gains ascendance. The legitimization of one way of knowing as authoritative devalues, often totally dismisses, all other ways of knowing. Those who espouse alternative knowledge systems tend to be seen as backward, ignorant, or naive trouble makers. Whatever they might have to say about the issues up for negotiation is judged irrelevant, unfounded, and not to the point (Jordan, 1989). The constitution of authoritative knowledge is an ongoing social process that both builds and reflects power relationships within a community of practice (Lave & Wenger, 1991). It does this in such a way that all participants come to see the current social order as a natural order, i.e. the way things (obviously) are. 1 The devaluation of non-authoritative knowledge systems is one mechanism by which hierarchical social structures are generated, maintained, and displayed. The French anthropologist Pierre Bourdieu writes insightfully about the role which formal education may play in the devaluation of folk knowledge in a class-structured society: [Formal schooling] succeeds in obtaining from the dominated classes a recognition of legitimate knowledge and know-how (e.g. in law, medicine, technology, entertainment or art), entailing the devaluation of the knowledge and know-how they effectively command (e.g. customary law, home medicine, craft techniques, folk art and language, and all the lore handed on in the hedge-school of the witch and the shepherd …) and so providing a market for material and especially symbolic products of which the means of production are virtually monopolized by the dominant classes (e.g. clinical diagnosis, legal advice, the culture industry, etc. (Bourdieu & Passeron, 1977, p. 42) In the medical field, Paul Starr (1982) gives a compelling account of the historical transformation of authoritative medical knowledge in America. Well into the twentieth century, medical care was provided by a multi-stranded, pluralistic medical system within which the knowledge held by barber surgeons, homeopaths, folk healers of various kinds, Notes on the Achievement of Authoritative Knowledge 97 midwives, and other empirically based practitioners was considered authoritative by different parts of the population. A series of events culminating in the Flexner Report of 1910 resulted in establishing allopathic professional knowledge as the dominant form – a transformation which quickly delegitimized all other kinds of knowledge, putting the newly defined medical profession in a position of cultural authority, economic power, and political influence. Starr introduces the idea of “cultural authority” which refers “to the probability that particular definitions of reality and judgments of meaning and value will prevail as valid and true” and argues that the acquisition of cultural authority by doctors had the consequence that they came to be in charge of “the facts,” that is to say, have the authority to define when somebody is dead or alive, sick or well, competent or not (Starr, 1982, pp. 13-15). The process whereby the authority of any particular knowledge system and the power relations supporting it and benefiting from it are perceived not as socially constructed, relative, and often coercive, but as natural, legitimate, and in the best interest of all parties is termed “misrecognition” by Bourdieu and Passeron (1977). Others as well have pointed out that this process makes the achieved order of the world appear to be a fact of nature, with the consequence that the dominant positions in that order are also a fact of nature, and hence cannot be changed. The best way to avoid change or revolution is to make change or revolution literally unthinkable. Authoritative knowledge is persuasive because it seems natural, reasonable and consensually constructed. For the same reason it also carries the possibility of powerful sanctions, ranging from exclusions from the social group to physical coerciveness (Davis- Floyd, 1992; Irwin & Jordan, 1987). Generally, however, people not only accept authoritative knowledge (which is thus validated and reinforced), but are actively and unselfconsciously engaged in its routine production and reproduction. It is important to realize that to identify a body of knowledge as authoritative speaks, for us as analysts, in no way to the correctness of that knowledge. Rather, the label “authoritative” is intended to draw attention to its status within a particular social group and to the work it does in maintaining the group’s definition of morality and rationality. The power of authoritative knowledge is not that it is correct but that it counts. I want to further point out that when I, as the analyst, say that somebody “has” knowledge, authoritative or otherwise, this constitutes for me a commitment to try to come to an understanding of how participants in a social setting make that fact visible to each other, ratify it, enforce it, elaborate it and so on, since I see knowledge not as a substance that is possessed by individuals but as a state that is collaboratively achieved within a community of practice. By authoritative knowledge, I mean, then, the knowledge that participants agree counts in a particular situation, that they see as consequential, on the basis of which they make decisions and provide justifications for courses of action. It is the knowledge that within a community is considered legitimate, consequential, official, worthy of discussion, and appropriate for justifying particular actions by people engaged in accomplishing the tasks at hand. As Heath and Luff (1991) have pointed out, in order for people to work together, there must be a publicly available set of practices and reasonings which are developed and warranted within a particular setting, and which systematically inform the work and interaction of participants. In all social groups people provide justification for what they do, reasons for why they do what they do in this way and not another, or why, when trouble arises, it should have been done in a particular way. Authoritative knowledge is about accountability in a community of practice that produces and reproduces itself even as it produces and reproduces its version of authoritative knowledge. By authoritative knowledge I specifically do not mean the knowledge of people in authority positions. To the extent that such persons are members of a community of practice, they will share the local version of authoritative knowledge with other members, but it is the local production and display that is of importance for the present analysis. Authoritative knowledge is an interactionally grounded notion. What I am interested in here is how participants in 98 B. Jordan particular work environments make visible to themselves and to each other what the grounds are for their proceedings. I thus forego theoretically derived notions of authority and knowledge in favor of investigating how participants deal with such issues in actual work situations. In the following sections, I contrast the authoritative knowledge in use in two high technology settings: a labor ward and an airlines operations room. These particular cases vividly illustrate the ways in which technology and technology-based procedures become a resource for the collaborative production and display of authoritative knowledge.
The Labor Room
The Setting The first set of data for this analysis comes from a large research project on the dynamics of care during the second stage of labor which was carried out in a perinatal center of a western city between 1986 and 1989.2 The protocol for the project included videotaping of women’s labors from about an hour before the birth of the baby through an hour afterwards. In addition to these videotapes, I had access to a summary of the medical record and the transcript of an interview conducted with the women about four weeks postpartum. While the birth I will be analyzing was not atypical for births in that particular hospital, its typicality or lack thereof is not what matters for my analysis. Rather, I use this birth as a means to illustrate the complex interaction between the material resources of this particular workplace and the social relations that characterize it, in an attempt to point to the mechanisms by which, in high technology settings, authoritative knowledge comes to be distributed in particular ways. I do intend to claim that my argument holds for settings that are like this one in regard to hierarchically organized ownership of the salient technologies, be they labor rooms or not. What I am specifically not claiming is that births in American hospitals are always or typically conducted in this way. The point here is not to indict American birthing practices, but rather to show what happens when technology- dependent knowledge becomes hierarchically distributed. About nine minutes of the transcript of this labor are included as appendix A. Most examples that illustrate my analysis are drawn from this segment. The people present in the labor room with the woman are, initially, her husband and a nurse technician who has been taking care of her throughout the labor. The husband appears intimidated by the scene. He comes to the woman’s bedside when she calls him but gets out of the way when the medical team move in. The nurse is in a delicate position. She is the liaison (not to say interface) between the woman and the physician who will perform the delivery. As such she needs to assess the woman’s state within a small range of error in order to be able to call the physician in time for the crucial stages of the delivery that require his presence, but not so early as to waste his valuable time. Throughout the labor, she is very much preoccupied with the electronic fetal monitor (EFM), a machine that plots the strength of uterine contractions against the fetal heart beat. The EFM is widely believed to give early warning of intrauterine difficulties, even though it has never been shown that routine EFM treatment improves birth outcome (Leveno et al., 1986; Prentice & Lind, 1987). It is positioned at the bedside in such a way that the nurse can consult it in the same glance with which she looks at the patient. Since the woman’s medical chart has been placed on top of the fetal monitor, the activity of making periodic entries in the chart also involves turning to the machine.
The Story of This Birth The woman on the tape has gone to a large, inner-city hospital. She has been in labor for 10 hours. She is 25 years old and this is her second child. She is in bed, flat on her back, attached to an IV pole through an intravenous line that goes into her left hand; she is connected to the electronic fetal monitor through wires coming out of her vagina. The videotape is started about half an hour before the baby is born. In the preceding hours, Notes on the Achievement of Authoritative Knowledge 99 during the first stage of labor, the woman’s cervix has slowly opened up so that the baby’s head can pass through. She is now in the second stage of labor. During this stage, women experience increasingly powerful urges to push which become progressively more irresistible until the baby is finally expelled. In this particular case, however, the woman is not allowed to push. Every effort is made to keep her from giving in to the overpowering impulse to bear down. She is asked to suppress the urge long enough for the physician to come in and pronounce her ready. The physician is paged several times but does not appear. Meanwhile, the woman is doing Lamaze breathing, a learned type of breathing intended to help her last through the contractions without pushing. The pattern sounds something like “he he he hoo”¸ “he he he hoo.” The visible and audible breathing pattern women are taught provides a convenient standardized metric by which the degree to which they are in or out of control can be assessed by themselves and by their attendants. The nurse makes every attempt to help the woman remain within acceptable behavioral norms by breathing with her in the Lamaze pattern. As time goes on, the woman’s distress and pain become more and more pronounced. The nurse leaves for a short while to see about paging the doctor herself. A nursing student (who has been running the camera) takes her place until she returns. A woman medical student comes in. She and the nurse agree that the woman should be checked. The medical student performs a vaginal examination without asking permission or explaining what she is doing. The examination is inconclusive both in the sense that the medical student cannot feel what the state of the woman’s cervix is and in the sense that even if she knew, it wouldn’t matter because she cannot give the official permission to push. The physician finally arrives together with a male medical student. He examines the woman and declares that she is ready to push. The staff prepare her for the delivery. They put her feet in stirrups and swab her down with antiseptic solution. The husband is told to take his place at her head. The woman medical student puts on gloves to deliver the baby. The physician stands ready with a suctioning tube. As the head emerges, he suctions the baby’s nose and mouth. The child is delivered by the medical student who announces that it’s a boy. She immediately gives the baby to a pediatrician who dries, suctions and Apgar- scores him, out of the mother’s line of sight. The camera remains mostly on the baby being processed. Quick cuts to the mother show her in pain. Presumably the placenta is delivered. Finally, several minutes after the baby is born, he is given to his mother to hold. She touches his cheeks gingerly, with one finger. After a while mother and father slowly peel away the layers of clothing to take a peek at their baby. The mother begins to smile. Her face is transformed.
Access to Technology and the Hierarchical Distribution of Knowledge What is massively evident on the tape is that, throughout the labor, participants work hard to maintain the definition of the situation as one where the woman’s knowledge counts for nothing. They all know that she “cannot” push until the doctor gives the official go-ahead. Within this particular knowledge system, it is believed that only the doctor can tell when a woman is ready to push – information he gains from checking the dilatation of the cervix during a vaginal examination. This fiction is maintained collaboratively, by agency of the woman herself, her husband, the nurse, the medical student – in the face of the fact that anybody who cares to look or listen can see that this woman’s body is ready to push the baby out.3 However, what the woman knows and displays, by virtue of her bodily experience, has no status. Within the official scheme of things, she has nothing to say that matters in the actual management of her birth. Worse, her knowledge is nothing but a problem for her and the staff. What she knows emerges not as a contribution to the store of data relevant for making decisions, but rather as something to be cognitively suppressed and behaviorally managed. In the labor room authoritative knowledge is privileged,4 the prerogative of the physician without whose official certification of the woman’s state the birth cannot proceed. 100 B. Jordan
How is it, then, that the participants in the labor room display to each other and to themselves, that authoritative knowledge is held by the physician and that the woman’s knowledge does not count? If technology is seen not only as a collection of complex gadgets and machinery, but also as the methods and techniques developed in the communities of practice that use these technologies, then we see that technologies create particular kinds of social spaces within which certain activities are more or less possible and more or less likely. In the present context, I am particularly interested in the ways in which technologies are socially situated, that is to say, are given meaning in and through social interaction, are appreciated for their symbolic value as well as their use value, are owned and displayed by different segments of a community of practice, and are used to express power, expert status, and other socially meaningful relationships between people. Modern obstetric environments are full of technologies of different kinds, and women who have gone through prenatal medical care have become familiar with a great deal of it during their pregnancy. They know about screening and stress tests, ultrasound examinations, electronic fetal monitoring, and the like. They also know that just beyond the doors of the labor room is an operating room where C-sections can be performed. In spite of such exposure to obstetric technology, it appears that the woman (whom one might consider the central actor) is inert with respect to the technologies salient in the setting. None of them are ordered, operated, or interpreted by her. She apparently understands little about the role of the intravenous drip of oxytocin that has been increasing the strength of her contractions nor does she know how and why such an increase was ordered. Similarly, there is no evidence that she actively processes the output of the fetal monitor, in spite of the fact that it is right next to her bed and that there are times when it contradicts her experience. One might say that the artifacts and procedures which make up professional obstetric practice are arcane to her. She doesn’t look, she doesn’t touch. She is passively tethered to the IV pole on one side of her bed and to the fetal monitor on the other. The nurse, on the other hand, is very much involved with the machinery. It provides for her a level of reality which her unmediated observations, her direct experience of the woman’s state, do not. Throughout the labor, she looks to the EFM for information about the course of the contractions. We see her eyes glancing at the machine, often just when the woman is in greatest distress. In this setting, checking with the machine is not an occasional event but an ever present phenomenon.5 The Medical Staff as Gatekeepers. As a member of the medical team, the nurse is an expert reader, interpreter, and user of the information the EFM machine provides. The laboring woman is not, and no attempt is made to explicate the role of EFM information in decision making about the conduct of her labor. Other artifacts and procedures important for the conduct of birth are even less transparent and at the same time more restricted as to who can legitimately and consequentially employ them. For example, only the physician can do the vaginal examination on the basis of which the woman will be “allowed” to push the baby out. It is interesting that there are others in the room who are known to be competent to do that examination, such as a nurse standing off camera. But she says she doesn’t want to do it because the physician would have to repeat it anyway. The nurse knows that she doesn’t need to check because it doesn’t matter. In so far as her knowledge is not, cannot be, consequential in this setting at this time, it has no status. In other words, it is not so much the information that the woman is ready to push which is necessary here (that information, as we have seen, is amply available), but rather, this information has to be produced by the right person in order to become authoritative knowledge. Though everybody knows that the woman is ready to give birth, that information counts for nothing until it is legitimized by the physician. Within this system, only the physician can give the go-ahead. It is this gatekeeping function that is acknowledged by the participants when they agree that it would be futile to do a vaginal examination now. Notes on the Achievement of Authoritative Knowledge 101
One might ask, why are nurses allowed to perform dilatation checks at other times during labor? It appears that progress checking is one of the functions of the auxiliary staff which contributes to the proper staging of the main event. By reserving the certification to the physician, however, the system also assures that the birth does not proceed without him, which is, after all, an ever-present threat. The requirement that it be the physician who decides when the woman can push has a further consequence. The nurse notes the time of the pronouncement, and it is this time that officially determines the beginning of second stage. In this particular case, the baby is born six minutes later which makes the official duration of second stage, as noted in the medical record, six minutes. One can judge from all the behavioral signs that the second stage, in fact, began quite a bit earlier, at a time when the physician who is required for certification was simply not present. This artificial punctuation of the labor process produces prejudiced statistics which, by entering into computations of average length of second stage, become normative for the management of labor. Birth attendants practicing in home settings argue that hospital-based data are skewed in the direction of shortening the normal stages of labor. The Status of the Woman’s Knowledge. In this labor room, there coexist two versions of reality, two alternative claims to relevant knowledge. The woman presents hers verbally and bodily. She knows she has to push and says so clearly.6 She also expresses it in the visible, almost superhuman effort she marshals to suppress the urge to push. But every time she tries to get her desire, her expressed knowledge about the state of her body acknowledged and made the basis for proceeding with the birth, her version of reality is overridden, is ignored, is denied, or, most frequently, is side-tracked, deflected, and replaced with some other definition of reality. Something else is offered up as being more relevant, as might happen to an obstinate child whose parent opts for distraction rather than confrontation. This phenomenon is massively present as an inspection of any part of the transcript will reveal. A typical set of examples might look something like this: 7
Woman: I gotta push NOW → Nurse: you can pretty soon Woman: I can’t → Nurse: look at me Woman: I can’t → Nurse: all you can do is try Woman: HOO:::::H::::: → Nurse: its almost gone (pain sound) Woman: I can’t → Nurse: take a cleansing breath Woman: I can’t → Nurse: let’s just say you can Woman: I just wanna push → Nurse: I know … it’ll feel better for you to push, but in the meantime I don’t want you to. etc. etc.8
The woman is instructed to override what her body tells her and to act and feel otherwise. How is that “misrecognition” of her own interests accomplished? More specifically, how can a person be enlisted in the incredibly difficult enterprise of resisting such powerful bodily impulses? One strategy is to encourage her to do the patterned Lamaze breathing. When the woman cries out that she cannot control the pushing urge anymore, the nurse bends over her with direct eye contact and makes the official “he he he hoo” sounds, forcefully suggesting that that is the way to control the painful urge. The woman, in desperation, pours her wrenching bodily experience into the making of the permitted sounds, the officially sanctioned language of distress in this situation. As long as she produces the magic incantation “he he he hoo”, no matter how desperate – in so far as these are the officially sanctioned sounds and not an idiosyncratic outcry – she is seen by herself and those around her as “not out of control,” “collaborating,” “a good patient.” 9 And by holding on to those sounds and not giving in to uncontrolled breathing, writhing, and screaming, the woman expresses her desire to be a good patient while, in the modulating of the “he he 102 B. Jordan he hoo” through clenched teeth or with sobbing outbreath, she can nevertheless express her pain and misery without being censured for losing control.10 So it is the case here that the nurse and the other bystanders in the room (i.e. the woman’s husband, the medical student, the nursing student who operates the camera, and a second nurse who had been paging the doctor) understand clearly that this woman is ready to push. Yet this knowledge counts for naught. It has no status and no consequences. The woman is spoken to consolingly, encouragingly, soothingly, or firmly, as her behavior requires, often in a kind of singsong voice that is close to the inflection familiar from kindergarten and grade school teachers. The attendants’ pseudo-intimate voice emphasizes the childlike status of the woman. The staff are nice to her because she cannot help it if she lapses into unapproved behavior. As with small children, they may even have to physically restrain her on occasion, but they do it for her benefit. Another way of controlling the woman’s behavior is by straightforwardly giving orders:11
Hus: you want some ice? woman pats her face rhythmically with washcloth, indicates “no” 21.1712 Wom: I just wanna push
21.19 Nur: I know it won’t be long it’ll feel speaks to woman without looking better for you to push at her while writing in chart but in the meantime I don’t want leans towards woman and you to whispers – okay? emphatic
As things become more difficult, the nurse uses a large number of unmitigated imperatives, such as: “look at me;” “come on;” “breathe with your mouth;” “take a cleansing breath;” “take a deep sigh;” etc. The nurse also indicates correct behavior with such praise as “good,” “perfect,” etc., a clear indication of who in this situation holds the knowledge that counts. These evaluations are similar to those used by teachers in schools and reinforce the woman’s childlike position. Information derived from the machine serves as a resource and a justification for negating and redefining the woman’s experience. For example, at 20.10 the nurse, consulting the monitor, tells the woman what she should be feeling:
[the contraction] is at the peak ... it’s going down ... it’s a smaller contraction ... almost gone ...
The nurse’s characterization contradicts the rising, not decreasing, pain visible in the woman. So we have in this scene simultaneous but conflicting claims about what the woman’s body is up to. The nurse’s knowledge is machine based; she can see the contraction fading away. But the woman is falling apart because her experience is quite otherwise. What we get here is a negation of what the woman’s body tells her by what the machine tells the nurse. Staging the Physician’s Performance. The physician’s unquestioned status and authority rest, in the last analysis, on a societal contract which accords him that authority. What I am interested in here is how, for participants in this delivery (the woman, her husband, and the medical staff) this authority is not only displayed but in its implementation is interactionally achieved. It becomes visible in the ritual deference paid to the superior status of medical knowledge. It is also displayed in the way activities in the labor room are orchestrated, unfolding in the manner of a dramatic theatrical metaphor. As the labor progresses, there is a palpable buildup of tension, though not, as one might expect, foreshadowing the moment the woman gives birth, but rather leading up to the entrance of the physician without whom the delivery literally cannot proceed. His entry is eagerly awaited. He is paged, with increasing urgency, at least four times in the 12 Notes on the Achievement of Authoritative Knowledge 103 minutes before he finally appears. Then he sweeps in with his entourage, a male medical student holding his white coat. Without a glance at the woman he walks over to the fetal monitor, cursorily checks the output and then confers briefly with the nurse and the male medical student. The team take their position as if on a stage or in the battlefield, around the lower end of the woman’s body, essentially dividing her into two parts: the “interaction end” at her head, to which the husband is delegated, and the “business end,” where the important work of getting the baby delivered takes place.13 The physician performs the long-awaited examination standing up, looking away over the woman, with the nurse gazing up at him. This is an achieved arrangement. One can do a vaginal examination standing up or one can get down to the woman’s level as midwives are wont to do, looking at her, talking to her as they do the exam. This doctor’s attitude and stance, and the framing that is done by the team, are meaningfully produced; it is not that the world is that way “naturally.” Nor is this kind of framing of the physician restricted to this labor room or labor rooms in general. It is common in medical interactions that have staff of various ranks present (as, for example, attending physicians, nurses, residents, and medical students during walking rounds). Kirkham, observing labors in hierarchical hospital settings, notes the staff “waiting on” the doctors in what she calls a pattern of “dancing attendance.” She also notes that such actions inevitably reinforce the situation which led to them (Kirkham, 1988).14 The team frame him not only physically but also shadow him verbally. They explain, highlight and interpret his actions to the woman with whom he does not communicate directly. The medical student explains: “He is checking to see if you can push, okay?” (27.58). The team takes up what the physician says, repeating his words, translating them, pointing out their significance:
28.10 Doc: Yeah to nurse she can push Nur: can she? plus one? looking up at doctor getting ready to write Doc: yeah plus two nurse writes in chart Wom: Oh: NO:::: in pain 28.15 Nur: you can push to woman, with relief, like a good news it’ll feel good announcement
The repetition of the physician’s words by the staff highlights, like a theater chorus, what is to be considered important. The physician’s professionalism, on the other hand, is expressed in his totally impersonal attitude towards the woman. He treats her as an object, a performance that is made possible by the fact that others isolate and shield him. He never has to deal with this woman as a person. The only time he addresses her before the birth Is when he says “let me check you before you get another contraction” (27.49). The woman, in that she makes no interactional demands on him, collaborates in this construction.
Participation Structures in the Labor Room. Students of interaction, from Goffman (1963, 1981) to Goodwin and Goodwin (1996), Heath (1986), Jordan and Henderson (1995), Kendon (1985, 1990), Sacks (1992), Suchman (1987) and others, have noted that important social “work” is done through participation frameworks – fluid structures of mutual engagement and disengagement characterized by bodily alignment (usually face-to- face), patterned eye-contact, situation-appropriate tone of voice, and other resources the situation may afford. What is striking in the labor room is that the laboring woman, who might be seen as the 104 B. Jordan focal participant, has only limited access to the various participation structures we observe. She is primarily engaged in dyadic interaction with the nurse, or, occasionally, with her husband. But these sometimes intense interactions are always in the service of the business at hand: dedicated to maintaining the current definition of reality by preventing her from letting her bodily experience gain ascendance. These dyadic interactions appear to be the only legitimate type of interaction for her. She does not enter into other kinds of participation frames. As soon as other people enter the room, such as the woman medical student or later on the physician with his entourage, the laboring woman is virtually excluded from any sort of engagement in talk or activity. Neither the physician nor the students introduce themselves to her. The physician never looks at her, doesn’t address her until he stands ready to perform the vaginal examination, and then he simply announces what he is going to do – a type of statement to which the most appropriate response is silent compliance. The nurse is involved in a number of different participation frameworks, shifts which are indicated by changes in body posture (e.g. straightening up, turning away from the woman and towards the door) and, maybe most significantly, by voice quality. There is a reciprocated, bantering tone in her interaction with the medical student, an enthusiastic, dramatic inflection when she asks the physician: “can she [push]?” even as she speaks to the woman in a multi-modulated parental voice. In this setting, social interaction, beyond that required to maintain control, is done without the woman. Business gets done with her as an object but not as an actor. At the height of the drama when she is in great pain and barely able to control the pushing urge, the nurse and the medical student have a little chat, engage in a little private chuckle (26.35). The woman’s head comes up from her pillow as if trying to see, as if trying to make a bid for inclusion or at least for acknowledgment of her plight, but to no avail. Her physical position is such that even eye contact is not easily initiated and, at any rate, there is no opening for her in the participation structure that is already set up. Once the doctor enters, the staff interact as a team of which the physician is the focal member and from which the woman is specifically excluded. No input is solicited from her; talk is not produced for her overhearing or participation. No explanations are given. They do the business of examining her and preparing for the delivery amongst themselves. The woman is the object to be prepared and to be delivered. The result of this systematic objectification of the woman is that there are two different enterprises going on in the room. The woman is desperately struggling against the sensations of her body, cajoled and parented by the nurse who, in turn, has one eye on the medical team. The second, quite separate enterprise is to deliver the baby which is the business of the staff. For all practical purposes, the woman has nothing to do with that nor has she anything to say about it. She is not giving birth, she is delivered. When the doctor finally announces that she can push, the announcement is directed to the medical team and not to the woman. The doctor says: “she can push,” and the nurse relays the message: “he says you can push,” as if doctor and woman were not in the same room. The woman has become an object to be reported on, rather than an actor to be engaged. In the ways in which participation structures are set up in the labor room, her exclusion is ratified, executed and displayed over and over again. This is one of the mechanisms by which she is denied any say in the conduct of her labor, by which she is given the message that she doesn’t count. The formal and informal professional participation frameworks of the labor room specifically exclude her. We have seen, then, that in the labor room several different kinds of knowledge are actually present, but the only kind that counts is the knowledge delivered by the physician. This knowledge is communicated downward along a hierarchical structure of which the woman is the most distal member. All major decisions are reserved to the physician who is in charge of “the facts,” the knowledge on which rational decision- making is to be based. Notes on the Achievement of Authoritative Knowledge 105
In the following discussion I consider another kind of situation, one in which there is also a great deal of reliance on complex technology, but where access to that technology and competence in technology-based procedures is shared. As a consequence, authoritative knowledge is horizontally distributed. Unlike the labor room, analysis here does not reveal a competing version of reality, a conflicting “non-authoritative” way of knowing. Rather, as far as we can see, there is only one kind of authoritative knowledge present in this situation.
The Airlines Operations Room
The Setting My second set of data comes from another technology-rich environment, the operations room of a major airline in a metropolitan airport in the western United States. “Operations” or “ops” is the communications and control center which organizes an airline’s ground operations. It is the locus for the coordination of all activities having to do with the arrival and departure of planes, such as the movement of passengers and baggage, fueling of planes, provisioning with meals, cleaning and servicing of planes between flights, and the like. Our evolving understanding of the work of ops has been informed by ethnographic fieldwork carried out by members of an interdisciplinary research team. In addition to video tapes filmed over several months, the data corpus includes field notes on many hours of participant observation, interviews with key informants, and the analysis of work- related documents. The present analysis focuses particularly on four hours of videotape filmed on a weekday afternoon and evening in order to document routine activities in one of the ops rooms we studied. Appendix B includes a transcript of 4 ½ minutes from that tape. As much as possible, examples for the discussion which follows will be taken from that brief segment. Our fieldsite is a hub for Atlantic Airlines.15 At certain times of the day a flock of planes from all corners of the country descend from the air, roll into Atlantic’s eight gates, exchange passengers, baggage, and crews, are serviced with fuel and food, and go out again to different destinations. One can think of the ops room together with its associated work areas (the ramp, the gate, the baggage area, etc.) as a pulsing organism which periodically sucks in planes, people and objects, takes a deep breath, and then expels them again – hopefully on schedule. At the height of such “complexes,” when all of the airline’s gates are busy, the activity level in the ops room is at a pitch, only to relax again as the complex fades away. There are nine such complexes in the course of a working day. The ops room is a multi-party, multi-task work environment, characterized by a mix of communication technologies arranged along the walls, with operators seated to face them. Thus the normal working arrangement is not face-to-face but back-to-back communication among co-workers (see figure 1).16 Information about the state of the world comes into the windowless room through audio, video, and paper documents, over radios, phones, computer screens, printers, video monitors and, every so often, from another employee wandering in from the ramp or the gate. This information is taken in, processed, and then sent out again in the form of data and directives tailored to the needs and activities of other parts of the system, such as pilots, fuelers, baggage loaders, maintenance workers, and so on. Some of the information the ops room processes comes from headquarters in a distant city, e.g. instructions about how much fuel to put into an airplane, where to load the baggage, etc. Other information comes from planes and pilots, either by voice over the radio or through a computer system installed in most planes. Thus ops workers communicate not only about technical operational matters such as a problem with a fuel gauge or a plane’s ETA17, but also about such mundane issues as a new seat cover needed on an incoming plane because a passenger threw up, or the location of a forgetful pilot’s
106 B. Jordan
Figure 1. Technology and positions in the ops room. keys. In addition to cockpit crews and headquarters, ops workers are also in frequent radio communication with gate agents and with the ramp area where the ground crew stands ready to push the exit stairs up to the plane, take care of baggage transfers, etc. (see figure 2). Ops workers have visual access to the remote gate area through a bank of eight video monitors mounted high up on the back wall of the ops room. These show the situation at each gate via a camera facing the incoming airplane. The camera controls are located above one of the workstations, so that operators can zoom in on a particular plane or pan from one side to the other. This bank of monitors is frequently consulted since it is one major source of information about the state of the real world (as compared to the ideal world of schedules). In addition to processing information directed specifically at the ops room, there are also information streams aimed elsewhere in the system which the ops room monitors: the two printers are constantly spewing out printed messages that must be scanned for relevance and either discarded, filed, communicated, or otherwise processed. In the auditory sphere, open channels for Tower and Ground Control provide a stream of announcements about planes approaching, landing, on the ground, taxiing, and so on. This somewhat facile description of information processing in the ops room glosses over the fact that “information” does not “come in” in any simple sense, nor is it processed and sent out again as if it were a substance to which an ingredient or two have been added. Rather, in observing activities in the ops room, we witness the moment-by-moment construction of locally meaningful and consequential information out of the special resources this environment provides. For example, we recognize as a collaborative achievement and an artful practice the process by which workers pick a particular set of noises out of the dense “sonic soup” of incoming messages or recognize a particular set of symbols on the screen – but not another set – as relevant to certain ongoing or projected actions.18 Here, what a given message could mean is a function of what needs to be done with it, of the Notes on the Achievement of Authoritative Knowledge 107
Figure 2. An ops-centered view of the world. ways in which this information enters into the routine activity sequences that make up the work day. What counts as relevant information, then, is worked out on the spot, in the course of doing the work, and is different at different times and for different ops room workers. In this particular ops room there are four operators and a supervisor (SUP), each of whom has specific responsibilities. For present purposes it suffices to note that the Passenger Service Planner (PSP) communicates with gate agents and ensures that passengers whose planes have been delayed or canceled are rebooked. Operations-A (OPS-A) talks to jet pilots, either by radio or through an onboard computer, while Operations-B (OPS-B) talks to the pilots of Atlantic Hawks, the airline’s small commuter planes. The Baggage Planner (BP) communicates with ramp personnel who are in charge of servicing the airplane and moving baggage. On the day in question, a “routine anomaly” occurred: a series of planes had to be switched around in order to divert one particular plane to a repair facility. Such unscheduled plane swaps are not uncommon, yet are not part of the normal daily working routine. Routine anomalies stand in contrast to major, unforeseen, one-of-a-kind problems that require crisis level measures. Routine troubles may occur with or without advance warning.19 In this particular case there was ample advance notice, so the problem could be handled, to a large extent, prospectively. Yet, while the desired outcome and, in some ways, the general procedure for achieving that outcome, were clear to everyone involved, the details for handling the contingencies emerging in this particular case had to be worked out as the day progressed. The very working out of such problems contributes to the further domestication of trouble in that it adds to the repertoire of resources available to the team on a next occasion.20 Much of the videotaped record is concerned with the orchestration of deviations from the usual routine which became necessary because of the switch. The hours preceding the event were shaped by a joint effort in the ops room to come to a shared understanding about what needed to happen and to communicate that 108 B. Jordan understanding to other personnel who would be carrying out the switch itself as well as instituting various remedial procedures necessary to deal with the ensuing fall-out. The transcript provided in appendix B deals only with a small fraction of those. It is not particularly important that the reader understand the technical details of the switch. As a matter of fact, most any other stretch of this tape would have served just as well to make the points I am going to make. The narrative account which follows is provided, in conjunction with the transcript in appendix B, in the hope of giving the reader some access to the data on which my analysis is based.
The Story of the Three-Way Airplane Switch On this particular day, aircraft #677, coming in from SEA as flight 1018 and scheduled to go out to SNA under the same number, developed a problem with one of its fuel tanks.21 Since the facility specializing in the appropriate repair is located in Los Angeles, a decision was made by headquarters to reroute #677 to Los Angeles by assigning it to flight 1091 which had a Los Angeles destination.22 The original flight 1091 aircraft, #656, was to take out flight 909 to SEA because the aircraft of 909, #676, which had come in during an earlier complex, would be needed to take out 1018 to SNA, the flight which the damaged airplane could not complete (see figure 3).23
Figure 3. The three-way airplane switch. Notes on the Achievement of Authoritative Knowledge 109
So during complex 7, aircraft #676 which comes in as flight 909 does not go out. Rather, passengers and baggage are held till complex 8 when their flight goes out on aircraft 656. Their original plane, aircraft #676, is towed during the slack period between complexes from gate 18 where it arrived during complex 7, to gate 14, from which it will leave during complex 8. The transcript excerpt in appendix B refers to this period between complexes 7 and 8. As the transcript shows, other flights are affected by these maneuvers. For example, gate 15 needs to be freed for incoming flight 1018 which has just radioed that it will arrive early on this particular day. An extra set of rear stairs has been provided to speed up passenger boarding for outgoing flight 475 but it turns out that these extra stairs can’t be used because the Marriott provisioning truck is in the way. Another set of issues revolves around flight 225 which, during the time represented on the transcript, is still in the air but scheduled to arrive at gate 19, with an expected departure time of 19:26. Gate 19, however, at that time will be occupied by aircraft #656 which will take out the delayed flight 909 from complex 7 at 19:40. The crew of flight 225 has to be notified of the fact that they will have a lengthy wait on the tarmac until they can pull into the gate. In addition, there are other flights arriving and departing which are not directly affected by the 3-way switch but whose demands need to be satisfied as well. For example, at 7:06:29, the supervisor announces the departure of flight 1147 from the gate. A few minutes later, at 7:08:48, OPS-A reads “the numbers” to flight 1147 which is by now taxiing to the runway, waiting to take off.
Access to Technology and the Horizontal Distribution of Knowledge In contrast to the labor room where there is a division of interest between those who deliver a service (the medical team) and the recipient or object of that service (the woman), in the ops room there is no such distinction. All participants have a similar orientation to the work that is to be accomplished. Here, in contrast to the labor room, access to information-producing artifacts and procedures is not privileged. There is no single technology relevant to the business at hand that is restricted to a particular person or to the occupant of a particular position within the team. We observe all of them, supervisor and operators alike, manipulating the camera controls, talking on radios and phones, looking at computer screens and printouts. While not all of them use all of the technologies with equal frequency and competence (for example, the supervisor is a slow typist), no technology is reserved to one person. This uniform access to the salient artifacts in this workspace constitutes and displays a shared distribution of responsibility and accountability, in fact a joint constitution and constant re-constitution of shared ownership of the work. In the following sections I draw attention to the ways in which the characteristics of the various communication technologies and the organization of the social interaction within the physical workspace provide for the horizontal distribution of authoritative knowledge within a collaborating team. Joint Production of Shared Information. The ops room is a place where information about the current state of the world collects. The “world” at issue is the world of planes in the air, on the ground, and at the gates and their state of readiness in regard to passengers, baggage, fuel, food, and crews. The work of ops consists in comparing this de facto state to an ideal state as reflected in schedules, and then initiating adjustments of various kinds which bring the current state more or less in line with the ideal state.24 The ideal state appears in ops documents as SKED, i.e. scheduled time of arrival or departure, the standard against which performance is measured. Approximations to the ideal state are achieved through coordinated efforts between participants in ops-internal operations and between ops and the associated locales which their directives affect. Though each operator has his or her particular set of tasks and responsibilities to carry out, most of the information coming into the ops room is relevant not to one particular operator but to several or all of them. In like manner, what information goes out and in 110 B. Jordan what form it goes out is of shared concern. For example, the delay of one plane commonly pulls in its wake disturbances in the departure of others, and it is extremely important that emergent information of this sort be available to everybody in the room as it develops since each of them may be called upon to use that information for updating other parts of the system. By contrast, the woman in the labor room is not a recipient of information about her state as it becomes available through technologies and procedures. The nurse takes her blood pressure without communicating the results; she consults the fetal- monitor without telling her what she sees; when the medical student does a vaginal examination, she tells the nurse in medical jargon what she finds, but not the woman. The staff act as if the only piece of information that could be at all relevant to the woman is whether she can or cannot push. Beyond that, the only information she gets are vague projections like: it’ll be soon. As part of their working routines, ops workers are constantly oriented to determining the “picture,” i.e. assimilating and in turn making available to co-workers, information about the current state of the world. As a matter of fact, one might think of them not so much as occupied with the enterprise of gathering information for doing their own individual jobs but rather as engaged in updating the group’s collective take. The process of forming and updating their picture of what is going on in the material world of planes, crews, and passengers requires the integration of multiple streams of representations in symbolic, auditory, and iconographic modes into a coherent and in some sense efficacious picture of the relevant material world. This integration is a strikingly interactional achievement and appears to lie at the very heart of successful coordination and control operations in high- tech environments (Heath & Luff, 1991; Zuboff, 1988). It is no surprise, then, to find the layout and social relations of the ops room organized for the social production and utilization of information. The internally barrierless physical setting and the characteristics of the communications technologies employed are such that much of the incoming and outgoing information is for multiparty listening and shared viewing. Because of the physical arrangement of the work setting, ops room workers are a party to both sides of their co-workers’ radio communications; they overhear their phone calls as well as radio information from the Tower and from Ground Control. Furthermore the bank of monitors on the back wall of the room provides a common, public display space where a visual representation of the state of the world at the gates is publicly and simultaneously available to all. The work environment is thus alive with symbolic, visual, and auditory activity which is screened and variously appropriated by workers for their own or co-workers’ requirements. In this regard unrestricted access to the various communication technologies is crucial. At the same time, individual work stations make it possible for operators to follow their own paths of activity for stretches at a time. The often unconscious details of work practices which have arisen in this environment come to support the joint production and use of information. For example, a common feature of communication in the ops room is an initially curious habit of ops room workers to make statements and requests which are, so to speak, launched into the room, offered To Whom It May Concern, rather than being addressed to anyone in particular. Such “outlouds” often generate no immediately visible or audible reaction. This stands in contrast to what we expect in multiparty conversations where speakers, even when they have not specifically addressed another person, count on a response from somebody in the group. If no response is forthcoming, this constitutes an awkward or otherwise implicative “noticeable absence.” Under the working conditions of the ops room, on the other hand, certain verbal statements produce no verbal response and this seems to present no problem. In particular, we see no remedial action occurring, such as repetition, apology, and the like. On closer observation, these outlouds do have consequences. On occasion, somebody in the room self-selects to provide a direct verbal response to the speaker, though often with a considerable time delay. On other occasions, no response is forthcoming for the original speaker, but rather the topic is taken up and verbally relayed, usually in modified form, to Notes on the Achievement of Authoritative Knowledge 111 some party outside the ops room. On still other occasions, no verbal response is forthcoming, but some other kind of action takes place which can be seen as responsive to the original statement. For example, at 7:05:02 25 the Passenger Service Planner (PSP) says, more or less into the room:
7:05.02 PSP: That’s the last of the people there. turns to speak into room He said catering was originally in [re flight 475 at gate 15] the way back there, so …
Nobody reacts verbally, but the supervisor goes and manipulates the camera controls, presumably to see for himself if the boarding process is complete. In spite of the lack of overt verbal reaction to the announcement, it is important to realize that the PSP has just provided a critical piece of information relevant to everybody in the room. He was talking about flight 475, a flight that needed to be processed as quickly as possible in order to make room for incoming flight 1018 at gate 15 (see figure 3). Ops had ordered an extra set of rear stairs to expedite passenger boarding, but somehow these had not been used. Apparently the food service truck had been in the way. What PSP is saying now is that there is no further problem and flight 475 can depart immediately. It is not uncommon that a statement just floats in the room, without visible reaction. Yet there is ample evidence that the originators of such outlouds monitor their fate. In the example below, the PSP’s announcement that all passengers have been boarded on flight 475 does not get taken up by the Baggage Planner. PSP follows up with a verbal and physical escalation, showing that he expected BP to do something in return. (For clarity, the excerpt below contains only the exchange between PSP and BP. The full transcript can be found in appendix B.)
7:05.02 PSP: That’s the last of the people there. turns to speak into room He said catering was originally in [re flight 475 at gate 15] the way back there, so … you might wanna tell the ramp-uh [re flight 475] they can go in and probably plan steps over to BP, who is listening to to pull those stairs up (while xxxx) the radio with headphones and does not react; goes back to his station, looks up at monitors again. 7:05.21 BP: Okay, yeah, they’ll, they’ll be told still talking on radio to crew chief to hold out there at that gate at gate 15 7:05.26 BP: Sorry, Dave, what (was that)? swivels on chair towards PSP, now acknowledging his earlier request PSP: We didn’t end up using the rear turning to BP stairs. BP: Oh. PSP: I guess Marriott’s was in the way earlier so-uh and that’s the last of the people; we can go ahead and put those rear stairs up. 7:05.33 BP: On fifteen? [re 475] PSP: Fifteen. yes (x)=
At 7:05.11, PSP follows up his earlier statement which was directed into the room, when he realized that BP had not shown the appropriate reaction. He takes a step in her direction, physically putting himself into her transactional segment (Kendon, 1990) to draw her attention. BP, in fact, does come around after finishing her radio conversation to get the relevant update on the state of the world. 112 B. Jordan
We also find not uncommonly that along with announcements, requests for information are addressed to the room. Sometimes a respondent self-selects to provide an answer. For example, at 6:11.40 (not on this transcript), the PSP says: “Is that two-eleven I see out there at the gate?” In response, the Supervisor goes and manipulates the camera controls, then responds. What addressing such requests to the room does is to signal that some part of the group is not in on “the picture.” A response then might consist of a verbal update or a physical action that produces the required information. So we begin to see that in the environment of the operations room, outlouds that have no specified addressee are common and consequential. In generating appropriate actions by one or several respondents, broadcast statements and questions that elsewhere might be taken as random babble or mutterings, can be seen to fulfill important and specifiable functions. Heath and Luff (1996) found a similar phenomenon in a London Underground Control Room. This is initially all the more curious as there are only two operators. They mention that the Controller frequently engages in what they call “self-talk,” a technique that allows him to undertake quite complex changes to the timetable while simultaneously passing information to his colleague who is in charge of updating passengers over the public address system. They note that these outlouds not only provide the necessary technical details to the second operator but also the reasoning used by the Controller in making the particular changes. Other investigators have also found this curious habit in place in work environments where there is a premium on the joint co-construction of the state of the world. I would suggest, then, that requests which are addressed to the room work because knowledge here is socially distributed. That is, it is embodied in the system as a whole. Requests are produced for the room not so much because workers don’t know where the information they need is located and therefore don’t know whom to ask, but rather, asking a question as an outloud acknowledges that anybody could hold the answer, given the distributed access to the information-producing technologies and social networks. The answers to questions addressed to the room are produced by co-workers as they become less occupied and able to pay attention Given the non-hierarchical distribution of informational resources in the ops room, wide ranges of questions can potentially be answered by anybody. Under such circumstances, the selection of the entire group as a recipient ensures that the individual in the best position to respond can self-select, either verbally or with some appropriate nonverbal action. It is thus an extremely efficient, context-sensitive device for accomplishing the continuous updating that the system requires for efficient operation. What we have here, then, is an allocation mechanism that, rather than following a hierarchical distribution of authoritative knowledge, allows the accessing of that knowledge in the most efficient possible way. While the absence of the physician and his authoritative knowledge can bring the ongoing work of the labor room to collapse, the fact that the supervisor might not be there is, for the routine work of the ops room, not a problem. Common access to the salient technologies ensures that, in spite of specialization within a division of labor, any one of the agents is a potential source of information. Interestingly, it is not only verbal information that is produced “for the room.” This is also the case with visual information. We observed operators manipulating the camera controls to display information that is as much or more in the service of a co-worker’s needs as their own. In contrast to other communication technologies (on individual video screens or at the other end of a telephone call), verbal outlouds and visual displays are located in a public space, a space that in this environment is actively exploited for the joint updating of the state of the world. While the hierarchical distribution of authoritative knowledge characteristic of the labor room allows for only one person, or class of persons, to hold the relevant information, the arrangement in the ops room maximizes the potential number of agents available. It also minimizes the chance that the information requested will interrupt other ongoing business since it is provided by an agent who self-selects to respond to the query, Notes on the Achievement of Authoritative Knowledge 113 presumably on the basis of an in situ judgment of a not-intolerable work load of his or her own. One could speculate, then, that outlouds constitute a low-technology method of first choice in complex situations of this sort where cognition is socially distributed and knowledge acquisition is a palpably social process. Joint Error Detection and Joint Problem Solving. A consequence of the shared access to the relevant technologies and the public production of information in the ops room is that participants are constantly engaged in monitoring each other’s information needs. They ask each other for help, they offer assistance, and they provide their colleagues with unsolicited pieces of information they have picked up and consider useful.26 In the following interchange (not on the transcript). OPS-B requests information from PSP, who is just then manipulating the camera. PSP immediately complies and scans for the needed information:
07:01.59 OPS-B: How many-uh, David, how many PSP is standing, manipulating Hawks are out there? camera controls; OPS-B is sitting at his station. Both are looking up at bank of video monitors. 07:02.06 PSP: Looks like one’s taxiing out Still looking up at monitors; supervisor enters 07:02.10 PSP: still four ... eyes still on monitors OPS-B: one’s here (xxx) looks behind supervisor to see the monitors 07:02.25 PSP: looks like two ... three ... four? at continues to inform OPS-B who least four there, Randy, and is writing one’s taxiing out, so uh-five there. There’s five there.
About thirty seconds later PSP corrects his response and informs OPS-B:
07:02.54 PSP: Actually there’s six there now, Randy.
In an earlier example, at 7:05.11, we observed PSP suggesting to the BP that she might want to tell the ramp to pull the stairs. Here help was not requested by the BP, yet PSP provided the information on his own initiative, judging it to be important. An inspection of the transcripts reveals that information and other kinds of help are volunteered on numerous occasions in this environment By contrast, in the labor room available skills of idle coparticipants cannot be used to move the birth ahead. In spite of the fact that there is a nurse present who could do the required examination, the examination is not done because what she might find out is irrelevant to the work to be accomplished. Constantly engaged in monitoring the state of the world, ops room workers may well notice problems in a co-worker’s sphere and be able to initiate a corrective. In the following excerpt from the transcript, OPS-A, talking to flight 1091, gives the crew false information about where they need to go when they come in. The supervisor, who has been wandering around the room, without saying a word draws OPS-A’s attention to the mistake which OPS-A then promptly corrects:
7:05.13 OPS-A: Okay. You’ll be looking for [to pilot of flight 1091] aircraft six-seven-six which is [false information] here and it’s-uh being pulled into gate fourteen right now, so turns head, looks up to check the airplane will be here when info on video monitor you get here. 114 B. Jordan
7:05.25 SUP: swivels on heels, walks back to OPS-A, taps him on shoulder (or points to schedule?) OPS-A: Roger? 7:05.29 OPS-A: I’m sorry, disregard. Six-seven- [to pilot of flight 1091] seven. Fifteen. [corrects mistake]
It is also interesting that the joint, collaborative way in which people share information and go about handling problems in this setting affects the conversational tone that characterizes talk in the room. People typically use mitigated forms of talk. For example, when PSP informs the BP about needing to pull the stairs this is done in a rather polite, non-directive manner:
You might wanna tell the ramp uh they can go in and probably plan to pull those stairs up.
There are few direct imperatives; rather we find requests, suggestions and undemanding recommendations for action. This style is shared, to a very large extent, by the supervisor as well who, except in highly charged situations, does not tend to give straight directives either. A typical example for supervisor-worker interaction occurs at 7:03.35 when he makes a request of the form: “Dave, you wanna see if you can find out ...” In general, there appears to be a prevailing ethos in the ops room which encourages all participants, regardless of rank, to contribute whatever knowledge and expertise they might have to solving the problems the room faces. Given that ops, against the background of its daily and complex-specific routines; nevertheless perpetually has to deal with new and novel problems, nobody’s contributions are excluded by virtue of their status in a hierarchy. Openness to multivocality is part of an ethos that values collaboration beyond individual prominence. It is supported by equal access to and use of the work- relevant technologies and is displayed in the joint ownership of the resultant authoritative knowledge. Mutual Delegation and Assumption of Tasks. Participants in the ops room are not only attuned to each other’s information needs, they also actively assume a co-worker’s task when that person is otherwise occupied. This is facilitated by what one might call “naturally occurring multi-skilling,” distributed expertise in handling the crucial technologies. There are multiple occasions when one operator is temporarily away from his or her work station and another simply slides over to pick up an incoming call, make a required entry, or answer a question. In contrast to the labor room, where division of labor is strictly enforced to the point that even persons competent in a task do not carry it out if they don’t have the appropriate job classification, mutual assumption of tasks here is accepted and expected. It is one of the ways in which impasses and bottle necks are largely avoided. The supervisor seems to incorporate assumption of other’s tasks as an integral part of his role in the ops room. For example, at 6:04.10, in a sequence occurring about an hour before the transcript segment (see appendix B), PSP is busy on the phone negotiating the airplane switch, making sure that all parties know what to expect. The supervisor, without saying a word, sits down at PSP’s workstation and types, probably making an entry in the computer to update the data base that people might consult. At 6:08.31, PSP terminates his phone call and makes an announcement to the room regarding the switch: “Unfortunately tonight, all three of these flights have through-people that have to get off.” Then he turns to the supervisor, thanks him in a soft voice for his assistance, and goes on with the business of alerting co-workers to the impending switch. At 7:09.10, OPS-B, who has been staring at the video monitor, announces, also into the room, that “475 has pulled the stairs.” This is an important piece of information which updates the room about the state of that plane as well as the state of gate 15, which is now Notes on the Achievement of Authoritative Knowledge 115 ready for incoming flight 1018. We see that the announcement is consequential; PSP acknowledges it with: “kay”, while the BP picks up the radio control from her lap and says into the radio: “475 locked up (and away),” alerting the ramp crew. It is interesting that this crucial piece of information is supplied by OPS-B, the one person who has no direct interest in it since his job consists of dealing with the Hawks, the small commuter planes. Over and over again in the course of a shift do we see such instances of cooperative work, such contributions to “the picture.” We find an orientation to joint ownership of the work and a shared accountability which transcends responsibility for individual tasks and thereby contributes to the collaborative construction of what counts as authoritative knowledge in the ops room. Participation Structures in Ops. Considering how work is accomplished in the ops room, it comes as no surprise that participation structures are fluid and often overlapping. As contingencies arise and are taken up for notice or action by co-workers, new alignments are constantly created and recreated. Thus we find multiple participation structures that are generated, maintained, and disassembled in response to the requirements of the business at hand. An interesting feature of activities in the ops room is that there is much interaction that, beyond physically co-present co-workers, involves other parts of the organization in more or less distant places. As we have seen, the work of ops as a communication and control center prominently consists of collecting incoming information, restructuring it in some way, and passing it on again to appropriate recipients. As a consequence, much ops work is necessarily and unavoidably linked to work spaces outside the ops room itself. A look at figure 2 makes clear the multiple, technology-supported linkages to the outside world. The various communication technologies afford a rich variety of social relations and social interactions with a diverse assortment of people, some of them known in person, others familiar as, for example, a voice on the radio. Ops workers, in fact, spend most of their time maintaining extended linkages and exchanges with remote co-workers, only to turn back to interaction with co-workers in the ops room as they conclude an externally oriented exchange. Especially during high workload periods, the default activity for ops workers is preoccupation with and orientation to the outside through their work station. This primary involvement provides the background against which interactions with physically co-present colleagues are produced. The “time-out” character of in-room interactions becomes visible in the many instances where participants in cross-room communication assume “torque positions” – turning head and torso towards another participant while indicating, in that they do not swivel around all the way to face the other worker, that they imminently intend to go back to their prior activity (Kendon, 1990; Schegloff, 1998). So interaction with co-workers in the ops room is often displayed as an interlude in the ongoing work with externally located co- participants. In that regard, the ops room (and work situations that are structured in similar ways) provide an opportunity to extend the notion of participation frameworks – originally developed to describe face-to-face interaction – to situations where significant exchanges routinely and necessarily take place with persons in technologically connected remote work spaces. In contrast to the situation in the labor room where the conversation between the medical staff specifically does not allow easy entry for the woman, there is no principled exclusion of individuals in the ops room. All co-workers participate fairly equally – that is, without structurally provided restriction – not only in the flow of communication directly related to work but also in the informal kinds of exchanges that appear in the interstices between tasks or when things slow down between complexes. Stories and jokes appear to involve all those present – as tellers, recipients, and commentators – without exclusion. As in the example below, evaluations of ongoing activities and of problems solved are typically expressed in terms of the work accomplished by the team, rather than as praise or blame directed towards an individual. 116 B. Jordan
7:08.29 PSP: That sure worked out good to get glances up at monitor, then turns that airplane moved, didn’t it? to OPS-A [re ... 676] 7:08.32 OPS-A: Huh? PSP: that plane got over there without again looking at monitor getting in anybody’s way? OPS-A: Yeah. 7:08.35 PSP: ‘ts great. 7:08.37 OPS-A: We got lucky that one-eighty- [184 was at gate 16] four took a small mechanical [re 676] (snicker)
In this light, we see “for the room” statements and questions as one of the mechanisms by which participation structures are displayed as joinable, by which, so to speak open invitations are issued that anyone can take up. Another difference to the labor room is found in the noticeable absence of the kind of centripetal orientation we saw around the physician which, in multiple and detailed ways, spotlighted him as the focal member. The supervisor in the ops room, on the other hand, is much more likely to be found wandering around between the various work stations, volunteering information and pitching in with required tasks. This is not to say that there is no difference between supervisor and ops workers. The supervisor’s authority becomes visible in tight spots, situations where everybody’s attention has to be focused on a particular problem. He then orchestrates the coordination of activities by giving direct orders. There are also many non-reciprocal interactions that make the difference in rank clear. For example, the supervisor corrects workers, but we did not see a worker directly correct the supervisor. He has greater freedom of movement than the others: the normal working arrangement has him wandering around, looking at the other workers without being necessarily looked at in turn; he is often standing whereas the others are mostly seated; he can tap someone on the shoulder without being tapped on the shoulder in turn, and so forth.27 What I want to point to here, then, is not that there is no difference in authority but rather that this kind of nonhierarchical management style produces, and is itself an expression of, an environment in which all participants collaborate in the production of authoritative knowledge. Given that this locally and jointly constructed authoritative knowledge is the basis for decision-making, it is clear that such decisions will mostly emerge from the situation, rather than from the supervisor in the role of gatekeeper.
Authoritative Knowledge and Technology in Two Settings: A Comparative View I have described two complex, multi-activity, high-technology work settings which differ in how they construct and distribute the knowledge relevant to getting work done. In the labor room, ownership of authoritative knowledge is limited to the authorized staff and distributed differentially and hierarchically among them, while the central participant, the woman in labor, is excluded. In the context of the labor room, medical knowledge is not only privileged, but also supersedes and delegitimizes other potentially relevant information sources such as the woman’s experience and the state of her body. This kind of knowledge is suppressed and delegitimized by all participants, including the woman herself. Professional medical knowledge is displayed as based on privileged technical procedures – machine output and test results interpreted by nurse and physician specialists – that provide legitimization for the management of labor and delivery. By comparison, participants in ops have equal access to the salient communication technologies and procedures, and though there is a pragmatic and historical division of labor, necessary work routines are not privileged. Technology-mediated information is Notes on the Achievement of Authoritative Knowledge 117 available for examination and use by whoever needs it. People mutually assume tasks when the situation calls for it. We also noted differences in the style of conversations that take place in the two settings. In the labor room imperatives are addressed to the woman and evaluative assessments of her performance are made, in much the same ways adults treat children in schools. In the ops room, under normal working conditions, people tend to use mitigated language; address requests, not orders, to others; use “we” instead of “you” in describing actions to indicate the shared responsibility; and phrase evaluations in terms of the jointly accomplished work. In contrast to the labor room where much energy has to be expended on suppressing the rival knowledge which is constantly threatening to seep in, here there is no competing knowledge. Rather, the success of the enterprise consists precisely in maximally taking advantage of the different perspectives contributed by team members towards the shared view of the world that constitutes the basis for decision making in this setting. In spite of the fact that in both settings there are people in formal leadership positions – the physician in the labor room and the supervisor in the ops room – the way participants’ statuses are treated differs. There is a clear hierarchy in the labor room. Checking the woman’s cervix and deciding whether she can push are duties reserved only for the physician. He does not participate in the earlier stages of the labor. He is awaited. He is paged a number of times, and when not found, every attempt is made to stifle the woman’s real need to push the baby out until the doctor can perform the examination and authorize the next stage of the delivery. The woman’s body’s natural responses are systematically erased and then reconstructed under the disinterested tutelage and coaching of the medical staff. This has the effect of taking away any notion of achievement from the woman, so that, indeed, as the nurse says, they (the medical staff) will “finish this up and have that baby.” In the ways in which the woman is led to collaborate in the violation of her body, the abnegation of herself, the misrecognition (in Bourdieu’s sense) of her own interests, in all these ways “the way power circulates in the world” (to use Foucault’s words) is displayed. By contrast, the supervisor in the ops room comes in when an extra hand is needed, but he does not make a grand entrance. He tends to slide in and out of the ops room, interweaving with the activities of others, often simply seated within earshot at his desk. Participants do not focus on him in the way they do on the physician; there is neither anticipation nor grossly deferential orienting. He is not framed in the central position, but rather moves in and out of the interactional frameworks of the ops room as the situation requires. He appears to take responsibility for monitoring the situation and is often seen walking around the room, ever alert to what the room requires, making himself available to assist whoever needs him. While he clearly takes charge in touchy situations, the ordinary decisions of the daily work routine emerge out of what is known by everybody about the current state of the world. The supervisor’s key competence is the ability to coordinate resources. In contrast to the physician, his primary function here is not that of decision maker or gatekeeper. Rather, he offers an example of what a non-hierarchical management style could look like. Production and use of authoritative knowledge are clearly shared. The preceding analysis raises a number of issues. For example, is there any sense in which either horizontal or hierarchical distribution of authoritative knowledge is “better?” But to decide this, one first has to answer the question, better for what purposes? In the sense of “more efficient”? Of lower emotional, cognitive, financial cost? Greater satisfaction for participants? In looking at two settings with different types of authoritative knowledge distribution we have seen some of the consequences. Other questions arise: How common are these types? What other kinds are possible? Is change possible and under what conditions? What changes would (have to) happen in the labor room if the woman’s knowledge were to be given a legitimate role? What would happen if in a redesign of the ops room some technology became privileged? 118 B. Jordan
If the two settings are seen as communities of practice what possibilities do they offer newcomers intending to become competent participants? What implications has the differential distribution of authoritative knowledge for legitimate peripheral participation? As we think about the design and redesign of technology support for human activities, consideration of the role of technology in the production of authoritative knowledge is crucial. It might be particularly interesting to pay serious attention to what it would take to build systems which are sufficiently participatory so that conflicting knowledge systems do not come to grow up.
Acknowledgments An earlier version of this paper was read at the Meetings of the Society for Applied Anthropology in Charleston, NC on March 16, 1990. I thank my colleagues from the Workplace Project and the Interaction Analysis Laboratory at Xerox Palo Alto Research Center and the Institute for Research on Learning for shaping my thinking about the issues discussed here. I am particularly indebted to Bracha Alpert who was an early collaborator on these data. The current version of this document has benefited from critical readings and substantive contributions by Phil Agre, Liam Bannon, Carole Browner, Debra Cash, Terry Craig, Sr. Mary Christine Cremin, Robbie Davis-Floyd, Martha Feldman, Wendy Freed, Jim Greeno, Robert Hahn, Chuck Kukla, Joyce Roberts, Barbara Rylko-Bauer, Ron Simons. I thank Teresa Simons, Lucy Suchman and Valerie Wheeler, and from the editorial sleight-of-hand of Paul Duguid. I thank Teresa Lewandowski for her copy-editing competence as well as her cheerfulness in the face of multiple revisions of this report.
Notes 1 Insofar as authoritative knowledge is unselfconsciously constructed, displayed, and used by participants in their daily interactions, it is similar to Garfinkel’s notion of common sense, which he defines as the socially sanctioned grounds of inference and action that people use in their everyday affairs and which they assume that other members of the group use in the same way. Socially-sanctioned-facts-of-life-in-the- society-that-any-bona-fide-member-of-the-society-knows depict such matters as ... distribution of honor, competence, responsibility, good will, income, and motives among persons; frequency, causes of, and remedies for trouble; and the presence of good and evil purposes behind the workings of things. (Garfinkel, 1959, p. 57) Authoritative knowledge differs from Garfinkel’s common sense in that, under certain circumstances, it comes to be possessed and exercised by a privileged group. 2 The project “A Comparison of Supported versus Directed Care during the Second Stage of Labor” was supported by grant # 1-R01 NR 01500-03 NCNR, NIH, DHHS, and directed by Joyce Roberts. 3 It is worth mentioning here that in less hierarchically organized obstetric systems such official certification is not necessary. In Holland, a country that has vastly better outcome statistics than the U.S., it is a combination of what the woman says and observations of her state by her midwife that determine when it is time to push. 4 By “privileged” I mean to suggest that access is restricted. 5 For example, during an arbitrarily selected five-minute segment of the tape we see the nurse look at the EFM 19 times. It would be well to keep in mind that there are alternative sources of information on the state of the labor: one can monitor the woman’s experience by observing her breathing and the rising and ebbing tensions in various parts of her body. With a hand on the woman’s abdomen it is possible to gauge the Notes on the Achievement of Authoritative Knowledge 119
strength of her contractions directly while a simple fetal stethoscope provides information on the fetal heart beat. These are, in fact, methods used in less technologized and less hierarchically organized settings. 6 Within 17 minutes of the birth of the baby, the woman explicitly states on eight occasions that she has to push. On another 16 occasions during that time, she indicates her inability to resist the urge to push with pleas like: “I can’t, I can’t.” 7 For an explanation of transcript conventions, see appendix A. 8 There is much evidence that non-answers of various sorts are a common strategy for dealing with women in obstetric settings. For example, Kirkham, who observed 113 labors, describes similar responses in labor wards in the UK. She cites the following as a typical pattern: Woman: “How long?” Nurse: “Not long.” Woman: “How long is that?” Nurse: Silence. End of conversation. Or changes subject (Kirkham, 1988). 9 We can speak of the woman as “losing control” – and see her as “losing control” – only if we subscribe to the view that she should shape her behavior according to what the medial staff require of her at this time. Within another framework, e.g. one that sees pushing as precisely what her body should be doing at this stage, she would simply be doing what she is supposed to be doing. I find it personally disturbing that I myself did not see the absurdity of this formulation until it was pointed out to me. This is just one of the ways in which, to use Harvey Sacks’ expression, culture has us by the throat. 10Subscribing to the “he he he hoo” generates a double bind for the woman. If the pain gets so intense that she cannot maintain the pattern, her abandoning it tells her and her attendants not only that she is now “out of control” but also that she did it, that by abandoning the Lamaze breathing she made herself lose control. The common reprimand: “If you had done your Lamaze, you wouldn’t have lost control” is true by definition. 11For the transcripts from which this and all following examples are taken please see appendices A and B. 12 The numbers in transcripts represent (hours:)minutes.seconds since the start of the videotape. 13I first drew attention to the operational bifurcation of the woman’s body in hospital deliveries in Jordan (1987b). 14Kirkham contrasts “waiting on doctors“ with “waiting on the labor,” which, she says, good midwives do when they are in charge of birth. They take their cues from the woman in labor, whereas for the vast majority of women whose labors she observed, the cues they gave and indeed their specific requests were ignored. Midwives and occasional doctors who waited on the labor, on the other hand really listened to the woman. Such listening is rare in most hospital settings because the staff’s primary responsibility appears to be listening to and waiting on the doctor. 15All proper names are pseudonyms. 16I am indebted to Charles Goodwin for this figure. I am indebted to Klaus Rögner and Matthias Kating for their assistance in re-formatting the manuscript. 17ETA: Expected Time of Arrival. 18Bregman, in a recent book entitled auditory scene analysis: The perceptual organization of sounds, suggests a mechanism he calls auditory stream segregation in which pitch plays a major role. He notes that mixing a spoken word from one speaker with the babble from many others buries the frequency characteristics of the word in a spectogram, yet a speaker may still be easily understood if the pitch of the utterance is sufficiently different from the pitch of surrounding conversations (Bregman, 1990). 120 B. Jordan
19A problem that occurred in this ops room without advance warning is analyzed in Suchman and Trigg (1991). A plane’s exit stairs had become inoperative and in that case resources had to be mobilized on the spot. 20Barley (1988) gives a detailed account of this process in a different professional community. He describes how the operation of initially experimental, unfamiliar technology becomes routinized and absorbed into the standard practice repertoire of a professional community. A salient part of this process is the routinization of anomaly, i.e. learning by experience which kinds of troubles tend to re-occur and what range of resources can be assembled and held available for their solution. Similarly, Koenig (1988) analyzes the processes involved in “the social creation of ‘routine’ treatment” as new methods for therapeutic plasma exchange are introduced. In these studies and others of a similar vein it becomes clear that the relevant knowledge is not available through formal instruction but is co-constructed within communities of practice as actors appropriate the new technologies and what they afford. 21Ops room personnel may refer to the same plane by three different numbers: the flight number (e.g. 1018), the gate number (e.g. 15), or the aircraft number (e.g. 677). The latter uniquely identifies the plane as a physical object to which plane-specific performance and repair statistics can be traced. 22In ops room parlance, “677 takes out 1091.” 23I am indebted to Teresa Lewandowski for this figure. 24This insight into the gap between the world as it should be and the world as it actually is encountered and managed by on-the-ground actors has remained a guiding principle in our understanding of systemic issues in corporations and other large organizations (Jordan, 2011; Jordan & Lambert, 2009). 25For complete transcript segment and explanation of transcription conventions used see appendix B. 26Again, we find striking parallels in Heath’s work in the London Underground Control Room where there is a similarly pervasive orientation to updating “the room” (Heath & Luff, 1996). 27I am indebted to Phil Agre for some of these points.
References Barley, S. R. (1988). The social construction of a Goffman, E. (1963). Behavior in public places: Notes machine: Ritual, superstition, magical on the social organization of gathering. New thinking and other pragmatic responses to York: Free Press. running a CT Scanner. In M. Lock & D. Gordon Goffman, E. (1981). Forms of talk. Philadelphia: (Eds.), Biomedicine examined (pp. 497–539). University of Pennsylvania Press. London: Kluwer. Goodwin, C., & Goodwin, M. (1996). Seeing as Bourdieu, P., & Passeron, J.-C. (1977). Reproduction situated activity: Formulating planes. In Y. in education, society and culture. London: Engeström & D. Middleton (Eds.), Cognition Sage. and communication at work (pp. 61–95). New Bregman, A. S. (1990). Auditory scene analysis: The York: Cambridge University Press. perceptual organization of sound. Cambridge: Heath, C. (1986). Body movement and speech in MIT Press. medical interaction. Cambridge: Cambridge Davis-Floyd, R. (1992). Birth as an American rite of University Press. passage. Berkeley: University of California Heath, C., & Luff, P. (1991). Collaborative activity Press. and technological design: Task coordination in Garfinkel, H. (1959). Aspects of the problem of London Underground control rooms. common-sense knowledge of social structures. Proceedings of the Second European Transactions of the Fourth World Congress of Conference on Computer-Supported Sociology (IV, 51–65). Cooperative Work, Amsterdam, The Notes on the Achievement of Authoritative Knowledge 121
Netherlands. Berghahn. Draft available at http://lifescapes. Heath, C., & Luff, P. (1996). Convergent activities: org/Papers/7_Ch_4%20%20Jordan.doc Line control and passenger information on the Kendon, A. (1985). Behavioural foundations for the London Underground. In Y. Engeström & D. process of frame attunement in face-to-face Middleton (Eds.), Cognition and interaction. In G. P. Ginsburg, M. Brenner, & M. communication at work (pp. 96–129). New von Cranach (Eds.), Discovery strategies in the York: Cambridge University Press. psychology of action (pp. 229–253). London: Irwin, S., & Jordan, B. (1987). Knowledge, practice Academic Press. and power: Court-ordered Cesarean sections. Kendon, A. (1990). Conducting interaction: Patterns Medical Anthropology Quarterly, 1(3), 319-334. of behavior in focused encounters. Available at http://lifescapes.org/Papers/ Cambridge: Cambridge University Press. COCS%20Hahn%201987.htm Kirkham, M. (1988). Midwives and information- Jordan, B. (1977). The self-diagnosis of early giving during labour. In S. Robinson & A. M. pregnancy: An investigation of lay Thomson (Eds.), Midwives, research and competence. Medical Anthropology ,1(2), 1– childbirth (pp. 117–138). London: Chapman & 38. Available at http://lifescapes.org/Papers/ Hall. Self%20Diagnosis%20of%20Early%20Pregna Koenig, B. A. (1988). The technological imperative ncy.pdf in medical practice: The social creation of a Jordan, B. (1987a). High technology: The case of “routine” treatment. In M. Lock & D. Gordon obstetrics. World Health Forum, 8(3), 312–319. (Eds.), Biomedicine examined (pp. 465–495). Available at http://lifescapes.org/Papers/ London: Kluwer. hi%20tech%20obstetrics%20WHO.doc Lave, J., & Wenger, E. (1991). Situated learning: Jordan, B. (1987b). The hut and the hospital: Legitimate peripheral participation. New York: Information, power and symbolism in the Cambridge University Press. artifacts of birth. Birth: Issues in Perinatal Care Leveno, K. J., Cunningham, F. J., Nelson, S., Roark, and Education, 14(1), 36–40. Available at M., Williams, M. L., Guzik, D., Dowling, S., http://lifescapes.org/Papers/87%20HutHospi Rosenfeld, C. R., & Buckley, A. (1986). A tal.doc prospective comparison of selective and Jordan, B. (1989). Cosmopolitical obstetrics: Some universal electronic fetal monitoring in insights from the training of traditional 34,995 pregnancies. New England Journal of midwives. Social Science and Medicine, 28(9), Medicine, 315, 615–619. 925–944. Available at http://lifescapes.org/ Prentice, A., & Lind, T. (1987). Fetal heart rate Papers/cosmopolitical%20obstetrics%20SSM monitoring during labor – too frequent %2089.doc interventions, too little benefit. Lancet, Jordan, B. (1993). Birth in four cultures: A 2(8572), 1375–1377. crosscultural investigation of childbirth in Sacks, H. (1992). Lectures on conversation. (Ed. by Yucatan, Holland, Sweden and the United States G. Jefferson, Vols. I and II.) Cambridge: (4th, expanded ed., rev. by R. Davis-Floyd). Blackwell. Prospect Heights: Waveland. (First edition Schegloff, E. A. (1998). Body torque. Social 1978, Eden.) Research, 65(3), 535–596. Jordan, B. (2011). Transferring ethnographic Starr, P. (1982). The social transformation of competence: Personal reflections on the past American medicine. New York: Basic Books. and future of work practice analysis. In M. H. Suchman, L. (1987). Plans and situated actions: The Szymanski & J. Whalen (Eds.), Making work problem of human-machine communication. visible: Ethnographically grounded case New York, Cambridge University Press. studies of work practice (pp. 344–358). New Suchman, L., & Jordan, B. (1988). Computerization York: Cambridge University Press. Draft and women’s knowledge. In K. Tigdens, M. available at http://lifescapes.org/Papers/ Jennings, I. Wagner, & M. Weggelaar (Eds.), Transferring%20Ethnographic%20Competen Women, work and computerization (pp. 153– ce%20091201%20gj.doc 161). Amsterdam: North Holland. Also Jordan, B., & Henderson, A. (1995). Interaction published in Proceedings of the IFIP analysis: Foundations and practice. The Conference on Women, Work and Journal of the Learning Sciences, 4(1), 39–103. Computerization, Amsterdam, April 27–29, Available at http://www.lifescapes.org/ 1988. Papers/94%20IA%20IRL.pdf Suchman, L., & Trigg, R. H. (1991). Understanding Jordan B., & Lambert, M. (2009). Working in practice: Video as medium for reflection and corporate jungles: Reflections on design. In J. Greenbaum & M. Kyng (Eds.), ethnographic praxis in industry. In M. Cefkin Design at work: Approaches to collaborative (Ed.), Ethnography and the corporate design (pp. 65–89). Hillsdale: Erlbaum. encounter: Reflections on research in and of Zuboff, S. (1988). In the age of the smart machine. corporations (pp. 95–133). New York: New York: Basic Books. 122 B. Jordan
The Author Brigitte Jordan has had a varied career in academia as well as industry, first as Professor of Anthropology and Community Medicine at Michigan State University and then as Principal Scientist at the Xerox Palo Alto Research Center (PARC) and as Senior Research Scientist at the Institute for Research on Learning. Currently she consults on topics of interest to her, primarily focused on socio-technical issues in the interface between high technology and people’s everyday lives. Her most recent project is located in a high-tech industrial laboratory in Silicon Valley that is dedicated to research on the driverless car of the future. Brigitte Jordan has received a number of honors and awards, including the Margaret Mead Award of the American Anthropological Association and the Corporate Research Award for Excellence in Science and Technology of the Xerox Corporation. She has published several books, chapters and articles, including “Birth in Four Cultures: A Crosscultural Investigation of Childbirth in Yucatan, Holland, Sweden, and the United States”, and “Advancing Ethnography in Corporate Environments: Challenges and Emerging Opportunities. Many of her writings are available for download on her website www.lifescapes.org.
Appendix A:
Transcript of Labor Room Activities Wom: Woman in labor Nur: Obstetric Technician Hus: Husband Y: female voice off camera YMed: female medical student Doc: physician
UPPER CASE emphasis, loudness (xxxx) inaudible material a ::::::: lengthened sound (coming) transcriber’s guess [ ] untranscribable sounds [ overlapping talk
Note. much of the talk and other verbal productions are overlapping. Overlaps are not consistently indicated on transcript. Numbers on transcript represent minutes and seconds and correspond to the following format on tape: xx.MM.SS.xx, e.g. 00:19:09:16 appears in transcript as 19.09. We are 14 minutes from the birth of the baby, 19 minutes after videotaping started.
Talk Activity 19.09 Wom: o:::::h::: [ Nur: try not to curl your toes nurse rubs the woman’s toes, then leans over her, looking briefly at EFM, hands Wom: I can’ hhh I can’, I feel like I gotta push behind back 19.13 hu::::h Nur: you can pretty soon oka::y:? intonation as if speaking to a child Wom: N::O:::W woman obviously in pain hu:::h hu::::::h, hu:::::h, hu::::::h nurse moves hand next to woman’s face woman wipes her face with a washcloth Notes on the Achievement of Authoritative Knowledge 123
19.20 Nur: I’m gonna have them come and check you and we’ll see if you can. Oka:y? Do the same thing use this rest period in between ‘khay? nurse looks towards door, then looks at EFM; exits 19.29 Wom: [pain sounds, stressed outbreaths] breathing slowing down, turns head towards husband K:E:N:: uh o::::::::h::: [ 19.39 Hus: right here husband comes and stands next to woman’s bed, leaning towards her Wom: [rapid pattern Lamaze breathing nurse comes back in, glances at EFM, he he he hoo then at woman; stands next to bed, 19.50 leaning over woman Nur: ‘khay. Ruth come on glances at EFM Wom: he: he: he: hoo 19.56 he: he: he: hu:h breathing hard, barely maintaining I can’t control Nur: look at me nurse is leaning over woman, mouthing he he he hoo the Lamaze breathing pattern Wom: [attempts he he he hoo pattern] woman increasingly distressed Nur: he he looking at woman just with your mouth just come on [ 20.02 Wom: I can’t hu uh [ Nur: look at me, try that’s all you can do is try Wom: he he he hoo: 20.10 HOO:::::::hh, he uh nurse glances at EFM [ Nur: come on leaning over woman it’s at the peak Wom: he he he he he hoo [ 20.15 Nur: good glances at EFM Wom: he he hehoo [ Nur: oka:y it’s going down soothing voice [ Wom: he he he-he husband is still standing next to woman, [ looking at her; she is looking at nurse Nur: it’s a smaller contraction Wom: HOO:::::::H::::::: woman sounds like she is in great pain [ Nur: almost gone insistent voice [ Wom: OO:::::H::::: Y: (xxxx) woman wipes her face with washcloth nurse straightens up, turns away from woman to someone off camera 20.23 Nur: U:h-make sure Terry’s got the house staff with smile in her voice and on her face (coming/called) okay? Y: (xxxx) Wom: [moaning, in pain] 20.33 Nur: she called them (with the information) they to Y off camera should be. here any minute [ 20.37 nurse turns back towards woman, glances at EFM, wipes nose with left hand Wom: O:H::::: no::::: sounds despairing hhhu:::hh husband looks on silently 124 B. Jordan
I::: ca:::n::::’t 20.41 Nur: almost finished leans down to woman again, speaking in a cleansing breath low, almost intimate voice oka:y? Wom: [heavy in-and exhaling] 20.47 Nur: let’s just say you can: leaning over woman oka:y? 20.53 Wom: o:::::::::, no: no: no::: moaning in pain Nur: looks at EFM [ Nur: one cleansing breath as if talking to a small child big deep sigh? [ Wom: o::: :::h [heavy exhaling) Hus: adjusts woman’s cover in a soothing way Nur: good now rest up save your energy for this woman puts washcloth on her face next contraction okay? [ Wom: OH:: I ca::::n::’t Nur: scratches her upper lip, adjusts EFM output, looks at EFM Wom: uh-huh 21.05 ay:ay:ay:ay:ay:ay:ay:ay: rhythmic pain sounds ay:ay:ay:ay:ay:ay ay ay nurse writes in chart on top of EFM, [exhales] glancing back to check clock Hus: you want some ice? woman pats her face rhythmically with washcloth, indicates “no” 21.17 Wom: I just wanna push 21.19 Nur: I know it won’ be long it’ll feel better for speaks to woman without looking at her you to push while writing in chart but in the meantime leans towards woman and whisper I don’t want you to okay’? emphatic 21.27 Wom: NO:::H: I can’t help it [exhales] [ 21.28 Nur: Let’s make sure that cervix is singsong voice completely gone oka:y just try it that’s all I ask(xxx) looks at EFM, then starts writing Wom: 0:::::o:: o:: H::: K:E::::N: moaning in pain and distress, turns towards husband, lifts head Y: Sue: off camera 21.44 Nur: yea::h continues writing without looking towards speaker Y: She said she paged him a second time (and she wasn’t sure he’s coming) so I’ll just wait here(xxx) Wom: 0::::o::::o::I:::I can’t I can’t::: briefly lifts her head He he he he he begins a new round of rapid Lamaze breathing 22.00 Nur: good Wom: he he he hoo lifts head and upper half of her body in he he he hoo pain he I::no:: no:: 22.10 Nur: he he he hoo bends over woman, insistently modelling he he he hoo Lamaze breathing he he he hoo he he he hoo Wom: he he hoo he he he hoo attempts to breathe in unison with nurse he he he hoo he he he hoo Notes on the Achievement of Authoritative Knowledge 125
I:o:: no::no::no:: 22.17 Nur: (xxx) away it’s at the peak glancing at EFM he he he hoo woman in great pain, Wom: no::it’s not: barely able to keep he he he he he up Lamaze sounds O:::::::::::O Nur: come on sounding ever so slightly impatient he he he hoo he he he hoo (xxx) okay 22.22 Wom: he he he he hoo::::o cannot maintain nurse’s rhythm, her he he he he hoo sounds fall in between those of the nurse he he he hoo HE::HE::HE::HOO O::he he hoo Nur: it’s past the peak sing-song voice easing up going away turns back toward YMed who entered the room 22.38 she needs to be checked this time to YMed YMed: ahm: (xxx) Wom: O:::: o::go::d O:::::o O::::::o Nur: talking to YMed while moving away from bed, off camera 22.44 YMed: actually (xxx) and (Jim) is coming both YMed and Nur are off camera talking, moving something Nur: (xxx) YMed: first things first Wom: O::::::o wiping her face (XXX) plea:::se heavy pain sounds 22.53 Hus: moves off camera Wom: O:::::o
Nur: both approach bed. YMed puts a glove 23.00 YMed: on her hand, Nur squeezes some jelly from a tube on YMed’s finger Wom: plea:::::se 23.05 Nur: we’ll check you now, okay? see if your lifts sheet from woman’s legs, steps out cervix is completely dilated of the way Wom: [moaning, heavy pain sound) 23.13 YMed: okay approaching lower part of woman’s body [ Wom: [moans] Nur: positions herself to mark EFM graph 23.19 YMed: rest for me, okay? inserts hand, looking up while performing the check deep breath Wom: [heavy outbreaths] 23.30 YMed: head’s down (xxx) singsong Nur: good. marks the EFM output sheet Wom: O::::o no:: no::::::::::::o Nur: plus one? while marking EFM output YMed: yes Wom: no:::: outbreaths, moaning 23.40 YMed: can you open your legs a little bit more to woman for me Wom: aye I gotta::::aye:::hm:::: breathing heavily 23.50 Nur: okay. he he he hoo bends over woman breathing with her wipes her forehead with a towel Wom: he he he hoo he he he hoo 126 B. Jordan
he he he hoo 23.54 YMed: open up for me continuing with examination Wom: he::AYE::::AYE::AYE:::::: increasingly desperate pain sounds lifts her head 24.00 Nur: come on models breathing he he he hoo come on wipes woman’s forehead Wom: A::::o::: YMed: I’m not sure she is pretty close to to nurse; pulls off glove (complete) 24.04 Wom: AY::::: shouting in pain Nur: arranges the sheet back on woman’s legs while talking to YMed who moved away YMed: (xx) right now in a light voice 24.11 Wom he he::HURRY::: raises voice even more, heavy breathing Nur: almost gone takes woman’s hand she thinks you might be completely whispering done okay? 24.24 Wom: O:::::::::::o [camera moves in for close-up and Nur: it’s almost time to have this baby moves back] Wom: GO::::d:::::: why don’t they hurry:::: Nur: (let’s put your bed up) sound of some electric adjustment Wom: O:::::w::::::: slaps her own forehead moaning I want something for the pa:::in heavy outbreaths 24.50 Nur: feeds woman some ice chips with a you almost finished spoon it’s, it’s probably too late for anything, okay? puts the glass with the ice away [ Wom: [moaning] 24.58 Nur: you just gonna have to wait okay? wipes woman’s face with a towel that’s it you’re almost finished writes in chart 25.05 Wom: KE::N outbreathing, crying Hus: comes over and stands next to bed nurse is writing in chart 25.15 Wom: A::::ye:::: he he he aye::: he he he:: he he he hoo he he he hoo raises upper body he he he heavy breathing 25.27 Nur: go ahead Ruth puts pen in pocket, turns back to woman good Wom: I can’, I got to push 25.30 Nur: okay, open your eyes bands over woman her hands behind her he he he hoo back he he he 25.34 YMed: goes toward EFM and observes output Nur: just with your mouth not your chest Wom: [ sounds of pain he he he hoo together with nurse he he he hoo I CAN’T O::HO::::: very loud cry 25.45 YMed: she starting to push yet? to nurse Nur: not yet, but it’s right here points to EFM output (xxxx)okay? turns to YMed as the YMed takes off her white coat and walks away, short inaudible exchange between them Notes on the Achievement of Authoritative Knowledge 127
[ Wom: O::HO::::: crying, heavy breathing 25.51 Nur: almost gone to woman, bending over her it’s past the peak sing-song voice, trying to be soothing· easing up Hus: walks away from woman’s bed Wom: KE:N loud voice where are you going? 25.57 Hus: I’ll be right here 26.00 Nur: good job to woman, after briefly looking toward you almost done husband it’s almost all over wipes woman’s face with towel Wom: oh go:d 26.12 YMed: approaches EFM and observes the output Nur: moves off camera (to see about the page?)
YMed: takes over 26.18. Wom: I can’t YMed is standing by bed, hands on hips, I have t’pu:::sh then puts one hand on woman’s knee 26.25 YMed: NO:::
listen voice patterned, with a rehearsed quality take some deep breaths one hand on the woman’s knee, rubbing it deep breaths right now (x gonna get) someone to check is gonna see if you can push okay? she’s gonna (do it) right now [ Wom: [breathing heavily] YMed: I don’t know why somebody (xxxx) turning away from woman, speaking to (giggles) he is supposed to follow me, nurse in a chatty tone of voice you know when you’re paged woman lifts her head as if trying to see Nur: YEAH what they are doing 26.44 YMed: while one was right behind me and-uh he left (chuckles) 26.46 turns back into woman’s direction and adjusts face from “laugh face”- to professional demeanor; looks at EFM Nurse back in, takes over again Wom: [moans] inaudible conversation between nurse and YMed; nurse walks to monitor, checks clock and starts writing. 26.56 Wom: O:h god where are they desperate he:: he : nurse puts her pen in her pocket Nur: I know speaks in a pitying voice, while leaning we’re almost there over woman YMed: moves off camera, in response to doctor’s entry? Wom: [high pitched pain sounds, sobbing, in- and exhales heavily] YStud: We got it off camera Doc: ‘kay off camera 27.09 Doc: doctor walks in, followed by male medical student who is carrying a white coat; doctor approaches the bed without looking at the woman or speaking to her; immediately goes to EFM; pulls up output and glances at it. Wom: I can’t Nur: come on leaning over woman he he he hoo he he he hoo 128 B. Jordan
he he he hoo [ Wom: he he he hoo struggling desperately to maintain the he he he hoo pattern; great urgency in her voice he he he hoo he he he hoo 27.20 Doc: hmh inaudible conversation with YMed who holds out·a glove for him Wom: AYH AYH he oo nurse is wiping woman’s face with the washcloth 27.26 Doc: thanks. okay to YMed doctor walks towards monitor, drops glove wrapper on EFM Nur: leaning over woman, turns head to look good at EFM perfect, Ruth
past the peak singsong voice going down, slowing down Doc: pulls glove onto right hand, participants arrange themselves to frame him: he looks around, then goes over to turn spot lights on Nur: looks back at doctor, straightens up away from woman, tracks doctor’s actions Wom: [moaning] doctor approaches woman; looks at her O::h, I gotta pu:sh: for the first time since entering 27.49 Doc: let me check you before you get nurse walks to EFM, shuffles papers, another contraction starts to write but doesn’t okay? doc uncovers the sheet over woman’s let’s see if you can push legs come on over [ Wom: ey: I can’t: 27.58 Doc: come on cajoling tone, like to a child 27.58 YMed: he is checking to see if you can push in instructional voice, with a rehearsed okay? quality so try to relax leans over woman and rubs her shoulder some deep breaths here 28.00 Doc: starts examination Nur: take a deep sigh now (one or two xx) low whispering voice leaning very low over woman, holding her hand [ Wom: [heavy breathing and moaning] Doc: (Yeah I know) to medical student, in a low voice YMed: (xxxx) 28.10 Doc Yeah to nurse she can push Nur: can she? plus one? looking up at doctor getting ready to write Doc: yeah plus two nurse writes in chart Wom: Oh :NO:::: in pain 28.15 Nur: you can push to woman, with relief, like a good news it’ll fee good announcement Wom: uhoo::::::::::: woman moaning in pain nurse straightens up 28.16 Doc: just get her woman continues moaning just go ahead and get her into (the nurse and medical student start to lithotomy position) prepare woman for the delivery. 28.20 Nur: okay, Ruth, go ahead and just bear down. Put all you’re worth into your next contraction, okay? Notes on the Achievement of Authoritative Knowledge 129
Appendix B
Transcript of Ops Room Activities
BP: Baggage Planner SUP: Supervisor OPS-A: Operations A (in charge of jets) OPS-B: Operations B (in charge of commuter planes) PSP: Passenger Service Planner
(xxxx) inaudible material (zero left) possible hearing ::: lengthening of preceding sound - - - - (underline) stress = “latched to” preceding utterance (ending with =) without normal pause.
Note: much of the talk and other verbal productions are overlapping. Overlaps are not indicated. Most Tower and Ground Control radio communications are not transcribed. “Pilot” here means the person on plane who works the radio, most likely the First Engineer or copilot. The time is indicated in minutes and seconds just after 7 pm on a Wednesday evening. All proper names are pseudonyms.
Talk Activity 7:04.58 BP: Sorry. Ten-ninety-one just moved to on radio to Redge, crew chief at gate 19 nineteen (xxxx) nine-oh-nine and two-two- five will hold for gate nineteen SUP: walking around in room, glancing at work stations and activities OPS-B: looking up at video monitors PSP: Okay, you just about got everybody on? [to gate 15] Okay. Alright. Thanx. puts phone down, still looking up at monitors 7:05.02 That’s the last of the people there. He said catering was originally in the way turns to speak into room back there, so [re flight 475 at gate 15] 7:05.03 OPS-A: Uh-yes. The airplane will go on to Seattle- on radio, talking to aircraft #656, flight uh. You guys are-uh continuing on ten- 1091, coming into gate 19 ninety-one, right? 7:05.04 SUP: walks towards PSP’s work station, works camera controls, looking up at video monitors 7:05.11 PSP: you might wanna tell the ramp-uh they can [re flight 475] go in and probably plan to pull those stairs steps over to BP, who does not react; up (while xxxx) [she is listening to radio on head phone]; goes back to his station, looks up at monitors again. SUP: walking around the room, hands in pockets 7:05.13 OPS-A: Okay. You’ll be looking for aircraft six- [to pilot of flight 1091] seven-six which is here and it’s-uh being [false information] pulled into gate fourteen right now, so the turns head, looks up to check info on airplane will be here when you get here. video monitor 7:05.21 BP: Okay, yeah, they’ll they’ll be told to hold still talking on radio to crew chief at out there at that gate gate 15 7:05.25 SUP: swivels on heels, walks back to OPS-A, taps him on shoulder (or points to schedule) OPS-A: Roger? 130 B. Jordan
7:05.26 BP: Sorry, Dave, what (was that)? swivels on chair towards PSP, now acknowledging his earlier request PSP: We didn’t end up using the rear stairs turning to BP BP: Oh. PSP: I guess Marriott’s was in the way earlier so- uh and that’s the last of the people; we can go ahead and put those rear stairs up. 7:05.29 OPS-A: I’m sorry, disregard. Six-seven-seven. [to pilot of flight 1091] Fifteen. [corrects mistake] 7:05.33 BP: On fifteen? [re 475] PSP: Fifteen. yes (x). OPS-A: U::h 7:05.34 SUP: =Two-two-five, (Dave)? looking at OPS-A PSP: In rapid sequence, looks at monitor, manipulates camera controls, types into computer OPS-B: picks up a piece of scrap paper and makes a note. OPS-A: will be ten-ninety-one and he’ll be touching down in about five minutes. turns face up to supervisor SUP: Is that two-two-five? to OPS-A OPS-A No. 7:05.39 BP: takes drink from pop can, looking up at monitors intermittently SUP: If he calls in he’s gonna have a wait till forty [to OPS-A] [i.e. till 7:40 pm for gate 19] for a gate walks towards monitors OPS-A: Okay. [to supervisor] looks up at video monitors 7:05.43 SUP: or longer looking up at monitors 7:05.47 PSP: turns head away from monitors, looks down to desk; possibly receiving radio call over ear phone 7:05.48 BP: Kevin, (you guys gonna xxxx) [re 225] turns towards OPS-A in chair, holds torque position 7:05.50 PSP: Whenever we get-u::h looking down at his desk 7:05.51 OPS-A: Oh they turned the tug around, is that what [re #676 move], glance to monitor, then they’re doing? to BP And hook back up again? BP: (uh-huh pull) and drive forward into the talking to OPS-A gate there OPS-A: U::h 7:05.55 PSP: raises head listening to radio, Go ahead bends down to write on desk 7:05.59 BP: You guys gonna tell the-uh cockpit on two- two-five (they’re gonna hold, so they don’t [re 225] go zooming in here) OPS-A: If he calls me 7:06.03 SUP: working camera controls BP: Yeah nods, turns back to her work station, looks at monitors PSP: Thank you. into radio, leaning down onto his desk, making a note 7:06.06 SUP: He won’t have anywhere to go anyway looking up at monitors [re 225] OPS-A: He can’t zoom in anywhere cause twenny- [re 225] one’s full, so:: hhh: 7:06.13 OPS-B: gets up and takes output from printer BP: no, nineteen’s (the one xx) to OPS-A; turns back to her work station, looks down at her complex sheet SUP: (xx there’s gonna be somebody in there walks away from camera controls, pretty soon.) hands in pockets 7:06.16 SUP: So. the barn will be full when he gets here. turns around to look at monitors again BP: types on keyboard with single fingers of left hand Notes on the Achievement of Authoritative Knowledge 131
OPS-B: looks at output and rips it up SUP: works cameras, looking at monitors 7:06.29 Eleven-forty-seven’s gone. [freeing gate 20 for 1161] PSP: Excuse me, I’m sorry [into radio, re 1161, complex 8] types furiously, makes a note, types again OPS-B: types briefly, looks up at monitor BP: writes on complex sheet, erases SUP: (fairly inaudible conversation with ethnographer who is off camera) 7:06.39 OPS-A: Okay-uh, ten-ninety-one will be here at [ETA at 7:18 and ETD at 7:40pm] eighteen. So that forty oughta work pretty good for nine-oh-nine outbound. PSP: Yeah. ‘kay. into radio BP: (Brad’s) gonna be a little upset SUP: turns toward BP 7:06.57 PSP: eleven sixty-one was out of LA on time but [to room, re complex 8] he’s 14 minutes late getting here. brief glance at OPS-A. BP marks her complex sheet, OPS-A updates FID screen and complex sheet. SUP: (joking remark to BP: He normally works turns around, looks up at monitor, till eight. He can leave early. They both yawning chuckle) 7:07.08 PLT: San Juan ops ( ) fifty-one forty-one [flight 5141, plane #359, complex 8] [mechanical problem] 7:07.11 OPS-B: picks up radio handset This is San Juan go ahead please ( ) fifty- one forty-one? PSP: he’ working camera controls, looking at monitors 7:07.13 PLT: Would you call (the barn at eight and send xxxx) OPS-B: I sure will. Thank you. [re 5141/ plane #359] picks up phone, dials 7-digit number glancing at info sheet tacked up above him 7:07.16 OPS-A: Let’s see. Whadda we got. I don’t know any [OPS-A may have pulled up crew sheet of those people. Who’s? Oh, that’s Ed for 1018 on computer] Mitchell. Nyuh? He’s usually a pretty laid back guy, isn’t into room, looking at video monitors he? (pause) Isn’t he? PSP: opens yellow marker and marks complex sheet 7:07.18 SUP: walks off camera BP: types computer entry with both hands 7:07.30 BP: (Isn’t he) a chief pilot or something? turns head to left, continues typing OPS-B He used to be OPS-A: long time ago, yeah. turns into room I talked to him .a couple of times (during pilot training) he’s pretty nice guy PSP: continues to look at monitor and check off planes on complex sheet. Closes marker. Picks up complex sheet and makes entry on computer OPS-B: typing while holding phone to ear, waiting for answer 7:07.54 TWR: Heavy ten-eighteen San Juan Tower clear to land runway three zero left [first plane from complex 8 from Seattle landing 20 mins early] 7:08.00 OPS-A: ten-eighteen’s cleared to land for fiftee:::n. PLT: Ten-eighteen (pause) on the-uh visual three zero left TWR: Landing ten-eighteen San Juan Tower clear to land runway three zero left traffic two 132 B. Jordan
miles right base turning final is a metro liner at one thousand. (He’ll land) on three zero right. 7:08.03 BP: picks up radio control with right hand 7:08.10 OPS-B: redials BP: ten-eighteen is cleared to land for gate fifteen. drops radio control in lap, types 7:08.17 OPS-B: Hi, Charlie, this is Randy in ops? Uh- on phone Mitchell just landed three-five-niner looking for a mechanic and called. The Hawks maintenance (and then went) down [re 5141/plane #359] there, so if you happen to see one tell them that three-five-niner is going down there (when he comes in) alright? Thank you hangs up, turns toward room, looking up at monitors BP: looking at computer screen and making entries in complex sheet 7:08.29 PSP: glances up at monitor, then turn to That sure worked out good to get that OPS-A airplane moved, didn’t it? [re #676] 7:08.32 OPS-A: Huh? PSP: that plane got over there without again looking at monitor getting in anybody’s way? OPS-A: Yeah. 7:08.35 PSP: ‘ts great. 7:08.37 OPS-A: We got lucky that one-eighty-four took a [184 was at gate 16] small mechanical (snicker) [re #676] BP: moves paper to left of her work area; types with both hands 7:08.46 PSP: turns to station, picks up paper, today one looks up at information sheets tacked up above his station 7:08.48 OPS-A: Eleven-forty-seven, roger? on radio, talking to plane on runway preparing to leave Eleven-forty-seven take-off is eighty- seven- three, fuel thirteen-seven, zero a half, seventy-three five, status six and a [Reads “numbers” - weights and half, flaps five, passengers sixty, security balances] okay PSP: back to typing into computer BP: stretches towards fuel slip slot, makes a remark? 7:09.10 OPS-B: Four-seventy-five has pulled the stairs spoken into room; he has been looking up at video monitors throughout 7:09.12 PSP: ‘kay BP: picks up radio control from lap four-seventy-five locked up (and away) [freeing gate 15 for incoming 1018]
Instructions to authors
The Journal Talent Development and Excellence is an international scholarly journal. Manuscripts should be written in accordance with the publication manual of the American Psychological Association. See http://apastyle.apa.org/ Manuscripts must be written in English. It is recommended that non-native English speakers have their papers checked in regard to language accuracy prior to submission.
Submission and Reviewing Manuscripts may be submitted electronically to one of the Editors-in-Chief. All personal data will be removed by the Editor prior to the refereeing process to allow for a masked review.
Manuscript Length: A paper submitted should not exceed 6000 words including abstract, references, illustrations and appendixes. Abstract: An abstract should consist of a maximum 125 words. The abstract must, if it is the result of an empirical research, briefly outline theoretical basis, research question/s, methodology and instrumentation, sample/s and important characteristics (e.g. number, gender and age) as well as the main findings of the study. Also, it should include main conclusions. An abstract for a theoretical article or a review should describe the topic, the objective or thesis and the scope of the article. It should also outline the main conclusions. Footnotes should be numbered consecutively with superscript Arabic numerals. If reporting statistics, sufficient information must be included according to the APA Manual.
Figures and Tables Figures and Tables must be placed on separate pages; not included in the text. They should be submitted as separate file/s. Figures and Tables must have an Arabic number, an explaining text and a title. Their approximate place in the text should be clearly indicated. Authors should follow APA format in designing tables and figures and consider the fact that illustrations supplements - not duplicates - the text. In the text, refer to every table and figure and tell the reader what to look for. Discuss only the table's highlights.
Presentation of the Authors For the presentation of the Author(s) please hand in a digital photograph (min. 300 dpi, 4x5 cm/ 1.6x2 inch) and a description of yourself (max. 100 words).
If you have any questions about references or formatting your article, please contact the Editors-in-Chief.
Copyright It is a condition of publication that authors assign copyright or licence the publication rights in their articles, including abstracts, to the International Research Association for Talent Development and Excellence. Authors are themselves responsible for obtaining permission to reproduce copyright material from other sources.
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online)