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The perceived seriousness and incidence of ethical misconduct in academic science
Davis, Mark Stephen, Ph.D.
The Ohio State University, 1989
Copyright ©1989 by Davis, Mark Stephen. All rights reserved.
UMI 300 N. ZeebRd. Ann Arbor, MI 48106
THE PERCEIVED SERIOUSNESS AND INCIDENCE
OF ETHICAL MISCONDUCT IN ACADEMIC SCIENCE
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Mark S. Davis, B.A., M.A.
*****
The Ohio State University 1989
Dissertation Committee: Approved by
Simon Dinitz
Joseph E. Scott Adviser Kent P. Schwirian Department of Soci'tJlogy Copyright by Mark S. Davis 1989 To the memory of my father, Clyde H. Davis, a man who knew little about science but much about integrity.
ii ACKNOWLEDGEMENTS
While it is not possible to mention everyone deserving of thanks, I at least would like to express my appreciation to those without whose efforts the project would not have been possible. I would like to thank my mother and sisters for their love and support, and for teaching me to appreciate words. I am also grateful for the encouragement I have received from Carol Ventresca, Rick
Cooper, Phil Rack, and a number of other friends and colleagues who have helped sustain me through the entire doctoral process. The dissertation greatly benefitted from the efforts of Daryl Chubin, Harold Goldman, Ed Hackett, Vincent Hernparian, Elizabeth Knoll, Benjamin Pasamanick, Drummond Rennie, Patricia Woolf, and Harriet Zuckerman, each of whom read and critiqued early versions of the questionnaire, offering numerous insightful comments and suggestions. Thanks are also due to Debbie Edwards and
Debbie Potter for help in data cleaning and analysis.
iii Never «ill I be able to repay the debt I feel toward my dissertation committee members. My committee chair, Simon Dlnltz, has been more Indulgent than should be expected of any mentor. Where most advisers would
have been put off by the obsessions and digressions of
an aging, part-time graduate student. Dr. Dlnltz offered unwavering support, tempering his advisee's Intellectual and emotional extremes with his own wisdom and humanity. Joe Scott, my teacher and friend of many years. Is surely the busiest man I know. Nevertheless, he has always made time for me and has given the best of advice. And Dr. Schwirian, my favorite statistics professor. Instilled In me long ago an appreciation of
statistical Issues. For everything these men have done I am truly grateful.
Married graduate students do a terrible disservice
to their families. Throughout what must have seemed an Interminable process, my wife Jan tolerated my moods and absences, supported me through disappointments, shared
In the triumphs, and threatened me when I came close to chucking It all. The diploma Is at least half hers. To my daughters Heather and Stephanie, for your unqualified
support and understanding of my neglect, I promise I will try to somehow make It up to you.
Iv VITA
1974...... B.A., The Ohio State University 1975-1976...... Parole Officer, Adult Parole Authority, Gallon, Ohio 1977-1980...... Probation Officer, Franklin County Municipal Court, Columbus, Ohio
1980...... M.A., The Ohio State University 1981-198 2 ...... Teaching Associate and Lecturer, Department of Sociology, The Ohio State University, Columbus, Ohio
1982-Presen t .... Researcher, Governor's Office of Criminal Justice Services, Columbus, Ohio
FIELDS OF STUDY
Major Field: Sociology Studies In Criminology, Methodology and Statistics, and Social Psychology TABLE OF CONTENTS
DEDICATION...... 11 ACKNOWLEDGEMENTS...... 111-lv
VITA...... V LIST OF TABLES...... vlll-lx
Chapter I. INTRODUCTION...... 1 Statement of the Problem...... 1 Importance of the Problem...... 2 Examples of Scientific Deviance...... 4 Focus of the Present Study...... 10
II. DEVIANCE AND SOCIAL CONTROL IN ACADEMIC SCIENCE...... 12. The Cognitive Norms of Science...... 13 The Moral Norms of Science...... 15 Ethical Standards In Academic Science.... 19 The Boundaries of Scientific Deviance....22 III. SCIENTIFIC MISCONDUCT AS WHITE-COLLAR CRIME..26
White-Collar Crime as Violation of Trust...... 28 The Unit of Analysis In White-Collar Crime Studies...... 31 Scientific Misconduct as Violation of Trust...... 33
vl IV. METHODOLOGY...... 34. The Measurement of Seriousness...... 35 Magnitude Estimation v. Category Technique ...... 37 The Sample...... 40 Development of the Survey Instrument..... 43 Administration of the Survey...... 45 V. THE PERCEIVED SERIOUSNESS OF ETHICAL MISCONDUCT...... 49 Prior Work on the Seriousness of Scientific Misconduct...... 49 Seriousness in the Present Study...... 50 The Dimensions of Scientific Misconduct..57 The Explanation of Seriousness...... 63 VI. THE PERCEIVED INCIDENCE OF ETHICAL MISCONDUCT...... 67 Deviance in Science; How Much?...... 67 VII. DISCUSSION AND IMPLICATIONS...... 60 Major Findings...... 80 Suggestions for Future Study...... 62 Theoretical Implications...... 63 Policy Implications...... 67 APPENDICES...... 90 A. Survey Instrument...... 90 B. Supplemental Enclosure...... 95 C. Characteristics of the Six Samples...... 97
D. Geomeans for the Six Samples...... 104
LIST OF REFERENCES...... 117
vii LIST OF TABLES
Table Page 1. Return Rates for Each of the Six Samples...... 46 2. Sociodemographic and Professional Characteristics of the Combined Samples .48
3. Rank-Ordered Seriousness Ratings of Combined Sample...... 53
4. Matrix of Rho Values for Six Disciplines 57 5. Factor Loadings for Vignette Variables...... 59
6. Stepwise Regression Summary for Misrepresentation Factor...... 64 7. Stepwise Regression Summary for Propriety Factor...... 65
a. Perceptions of How Often Scientists and Scholars Steal the Work of Their Colleagues..69 9. Perceptions of Whether Respondents' Own Work Has Been Stolen or Plagiarized: By Gender.... 71 10. Perceived Plagiarism by Productivity Level...72
11. Perceived Plagiarism by Professorial Rank....72 12. Have You Personally Known Someone Who Has Fabricated Data and Passed Them Off as Legitmate Data?...... 74
viii 13. Scientists Reporting that Ideas They Shared Had Eesïî Used without Their Permission by Gender...... 76 14. Have You Ever Received Less Authorship Credit than You Believe You Actually Deserved?..... 77
Ix CHAPTER I
INTRODUCTION
Statement of the Problem
Science, one of the last bastions in modern society to come under attack, has been suffering a seige of
accusations that some of its members are engaging in unethical practices. In some cases these accusations have proven true, resulting in the resignation of scientists, the revocation of degrees, the retraction of
published papers, and the waste of research monies. For some time now journalists (Culliton, 1974;
Broad, 1981a, 1981b, 1981c; Budiansky, 1985; Wheeler, 1988) have reported occasionally on such misdeeds, but it has been only relatively recently that scientists
themselves (Petersdorf, 1986; Braunwald, 1987) and
governmental entities such as the National Institutes of Health and the U.S. Congress (Holden, 1988) have shown a willingness to frankly discuss the problem of fraud in science and its implications. Because the formal Interest in scientific misconduct is of recent vintage, there are few empirical studies on the causes, incidence, prevalence, and seriousness of these acts. Much of the available data are either case studies, anecdotal in nature, or are methodologically limited. The purpose of the this research project, therefore, is to help address this void.
Importance of the Problem
The notion that scientists might behave unethically is especially disconcerting because it shakes some time-honored and firmly-held beliefs. First, any kind of dishonesty is antithetical to science's raison d'etre
-- the search for truth. Over a long evolutionary course, the scientific method was developed to ensure that falsities would be discarded and verities retained. Second, it was always thought that the scientific community was self-policing (Merton, 1962:473). That
is, both scientists and those who have studied them
believed that the structure of the scientific enterprise
is such that fraud, charlatanry, and other forms of
dishonesty would easily be ferreted out. And third, it has been popularly held that these ethical breaches were
negligible. As a president of the National Academy of Sciences put It, "...the fraud issue la grossly exaggerated.* (Broad, 1981a). Just as persuasive, however. Is another prominent scientist's contention that "those of us in the biological sciences know that [the reported] cases are but the tip of the Iceberg
(Borek, 1975)." Several commentators have lamented the dearth of empirical studies of ethical misconduct In science. In a comprehensive essay on deviance In the scientific community, Harriet Zuckerman (1977) noted the paucity of both theoretical and empirical work on the subject. Not only did she acknowledge that sociologists know little of the Incidence and prevalence of scientific misconduct, she also admitted that prevailing theories of deviant behavior seem Inadequate to explain these serious departures from scientific norms. One social scientist who participated In an ethics workshop
sponsored by the American Association for the
Advancement of Science (AAAS) found It difficult to
believe that the scientific community would try to wage a war against Its ethical problems without first having
studied them. He writes: "... I am dismayed — although I suppose a social scientist should never be -- at what a tremendously small empirical base we have to start with In trying to understand how widespread fiscal misuse and.dbuse of human subjects are In the research community. We deal in a handful of anecdotes. If we like to think that research has something to say, why don't we do research using samples of survey work and other techniques in order to establish how widespread these problems are and what their contours are? I have a terrible sense that we are blind people feeling the elephants here, trying to make wise policy without understanding how widespread these problems are and so forth. And for God's sake, let somebody fund some empirical research to try to understand what is going on out there. It could be drawn from knowledgeable people. It could be done in various ways that would get us a lot further (Westin, 1981). More recently, Ben-Yehuda (1985*168) noted that although deviance in science "is a most fascinating subject for scientific inquiry, it is also the one that has been poorly researched to date.” Further, he asserts that "Ct]here are virtually no systematic scientific studies of deviance in science. Nor is there a systematic study of deviant scientists as a category"
(1985:197).
Examples of Scientific Deviance
The history of science offers a number of well- documented cases of dishonesty, but the example perhaps beat known in the behavioral sciences is that of the British psychologist, Cyril Lodowic Burt. Burt was a student of Oswald Kulpe and, as such, had the opportunity to figure prominently in the early development of experimental psychology. Early in hla career he began to focus on the measurement of human intelligence. Burt made history in the study of twine to test the inheritability of intelligence. Curiously, he also emerged as a prominent figure in early research on juvenile delinquency. His work was thought to be so important, his influence so profound, that he became the first psychologist to be knighted for his services (Broad and Wade, 1982). While there may be insufficient justification to question the entire body of Burt's scientific contributions, there is compelling evidence to suggest that he falsified the data on twins during the last thirty years of his career. Those who have studied Burt's published findings, including D. D. Dorfman
(1978) and Leon Kamln (Wade, 1976), discovered that for
each subsequent set of subjects, the statistical analyses yielded identical correlation coefficients. This, in short, amounts to a mathematical impossibility. An examination of Burt's personal notes by psychologist Leslie Hearnshaw (Broad and Wade, 1982) confirmed the suspicion that he had indeed fabricated the data. Analysts concluded that Burt so fervently believed his hypotheses were right that he no longer felt a need to observe the canons of scientific research. As Berkeley biologist Arthur Jensen benevolently put it, "It is almost am if Burt regarded the actual data as merely an incidental backdrop for the illustration of the theoretical issues” (Panati with McPherson, 1976). He
apparently concocted Imaginary data so his work could take on the trappings of publishable research and thus
convince his opponents that his ideas on the inheritability of intelligence vere correct (Havkes,
1979). The faking of data is not confined solely to the behavioral sciences. In fact, most of the cases that have come to light have taken place in biomedical research. One of the most infamous of these cases occurred in the field of cancer research. The protagonist, William Summerlin, vas a medical researcher
working at the world famous Memorial Sloan-Kettering Cancer Center in New York City. He was relatively young and had the opportunity to make a name for himself. He
specifically was interested in the possibility of culture-grown skin losing its rejection properties. The
implications of success in such a line of research
included the possibility of being able to transplant organs between genetically different individuals Summerlin was exposed. The case of oncologist Hare Strauss was aired in U.S. Senate committee hearings. Strauss, who had been affiliated with Boston University, was the principal investigator of a research team pursuing a project funded by the National Cancer Institute (NCI). When it was learned that the data were fraudulent, the research team, which was part of the larger Eastern Cooperative Oncology Group, was disbanded and their data were purged. Despite the fact they were notified at the time the fraud was uncovered, the NCI took its time investigating the matter. In the meantime, Strauss was awarded a $1.3 million grant for another project. The NCI was taken to task by several senators who considered it ludicrous to award new monies to someone who allegedly was involved in scientific fraud. Perhaps the most controversial case of scientific fraud to date is that of biomedical researcher John Darsee who, during his research stints at Emory and Harvard Universities, falsified data involving over 100 published papers and abstracts. Once suspected by his superiors at Harvard of having falsified cardiac experiments on dogs, Darsee vas placed under surveillance. Witnesses sav him label data collected in a period of a fev hours so it vould appear it had been collected over a period of tvo weeks (Culliton, 1983b). Further investigation revealed that he had perpetrated similar acts at Emory, and that his published papers were full of errors and misrepresentations. Harvard University drew much oriticien for its handling of the Darsee affair. When Darsee first was suspected of misconduct in the laboratory, his superiors began conducting their own investigation. They failed, however, to immediately notify the National Institutes of Health, the sponsor of the research in which Darsee was involved (Culliton, 1983). The university and Darsee's lab chief, Eugene Braunwald, were taken to task for "lax supervision and poor recordkeeping," among other mistakes (Roberts, 1983). But Darsee'8 fraud and the feet-dragging by Harvard were not the only controversial aspects of the case. Tvo seientiats vlth the National Znatitutea of Health, Walter Stewart and Ned Feder <1987), conducted an in-depth examination of the papera co-authored by Darsee and his colleagues at both Eeory and Harvard. They concluded that the published studies vere fraught with errors and inconsistencies, many of which should easily have been caught by Darsee's co-authors. When these tvo self-appointed fraud investigators tried to publish their findings they vere net with reluctance and hostility. Some of Darsee's former collaborators even threatened them with legal action (Boffey, 1986). Such reluctance suggests that the scientific community is not yet ready to accept with open arms the implication of widespread misconduct among its members. Of more recent vintage is the case of Stephen Breuning. Breuning, s former assistant professor of child psychiatry at the University of Pittsburgh, was charged by his former supervisor with having falsified psychopharmacological data on a number of mentally retarded children, a study supported by the National Institute of Mental Health. What makes this case uniquely insidious is the fact that many children may have been treated based on Bruening's falsified results (Wheeler, 1987). lO There are a number of other well-known oases In what Broad (1982) has referred to as the "scientific hall of shame." Anecdotes and case studies alone, however, fail to yield sufficient information on the contours of deviant behavior in science. Focus of the Present Study. This study is an attempt to assess the perceived seriousness of some of the forms of scientific misconduct. More specifically, how do those who supposedly subscribe to the norms of science feel about transgressions of those norms? How serious, for example, do they deem plagiarism? The falsification of data? Is it perhaps possible that acme of these behaviors are in fact condoned while others ere expressly proscribed? Applying techniques used by criminologists (Sellin and Wolfgang, 1964; Bridges and Lisagor, 1975; Evans, 1981) in assessing the seriousness of more traditional crime, this study measures the seriousness of scientific misconduct as perceived by a number of academic scientists. A second component of the study is an assessment of the perceived incidence of ethical misconduct. In this study, respondents report their experiences as victims 11 of unethical aoientlfic practices. They are also asked to report the extent to which they know of such misconduct by others. Like seriousness scaling, surveys of alleged victias have been used by criminologists interested in more traditional crime, but who were disoatisfied with the existing measures of incidence and prevalence. Victimization-type surveys offer the promise of yielding data on the nature and incidence of misconduct, especially where other sources of data are either unreliable or altogether nonexistent. This study is an attempt to answer some fundamental questions about scientific misconduct. It is an effort to apply current research methodologies to a relatively unexplored area of social deviance. Hopefully this study will not only answer some basic questions about the contours of acientifio deviance, but also stimulate further theoretical and empirical interest in the topic. CHAPTER II DEVIANCE AND SOCIAL CONTROL IN ACADEMIC SCIENCE Deviano*, »oi*ntific or otherwise, involves departures from noras (Zuokersan, 1977). By definition, then, deviance in science must involve a departure from the noras of science and not the noras of society in general. Harriet Zuckeraan <1977:113) makes the distinction like this: EScientific deviance) refers to those deviant acts people commit in their capacity as scientists, not the acts which some commit in the other statuses they happen to occupy: such as child abuse by scientist-pmrents, tea evasion by scientist-citlzens, or religious heresy by scientist-churoh members. Sexual exploitation is an example which illustrates the difference between general and scientific norms. In the worlds of business and government there are instances wherein individuals occupying positions of authority use their power to exact sexual favors from subordinates. This undoubtedly also occurs in the world of academic science. Consequently, sexual exploitation is not a problem peculiar to the milieu of academic 12 13 eoiemo* because it also occurs in business, governnent, and other settings. In this instance, sexual exploitation violates more general norms in a scientific setting. The question then becomest what precisely are the norms of academic science? The Cognitive Worms of Science In her comprehensive essay on deviant behavior and social control in science, Harriet Zuckerman <1977) discussed the role of cognitive norms. Cognitive norms can best be thought of as those rules which dictate the method of scientific work. In the the social sciences, for example, there are norms which govern how an experiment is to be conducted or how a survey sample is to be drawn. If the scientist departs from these norms either out of neglect or willful disregard, he or she thereby violates accepted methodological canons and as a consequence, risks suffering the disapproval of fellow social scientists for having done so. Yet another example might prove instructive. In the course of writing scholarly tretises, social scientists know that they should not only be familiar with the works of predecessors, but should elso acknowledge their intellectual debt by way of references, footnotes, or endnotes. The failure to do 14 so violates one of science's cognitive norms. The inadvertent form of this offense, citation amnesia, is perhaps common and even understandable (Garfield, 1981). The socialization process of scientists, however, emphasizes giving credit to all those who previously have written on the subject and whose work should have influenced the one in question. But even this practice can be taken to an extreme (Form, 1988). The proper allocation of credit is not a problem solely with regard to citation practices. In the scientific world, it is common practice for authors to have informed colleagues read their manuscripts prior to submitting them for publication. The investment made by these fellow scientists can range from giving the paper a cursory glance to an in-depth analysis, editing, and perhaps even some re-writing. Cognitive norms dictate that when the contribution is small, at least a mention of appreciation is due. But when the investment and contribution of the colleague is great, the credit due may more properly amount to co-authorship. In an effort to properly allocate credit, though, the scientist needs to be careful not to extend authorship to those who do not deserve it. It was discovered that data falsifier John Darsee had insisted upon giving co-authorship to 1 5 colleague* vho did not even feel their contribution* warranted it (Culllton, 1983). It la at thla point where the distinction between cognitive and moral norma becomes somewhat blurred. Moral noras suggest canons of behavior that Involve trust and openness rather than knowledge. When two scientist* co-author a manuscript and one of them takes entire credit for the effort, the Incident may rightly be termed plagiarism. But some Instances of this kind may not differ vastly from the case detailed above wherein a colleague reviewer falls to receive proper credit for the investment made during the review. Despite the existence of this grey area between science's cognitive and moral norms, there are a nuober of behaviors which are generally regarded mm morally offensive to science. The Moral Norms of Science Merton <1973) Identified four moral norms which are said to prevail over the conduct of scientific Inquiryt universalisa, disinterestedness, organized skepticism, and communism or communallty. The first, universalise, suggests that the claims of scientists be judged apart from the personalities 16 making the cimime. Aacorking to Stormr (1966), hov physical laws oper&ts in on* continent is the same way they operate in another. Moreover, he asserts, scientists should not reject the work of a colleague based on political differences. Ben-Yehudm <198Stl71> points out that this is often difficult when theories become linked with certain scientific personalities. The aftermath of the Cyril Burt affair is a case in point. Because of the psychologist's eminence and the perceived importance of his contributions, it was difficult, if not impossible, for many to accept that he had, indeed, falsified his data. Supporters, including Harvard hereditarian Richard Herrnstein, initially lashed out at the accusers who dared to defile Sir Cyril's name (Wade, 1976). In the end, however, those suspicious of Burt's work were vindicated, but the incident demonstrates how scientists are sometimes guilty of ascribing value and integrity to work which does not deserve it. Disinterestedness, another of Merton's moral norma, addresses the need for scientists to keep personal interest out of the process. Having some kind of stake in the outcome of research necessarily taints the results and the motives behind those results. This universal objectivity of which Merton speaks keeps 17 flclentlBts fro* being Misguided by financial greed, the desire for recognition, and other such psychological and suspect Motivations. Ben-Yehuda <1985*174) argues that this nora is unrealistic because of science's estees vithin society; recognition, wealth, and power are all well within the grasp of the contesporary scientist, especially those who can popularize their subject. Merton's third Moral nora, organized skepticisa, conveys the notion that scientists put to rigorous test the claias of other scientists. According to Storer (1968) this nora implies an obligation to ensure the validly of all previous work upon which the study in question is based. But criticizing the work of others, suggests Ben-Yehuda (1985*172), can be downright imprudent, especially when the criticized scientist is acre powerful than the critic. It has been suggested that soae scientists use this nora as an excuse to level attacks at others whose work and views are at odds with their own. Ben-Yehuda (1985*172) cites the example of journal referees who, despite their normative obligation to offer constructive critique, often use that role to attack new or otherwise unpopular ideas. The falsification of data, considered by soae to be sciences'* aost serious offense, violates the noras of 18 dlalnt«r«atcdncaa and communia* (Zuckarman, 1977*117). Falmifiomtion, forging, end faking are all terms used to describe instances wherein the scientist does not collect bona fide data but instead simply makes it up. The reason falsification is deemed so reprehensible is that it not only violates the norm of disinterestedness, it also threatens to weaken that most important bond between scientistsi trust. Scientists take for granted that the empirical groundwork laid by their intellectual forebears is reliable. Otherwise, they would have to verify all previous work before proceeding with their own (Zuckerman, 1977*113), a quite impractical prospect. Communism, or commonality as Barber (1952*130) prefers, is Merton's fourth norm. The norm implies that the work of scientists is not really their sole property. That is, engaging in scientific work carries an implicit obligation to communicate findings to fellow scientists. Secrecy, therefore, according to Barber (1952*130) is "an immoral cot." It is only in making a finding public, then, that one can lay claim to it. It should be remembered, however, that good ideas are at a premium in the world of science. Cases of plagiarism (Broad and Wade, 1982*38-56) and the theft of unpublished ideas (Ben-Yehuda, 1985*188) are not unusual. The scientist who shares an idea with an 1 9 unsorupulous colleague ray later see that idea in the for* of a published study under tha colleague's nara. For that reason, many in the scientific community may be reluctant to air an idea before they have an absolute guarantee of credit for its discovery. There is not, however, universal agreement on Merton's moral norms. Schmause (1983), for example, argues that scientists are bound not to norms peculiar to science, but to more general moral norms which require everyone to do his or her duty. Using a similar line of reasoning. Sham (1982) suggested that like manners, plagiarism should be left to society in general to enforce. Zuckerman (1984), has eubssquently taken Scheauss to task for suggesting a norm of such generality. This difference of opinion on the dimensionality of science's normative structure has particular relevance not only in theorizing on deviant behavior in science, but also in undertaking concrete empirical morte. Ethical Standards in Academic Science Despite their origin or dimensionality, the norms by which scientists are expected to work have become manifest in the form of written ethical standards. 2 0 Several of the professional societies to which academic scientists belong have been concerned with the problem of ethical misconduct and, as a result, have promulgated explicit standards of ethical conduct for their members. The American Institute of Nutrition, a constituent society of the Federation of American Societies for Experimental Biology The source of trustworthy scientific knowledge is conscientious, careful research. The responsible nutrition scientist carries out in an honest and ethical manner the collection, interpretation, and reporting of experimental data. No question or doubt should be possible as to whether or not, in the presentation or publication of research results, the ethical investigator has distinguished clearly his/her own data and their interpretation from those of other workers cited. Valid data or results must be reported, regardless of prior or initial bias, hypotheses, or experimental protocol. Both The American Psychological Association and The American Sociological Association (ASA) have developed and published rather detailed ethical standards which govern research and publication activities. From the ASA'S Code of Ethics* A. Objectivity and Integrity Sociologists should strive to maintain objectivity and integrity in the conduct of sociological and research practice. 21 1. Sociologist* should adhere to the highest possible technical standards in their research. When findings say have direct implications for public p o l i c y or for the well-being of subjects, research should not be undertaken unless the requisite skills and resources are available to accomplish the research adequately. 2. Since individual sociologists vary in their research modes, skills and experience, sociologists should always set forth ex ante the disciplinary and personal limitations that condition whether or not a research project can be successfully completed and condition the validity of findings. 3. Regardless of work settings, sociologists are obligated to report findings fully and without omission of significant data. Sociologists should also disclose details of their theories, methods, and research designs that might bear upon interpretation of research findings. "There is no universal acceptance in the academic profession of any explicit statement analogous to the Hippocratic oath," wrote Logan Wilson (1942), "and for many members there is merely a vague understanding of those ideals or norms of conduct that overreach the satisfaction of individual desires.” So while it is clear that some scientific associations have recognized the need to publish and enforce formal standards of ethical behavior for their ammbera, othor associations have not. The American Society for Biochemimtry and Molecular Biology, a constituent member of FASEB, currently has no code of ethics for its members. Perhaps this is because the members subscribe to the 2 2 "bad appla* th«$ory of eclontlfla alaoonduot. It perhapa could ba argued that soae solentista hold suoh a vie*, not beoauae they deea aoadeaic aclence aanoroaanot, but beoauae the available evidence doea not neceaaarily auggeat a prevalent problea. The Boundariea of Scientific Deviance Despite journalistic treataenta end a fe* iapreaaiona by acientlata theaaelvea, there la little known about the incidence and prevalence of deviance vithin the scientific community. But those vho vrite on the subject seea to fall into one of tvo caapat the "bad apple" caap or the "tip of the iceberg" camp includes such notables as sociologist of science Robert K. Merton (1962:470)> and foraer AAAS president Philip Handler (Svazey and Sober, 1981:190), aaintains that the nuaber of offenders in science is quite small in comparison to the total nuaber of men and voaen engaged in the scientific enterprise. Conversely, the latter group argues that the "bad apple" caap bases its contention solely on an impression grounded in a relatively infrequent nuaber of knovn incidents, vhich are likely to be a small percentage of the actual cases. 2 3 The truth le that there ere few empirical etudles from which the analyst of either persuasion can draw definitive conclusions^ The published studies which might have shed light on scientific deviance unfortunately are methodologically weak to #uch an extent that they are of limited value. Mahoney and Klmper <1976), for example, sent a questionnaire to a random sample of 400 physicists, biologists, psychologists, and sociologists. Their Intent was to examine patterns of conduct in scientific research, including professional ethics. The instrument included items designed to assena respondents* knowledge of deviance and their estimates of deviance by others within their respective disciplines. Eighty-two questionnaires were returned, 77 of which were usable. Although over 40 percent of the respondents were aware of at least one instance of data fabrication in their own field, the sample rated it as a rare occurrence. The authors issued caveats about the generalizability of their findings, but indicated their work served as a tentative sketch of the problem. Another study to which most analysts (Zuckerman, 1977I Ben-Yehuda, 1985) refer is the one reported by St. James-Roberts (1976) in the publication New Scientist. The magazine's subscribers were asked to complete a 2 4 questionnaire designed to measure the extent o£ intentional fraud in the biosedical sciences. Of the respondents, 92% indicated they had personal knowledge of fraud by others. But the author used a self-selected sample of readers, inviting the criticism that the respondents very well may not have been representative of scientists in general. More recently, June Price Tangney (1987) distributed a questionnaire to scientists at a major university "in an effort to begin to address these issues more systematically. * Of the 1,100 questionnaires distributed, 245 were returned, yielding a return rate of 22.3%. With regard to the seriousness of scientific misconduct, the majority of Tangney's respondents deemed the falsification of data and plagiarism as very serious offenses. She further notes that respondents did not vary by discipline on their assessment of the seriousness of falsification (Price, 1985). Concerning the respondents' own experience with scientific misconduct, 32% had at one time or another suspected s colleague in their field of falsifying data. Zuckerman (1984) noted that tho subject of deviance in science is still under-studied. Ben-Yehuda (1985*188) admits that "while the field Cof scientific 2 5 deviano*] la a moat faaoinating aubjeot for aciemtifio inquiry, it ia alao ona that haa baan poorly raaaarohad to data." As raoant aa 1986, two racognizad axparta on aoiantific niaoonduct notad that "...thara ara virtually no data on a aubjact obvioualy of graat interaat and aooial iaportmnoa" (Stawart and Fadar, 1986). "Reliance on unsubstantiated aaauaptiona," writes Nicholas Stenack (1984:12), "sight be acceptable if it were impossible to gather data on the state of research ethics in the practice of science." Ha goao on to argue that "Until wa address openly these and other vital questions about research ethics, we will not know the extent to which scientific research in general can be said to be ethical." While some of the more recant work helps to fill this empirical void, it is clear there is room for studies such as the one reported herein. CHAPTER III SCIENTIFIC FRAUD AS WHITE-COLLAR CRIME Behaviors now clamaifiad as white-collar crimes were not always regarded as such. Take, for example, the anti-trust cases which Sutherland (1949) analyzed. Typically such cases were handled administratively or civilly and, as such, were not punishable by terms of confinement. The dispositions of the heavy electrical equipment conspiracy cases of 1961 were novel, then, in that some of the defendants were sentenced to jail terms. This was particularly newsworthy at the time because the defendants were some of the most upstanding citizens in their communities. It was clear that even the defendants did not regard themselves as criminals (Geis, 1967). Recently, though, there seems to be evidence of the same evolutionary push to regard scientific fraud as criminal. Stephen Breuning, the wiental retardation expert who was found to have falsified data under a federal grant, recently pleaded guilty to federal 2 6 2 7 chargea of fraud. He vas aubaequently aentenced to serve a jail term, the firat auch sentence for falsifying data. By conventional standards the punishment vas light; however, it illustrates the way in which scientific misconduct has moved from purely a matter of ethics to the province of the criminal law. Aside from the fact that some forms of scientific misconduct are indeed illegal, there are yet other reasons for linking it to more traditional forms of white-collar crime. The scientist, like his counterparts in business and government, is intelligent and well-educated. And although the contemporary academic scientist may not reap the financial rewards associated with Wall Street, he enjoys a considerable amount of prestige. Even the white lab coat of the scientist — a symbol of cleanliness and purity — parallels the white collar of businessman. In an effort to place the behaviors under study in their appropriate criminological context, this chapter will discuss some of the major works on white-collar crime. Perhaps, then, through an examination of the theoretical and conceptual development of white-collar crime, will the rationale for the present study be made clear. 2 8 White-Collar Crime «a Violation of Truat Edwin H. Sutherland formally introduced the concept of white-collar crime in his 1939 presidential address to the American Sociological Society. In that address, Sutherland <1940) made it clear to his audience that theorizing about "feeblemindedness, psychopathic deviations, slum neighborhoods,* and the like would not explain the criminal behavior of business end professional men. Sutherland, who also was the progenitor of a criminological theory known as differential association, hoped to explain white-collar crime with the aeme perspective. It was his contention that the processes which accounted for the transmission of street crime worked the same for white-collar crime. In his now famous address, Sutherland asserted that all white-collar crimes in business and the professions had one factor in common; the violation of delegated or implied trust. Many of these violations, he asserted, could be categorized as; (1> misrepresentation of asset values and (2) duplicity in the manipulation of power. Sutherland's forms of trust violation may have their counterparts in the world of academic science. The faking of data, for example, is a misrepresentation 2 9 of both the aoienttst's actual investment and the worth of the product. And duplicity la exemplified by the profeaaor vho encouragea a student to vrite a paper the former intends to publish as his ovn. One of Sutherland's former students, Marshall Clinard, had an opportunity to observe the inner workings of wartime black market activities. Clinard <1946) concluded that differential association fell short in explaining what he had observed. He noted, for example, that many of the people who would have been intimately acquainted with the methods of violation refrained from violating. Further, he observed that the techniques for violating were accessable to virtually anyone because of their simplicity. Not long after World War II, sociologist Donald Cressey <1953>, yet anther of Sutherland's proteges, conducted a fascinating study of businessmen who had embezzled other people's money. Using a method he referred to as analytic induction, Cressey began studying cases in order to test his hypotheses. When he encountered a case which did not fit into his theoretical scheme, he broadened his theory to include it. Cressey identified what he termed the non-shsrecble problem in trust violation. One suoh 3 0 problem he uncovered van that resulting from strained employer-employes relations. Here the employee might feel he or she has been treated unfairly in some way by the organization. The problem ia non-shareable in that should the individuals suffering the problem suggest ways to alleviate the unfairness, they may lose status within the organization. But regardless of the original motivation for embezzling, Cressey*s subjects engaged in violations of trust. Herbert Edelhertz <1970), a recognized authority.on white-collar crime, offered the following classification of these offenses. _ ^ ^ » —— - , <1) Crime by persons operating on an individual, ad hoc basis, for personal gain in a non-business context (hereinafter referred to as "personal crimes">. (2) Crimes in the course of their occupations by those operating inside businesses. Government, or other establishments, or in a professional capacity, in violation of their duty of loyalty and fidelity to employer or client (hereinafter referred to as "abuses of trust"). 31 Of the tvo categories offered by Edelhertz, the second vould seem to apply to ethical misconduct in science. One could argue that the duty of loyalty of the academic scientist is not soley to his or her employer, but to science in general, and to his or her discipline in particular. In the same monograph, Edelhertz (1970) listed several categories of vhite-collar crime, each with a detailed list of offense examples. Interestingly enough, though, falsification or fraud by scientists was not an element in Edelhertz's schema. Because of the comprehensiveness of the list, the omission probably reflects a general reluctance at the time to consider science as criminogenic. Perhaps future such classificatory schemes will include whet might be termed Glab-coat crime." The Unit of Analysis in White-Collar Crime Studies Despite the fact that Sutherland's unit of analysis was the corporation, his interest vas in individual offenders. That is, he was not so much interested in the corporations as criminal entities as he was in the criminal milieu they provided for individuals, and the way the criminal mindset and technique were transmitted. 32 Consequently, Sutherland's vork can be vieeed social psychological as opposed to structural In approach. A number of criminologists (Ermann and Lundman, 1983, Schrager and Short, 1978), however, have chosen to focus on the organization as their unit of analysis In studying certain types of white-collar crime. Many turn to the concept of the juristic person But Is there any evidence to suggest that such a focus Is warranted In the study of deviance In academic science? In those publicized cases discussed In Chapter I wherein wrongdoing was substantiated, there la no evidence that the offender worked In collusion with other falsifiers of data. Moreover, whereas large corporations have profit as an Incentive for encouraging deviant methods In the production of goods and services, universities, as the potential entitles under study, have major disincentives for doing so. As noted in Chapter II, Individuals found guilty of ethical misconduct generally are forced to leave careers In research altogether. But the Institution, as well as the Individual, may be barred from applying for, or receiving, future research funds (Broad, 1981b). It also could be argued that the publicity which surrounds 3 3 an incident of scientific fraud is damaging to the reputation of the institution involved, as veil as to that of the individual offender. Therefore, unlike many kinds of corporate and organizational deviance, ethical misconduct seems to be antithetical to the organizational milieu in which it sometimes occurs. Consequently, criminologists should not attribute to organizations behavior vhich may veil be that of individuals. Scientific Misconduct as Violations of Trust Despite the different foci of the major analysts of vhite-collar crime, they have yet to shed the notion or importance of trust. From the Sutherland's early inquiries into vhite-collar crime up to the present one, the notion of trust has surfaced again and again as a definitional and conceptual tool. Regardless of motive or structural pressure, vhite-collar offenders have betrayed one form of implied trust or another in the discharge of their duties. "The continued existence of a society of any worthwhile kind," writes John Kleinig, "will depend on the general maintenance of a fair measure of trust between its members. Trust is perhaps the Kost important ingredient in social glue*" (Kleinig, 3 4 1982). It la the dissolution of that social glue in academic science vhich has universities, federal agencies, and scholarly societies so concerned. It is to the detriment of academic science for either individuals or groups to purposefully violate this trust. Unlike the large corporation that stands to gain enormous profits vhen it cuts corners, the institution of science vould collapse if its members engaged in large scale misconduct. Despite Zuckerman's (1984) contention that focusing on a single societal norm can be a "regressive theoretical step," the notion of trust may indeed be useful not only in the study of vhite-collar crime, but perhaps even in other forms of deviance. Just as fractions are reduced to their lovest common denominator, perhaps criminologists should consider homing in on specific, fundamental norms such as trust vhich tie together both deviant and conventional behavior. It is the realization that trust in academic science is occasionally betrayed that should prompt criminologists to rethink the norms of science vith a viev tovard a fresh, more realistic theory. CHAPTER IV METHODOLOGY The Measurement of Seriowsneae Sociologists Thorsten Sellln and Marvin E. Wolfgang <1964) vere dissatisfied vlth the FBI's Uniform Crime Report (UCR> as the official measure of crime In the United States. In particular, they sought a method which would enable analysts to add disparate offenses and numbers of offenses, thereby yielding a composite measure of both aggregate and Individual criminality. Am a result, they proposed to assess how serious people deem various criminal offenses. Their study tested two methods of offense seriousness scalingi the magnitude estimation method and the category method. In the first of these two methods, the raters are presented with a series of vignettes, each of wh.'oh describes a criminal offense. They are alao presented with i modulus, or standard act whose seriousness score Is already given. The raters then 35 36 asoign a positive number to eaoh of the acts which represents how many times more serious they deem the acts in relation to the standard act. The method yields ratio-level data since there is an absolute zero point and equal intervals between the units of measurement. In the category method, the raters are also presented with a series of vignettes. But instead of assessing the seriousness in relationship to the other acts, the raters choose from a rank-ordered list of numbers or penalties the one they feel would be appropriate to punish the described behavior. The seriousness of the penalties are ranked in advance either by the same raters or by a separate group of judges. The Sellin-Wolfgang project spawned a number of studies which applied the methods of seriousness scaling to other populations both national and international, tested many of the original assumptions, and analyzed various methodological issues. Some of these employed different groups to judge perceived seriousness, including inmates and correctional staff (Secrest, 1969), randomly selected adults (McCleary, O'Neil, Epperlein, Jones, end Gray, 1981). 37 Others (Hsu, 1973; Al-Thakeb and Scott, 1981; Evans, 1981) have focused on cross-cultural differences and similarities. Schrager and Short (1980) and Cullen, Link, and Polanzi (1982) analyzed attitudes toward white-collar crime. And the statistical and methodological issues have been given considerable attention in these replications. These include the additivity (Pease, Ireson, and Thorpe, 1974; Wagner and Pease, 1978; Gottfredson, Young, and Laufer, 1980) end the effect of item order (Evans, 1981). These numerous studies attest to the popularity of seriousness scaling in criminological inquiry as well as to the extent to which it has been refined. Magnitude Estimation v. Category Technique Sellin and Wolfgang (1964) argued that magnitude estimation is preferable because the subject and not the experimenter determines the scale values. Moreover, they maintained that because of the breadth of range offered by the magnitude scales, they provide "intrinsically more information" about the raters' judgments. For these reasons, Sellin and Wolfgang concluded that magnitude scaling is the better of the two methods. 38 In his replication of Sellin and Wolfgang's work, Figlio <1975) noted that the category technique is easy for raters to visualize and to understand. However, it is also numerically constraining. The magnitude technique, according to Figlio, has no such constraint but requires more abstract thinking. Each, then, has its own advantages and disadvantages. Bridges and Liaagor (1975) specifically sought to evaluate the two approaches and the relationship between the scales produced by them. They discovered that the two methods do indeed produce quite similar results and confirmed the logarthmio relationship as discussed by Shinn <1974). Consequently, they concluded that since the final product is the same regardless of approach, investigators should adopt the method which is best suited to a particular research need. Evans (1981) compared the two types of scaling techniques in her cross-cultural study of crime seriousness. She concluded that although the two yield similar results, the category technique is better for two reasons. One, the method requires less thinking and consequently is more easily understood. Second, one does not have to perform the logarithmic transformations necessary with the magnitude technique. 39 For the present study, magnitude estimation was chosen for several reasons. First, as Sellin and Wolfgang <1964) and others have observed, the method gives raters much more latitude in assigning a seriousness score. More importantly, however, in the study of the seriousness of ethical breaches, not enough is yet known about how these behaviors are punished and who metes the punishments out. With conventional crime it is fairly easy to determine the agents of social control end the options available to them for punishing violators. But in academic science there is no single court or tribunal to which accused offenders must answer. The university they work for may investigate and punish their behavior. The scholarly organizations to which they belong can conduct their own inquiries and impose sanctions including termination of membership in the association. And the agency providing financial support for the research in question may impose debarment, which means that the offender may not apply for or receive future funds for a specified period of time. For each of these potential agencies of social control there are innumerable alternatives which would make the compilation and analysis of penalties an impossible task. 40 The only type of category technique that could have been used, then, would have been the Llkert-type as used by Rossi <1974), Cullen et al (1982; 1985) and others. In this method, raters use a response scale of say, "1" to "9," with one end of the scale representing the least serious score, the other end the most serious. It yields ordinal-level data, but places an arbitrary and artificial ceiling on the seriousness of each act, one which may not correspond to how the respondent truly feels about the seriousness of the behavior in question. And finally, with regard to Figlio*s (1975) observation that the magnitude technique requires greater abstract ability, one can argue that academic scientists should be able to think abstractly enough to grasp the concept and method of this approach. The Sample Since the original purpose of the study was to survey academic scientists, it was necessary to determine how these prospective respondents would be identified. It was originally suggested that these subjects would be chosen from the membership rosters of the following scientific societies* 41 The American Physical Society The American Chemical Society The Federation of American Societies for Experimental Biology The American Economic Association The American Sociological Association The American Psychological Association But because many of the members of these societies are not members of the professoriate, that is, scientists mho hold the rank of assistant professor or higher at a college or university, it vas necessary to identify from the membership of these associations only the academic scientists. Membership directories, however, do not always have affiliation and rank of members. Such was the case with the American Physical Society and the American Sociological Association. Some societies, however, publish guides to graduate study which include the names of graduate faculty members. The American Sociological Association publishes just such a guide. This guide highlights all the academic programs in the U. S. which offer graduate degrees. Similar guides were available for four of the six scientific fields under study. For experimental biology and psychology, the general membership 42 directories had to suffice, but each vas then oversampled by choosing approximately tvioe the number chosen for the other four groups. The six directories used for sampling veret 1987-88 Graduate Programs in Physics, Astronomy, and Related Fields (American Institute of Physics) Directory of Graduate Research 1987 (American Chemical Society) Directory of Members (Federation of American Societies for Experimental Biology) Guide to Graduate Study in Economics, Agricultural Economics, and Doctoral Degrees in Business and Administration 1987 Guide to Graduate Departments of Sociology (American Sociological Association) Directory of Members (American Psychological Association) Once the six volumes vere identified and acquired, it vas necessary to select the appropriate number of cases. It had been predetermined that a total of 1500 subjects vould be chosen. This figure vas modified due to the decision to oversample as discussed above. The projected cost dictated the final ceiling more than did any other consideration. First it vas necessary to find the membership total for each association in order to sample proportionately. But then proportionate sampling had to be rejected vhen it vas discovered that the societies in question 43 differed greatly in size. Consequently, using proportionate sampling, the smaller associations would yield an insufficient number of cases for analysis. It vas decided that quota sampling vas necessary to avoid this problem. To calculate the sampling interval for each association, the total number of members in each directory vas estimated by counting the number of members on several representive pages and then dividing that total by the number of pages counted. That figure vas then multiplied by the total number of pages in the directory. Once this vas accomplished, the membership directory total vas divided by the number needed for each respective association, vhich yielded the sampling interval. All that remained vas the determination of a starting point for each directory. This vas done using a table of random numbers from Blalock <1977), a standard statistics text. The names of those chosen vere then entered on a computerized mailing list. Development of the Survey Instrument As originally conceived, the survey instrument vas to have three sections. First and the most important vas a series of vignettes, each of vhich vould describe 44 an act «hloh la potentially deviant. After reviewing the extant literature on ethica and aiaconduct in acience, and after discusaing these issues with a number of academic scientists, it was passible to draw up a preliminary list of vignettes. The second portion of the instrument was designed to assess the extent to which survey respondents knew of incidents of scientific misconduct and to which they felt they had been personally victimized. In collaboration with S. H. Lipset and E. C. Ladd's 1977 Survey of the American Professoriate, Harriet Zuckerman and Robert K. Merton included several questions which addressed the departure from the norms of science. Professor Zuckerman graciously supplied a copy of the questions. These were borrowed, but were modified slightly. Finally, the last portion of the survey included a number of socio-demographic questions. The initial list contained rather standard questions on sex, age, religion, religiosity, political affiliation, and so on. This bank of questions also included items designed to assess the respondents' recent involvement in research. Before it could be deemed ready for administration, the survey instrument was sent to a number of scientists, each of whom had agreed to read and critique 45 it. These scientists were selected on the basis of their interest and expertise in science. Some of the revieverc were social scientists whereas others worked in the physical and biological sciences. All have % demonstrated interest in scientific research. The returned copies of the questionnaires were combed for comments and criticisms. Since some of the reviewers also sent letters with additional comments, these too were included. Some of the issues that surfaced during this review included duplicate or redundant items, double-barreled items, and items promising little variability. Reviewers also suggested a number of new items designed to eessure issues not previously addressed. Administration of the Survey The survey instrument was designed to minimize inconvenience to the prospective respondents. To this end, a business reply account was established to eliminate the need for affixing postage to the questionnaires themselves. This also meant that respondents would not have to bear the cost of returning the survey. Only the returned instruments would be 46 charged to the account, avoiding the waste of postage in the case of discarded or misplaced questionnaires. With each questionnaire was included a postage paid postcard to confirm the respondents' return of the survey instrument. The postcard bore an identifying number for the respondent. The first wave of questionnaires was sent in April of 1988. In May of 1988 a second wave of questionnaires went out to those scientists who had failed to return the postcard. After the two waves, it was decided that a third administration probably would not yield a sufficient number of additional questionnaires to justify the expense. The return rates for each of the six samples are presented in Table 1. TABLE 1 RETURN RATES FOR EACH OF THE SIX SAMPLES Discipline Sent Returned Percent Physics 275 71 25.8 Chemistry 250 78 31.2 Biology 496 176 35. 4 Economics 248 57 22.9 Sociology 260 106 40.7 Psychology 580 202 34.8 Total 2109 690 32.7 47 The overall return rate la not high by social science standards. Price's <1985) survey of aoadesic scientists yielded ai return rate of only 22.3 percent. The sail survey by Mahoney and Kisper (1976) also had a lov return rate. They suggested that their lov rate say have been due to the absence of a postpaid return envelope, to conducting the survey during the susser sonthB, and to resistance by scientists to this kind of research. Since the postage vas paid in the current study and since it vas conducted in the spring vhile scat faculty vould still be on campus, it say be possible that those vho did not return the instruments are indeed resistant to this kind of study. Table 2 gives lists some of the sociodesographic and professional characteristics of the combined samples. Clearly the vast majority of respondents are male. A plurality of respondents fit into the age bracket 40 to 49, vith three-fifths of the total betveen the ages of 40 end 60. If one vere to drav a profile of the typical respondent, it vould be a tenured professor from a university vith an enrollment of at least 10,000 students. One characteristic vorth mentioning is that one-third <32.7%) profess no religion vhatsoever. 48 TABLE 2 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE COMBINED SAMPLES Number Percent Sex Male 585 85.4 Female 100 14.6 Age Less than 30 2 0.3 30 to 39 136 22.3 40 to 49 202 33.1 50 to 59 168 27.5 60 to 69 80 13.1 70 and over 22 3.6 Tenure Status Tenured 510 75.7 Not yet tenured 97 14.4 Non-tenure track 44 6.5 Other 23 3.4 University Size <2,500 Students 92 13.8 2,500-4,999 38 5.7 5.000-9,999 99 14.8 10.000-19,999 164 24.5 20.000-29,999 145 21.7 30,000 or more 131 19.6 Relioidus Preference Protestant 223 32.9 Catholic 88 13.0 Jewish 100 14.7 None 222 32.7 Other 45 6.6 CHAPTER V THE PERCEIVED SERIOUSNESS OF SCIENTIFIC MISCONDUCT Prior Work on the Serioweneae of Scientific Mlgconduct Given the faot that there has been little empirical vork conducted on the aubject of ethical misconduct in acience, it should not be surprising that there is even less material on the topic of its seriousness. Most of vhat can be found in the literature is based on the opinions of scientists or sociologists of science. Harriet Zuckerman, a sociologist of science vho has vritten an early, comprehensive essay on deviant behavior in science, asserts that "the faking of evidence in science is its capital crime" (Zuckerman, 1977). "Because of the interdependence of investigators," writes Patricia Woolf <1981>, "scientists are not likely to welcome someone who has betrayed their confidence. Once credibility in science is lost, it is lost for good. " Thus the seriousness of acts such as the falsification of data and plagiarism is 49 50 auch that violators are generally expelled from the discipline, never to be permitted to engage in research again. June Price Seriousness in the Present Study In Chapter III an argument vas presented for considering ethical misconduct in academic science as breaches of trust. It vas noted, however, that trust is not an element peculiar to any one milieu. Rather, it can be argued that in many, if not most, social milieux, trust plays an important role in maintaining cohesion among actors. If trust is pervasive throughout society, then, there should be consensus on the perceived seriousness of breaches of that trust. This, of course, implies a 51 aonsensus model of social norms. However, since consensus is central to Merton's structural-functional approach to the norms of science, it perhaps makes sense to consider approaching the empirical assessment of norm violations in science with such a vie*. Following procedures used by other investigators who have employed the magnitude estimation technique (Sellin and Wolfgang, 1964; Erickson and Gibbs, 1979; Evans, 1981 among others) the scores on the vignette variables were first converted to their natural logarithms. In order to rank-order the vignettes, the geometric means, which is the standard measure of central tendency for log-transformed data (Stevens, 1986), were calculated. This was done by exponentiating the log means of the vignette variables. The rank-ordered "offenses" for the combined six samples are listed in Table 3. As suggested in the anecdotal literature mentioned above, the falsification of data is indeed perceived to be the most serious of ethical breaches, even across disciplines. Grouped at the more serious end of the list are both the theft of ideas and written work. Sexual exploitation, which as discussed in Chapter II is found in many settings other than academe, is found on the more serious end of the list. 52 It is noteworthy that falsification and some of the other serious breaches of scientific ethics are considered more serious than the theft of a personal computer, clearly a felony by current criminal law. This finding might lend some support to what Sir William Blaokstone (1080) referred to as offenses mala in se. It may well be that there indeed are behaviors deemed inherently wrong regardless of the existence of codified rules prohibiting them. S3 TABLE 3 RANK-ORDERED SERIOUSNESS RATINGS OF COMBINED SAMPLES Abbreviated Vignette Geomean Rank Making Up Data 1092.a 1 Publishing Fabricated Data 1066.2 2 Conspiracy to Falsify Data 1028.5 3 Fabrication Of Data 1012.0 4 Faculty Steals Student Paper 822.4 5 Referee Steals Other's Idea 688.4 6 Sexual Exploitation Of Student 680.2 7 Reviewer Takes Idea For Proposal 565.2 8 Bogus Papers On Vite» 560.8 9 Makes Untrue Ethics Allegation 523.6 10 Stealing Colleague's Computer 518.0 11 Misappropriation of Research Funds 494.7 12 Pirating Others' Papers 494.4 13 Lying About Degree To Get Job 487.9 14 Suspect In Faking Destroys Data 438.8 15 Slight Intentional Data Errors 431.8 16 Untrue Allegation About Idea Theft 391.2 17 Assistant Fails To Get Credit 342. 1 18 Failing To Report Sample Bias 245.9 19 Refusing To Work With Minority 237.0 20 Lying About Significance Level 225.6 21 Fall To Disclose Original Data 225.3 22 Using Ghostwriter Without Honesty 206.9 23 54 TABLE 3 Abbreviated Vignette Geomean Rank Multiple Publication 198.3 24 Director Demanding Authorship 175.8 25 Selectively Reporting Of Data 162.0 26 Second Submission Of Paper 147.7 27 Colleague Steals Discussed Idea 123.7 28 Skirting Manuscript Revlev Process 119.4 29 Falling To Disclose Grant Sources 108.5 30 Hot Reporting Income For Taxes 99.7 31 Selling Desk Copies For Income 97.2 32 Falling To Cite Relevant Sources 76.1 33 Nhlstlsblcvsr First Goss To Press 75.7 34 Teaching Only Personal Viewpoint 71.8 35 Placing Unread Paper On Vitae 71.2 36 Reporting Only Significant Teste 64.9 37 Falling To Devote Time To Project 55.0 38 Submitting Favorable Evaluations 31. 8 39 Using Funds For Unrelated Project 42.3 40 Collaborator Finishes Paper Alone 35.7 41 Taking Supplies From Office 33.6 42 Five Papers Instead Of One 15.5 43 Writing Textbooks For Income 5.7 44 Falling To Acknowledge Assistance 1.0 45 55 Inspection of the lists in Appendix D suggests thst the six samples of scientists, as veil as the group comprised of all six combined, seem to be in general agreement on the seriousness of the 45 acts. Based on the anecdoctal evidence, the meager empirical evidence to date, and the assertions of Merton <1973) that a normative structure does exist in the scientific community, it vas hypothesized that each of the six groups of academic scientists vould rank the vignette variables in essentially the same order. That is, the research hypothesis asserts that astronomers and physicists vould place the falsification of data in roughly the same order as did the chemists, experimental biologists, and other groups under study; the null hypothesis asserts that there is no statistically significant relationship in the vay the six groups ranked the vignettes. To first test this hypothesis, the rank-ordered data vere tested using Kendall's coefficient of concordance. This measure is a non-parametric statistical technique that tests overall agreement among three or more ranks of data. The resulting coefficient can range from .00 to 1.00, vith the former indicating no association in the ranks, the latter indicating perfect agreement. 56 When W vae calculated for the six groupe, it yielded a rounded coefficient of .969. Following the instructions of Siegel (1956), chi-square was computed to test for statistical significance. It was significant at the .05 level. But since Kendall's W expresses the "average" agreement among the six groups (Kerlinger, 1973), is it perhaps possible that any individual group differences are obscured by the averaging of the seriousness scores. For example, if each of the six groups except the economists were in extremely high agreement, could it not be possible that the five groups in agreement would outweigh the one that was discordant? To answer this question, fifteen Spearman's rhos were calculated, each of which represented a unique two discipline combination. In this way, if any two groups were in the substantial disagreement on rankings, it would surface in the two-group tests. The results are reported in Table 4. 5 7 TABLE 4 MATRIX OF RHO VALUES FOR EACH TWO DISCIPLINES Field Phys. Chem. Biol. Econ. Soc. Psych. Phys. Chem. . 971 Biol. .972 .962 --- Econ. . 967 .955 . 969 ---- Soc. .968 .964 . 975 . 973 --- Psych. .969 .971 . 979 . 966 . 983 --- All are significant at .05 level. The Dimensions of Scientific Misconduct The 45 vignettes represent a considerable variety of potentially unethical acts, ranging from falling to footnote a colleague's contribution to stealing the colleague's computer. This range, then, goes from what could be deemed as merely poor manners to what Is clearly felony theft. Consequently, there exists the possibility that there are dimensions present In the data other than simply "ethical misconduct." 5 8 One way to identify these dimensions is to employ factor analysis. Factor analysis is a data reduction technique which illuminates any groupings of variables. These groupings can actually be identified in a matrix of intercorrelations among variables; however, factor analysis confirms these patterns. Moreover, it permits the investigator to rotate axes in three dimensional space in order to improve the initial fit. Because the empirical literature on scientific misconduct is so meager, and because the discursive material gives little clue as to what dimensions might underlie the behaviors represented by the vignette variables, any factor analysis to be performed on these data would necessarily be exploratory in nature. To examine the underlying structure of the data, the 45 vignette variables were factor analyzed using a varimax rotation. This technique makes the assumption that the resulting factors are orthogonal, or unrelated. While this assumption may not coincide with the reality of any social science data set, it makes the resulting factors more easily interpreted. To define the factors, a decision was made to use only factor loadings of .5 or higher. This substantially exceeds the .3 criterion as suggested by Kim and Mueller (1978). Variables which had loadings of 59 at least .5 on both factors were omitted. The results of the analysis are presented in Table 5. TABLE 5 FACTOR LOADINGS FOR VIGNETTE VARIABLES Abbreviated Vignette Factor 1 Factor2 Using Funds For Unrelated Project .097 -.491 Reporting Only Significant Tests .211 -.506* Making Up Data .904* -.109 Not Reporting Income For Taxes .312 -.631* Placing Unread Paper On Vitae .328 -.696* Taking Supplies From Office .142 -.653* Failing To Cite Relevant Sources . 325 -. 697* Skirting Manuscript Review Process .409 -.693* Selectively Reporting Of Data .516 -.566 Fabrication Of Data .910* -.172 Lying About Degree To Get Job .779* -.300 Bogus Papers On Vitae .856* -.263 Using Ghostwriter Without Honesty .594* -.491 Selling Desk Copies For Income .494 -.460 Second Submission Of Paper .567 -.634 Director Demanding Authorship .566 -.578 Multiple Publication .620 -.582 Failing To Acknowledge Assistance -.055 -.374 Writing Textbooks For Income .252 -.621* Collaborator Finishes Paper Alone .071 -.587* Pirating Others' Papers .836* -.340 60 TABLE 5 (continued) FACTOR LOADINGS FOR VIGNETTE VARIABLES Abbreviated Vignette Factor 1 Factor2 Teaching Only Personal Viewpoint . 380 “.652* Referee Steals Other's Idea .907* -,255 Reviewer Takes Idea For Proposal . 684* -.260 Submitting Favorable Evaluations . 180 -. 612* Whistleblower First Goes To Press .467 -. 389 Makes Untrue Ethics Allegation . 830* -.255 Failing To .Disclose Grant Sources .453 -. 694* Suspect In Poking Destroys Data .775* -.312 Assistant Fails To Get Credit .774* -.357 Publishing Fabricated Data .935* -. 143 Sexual Exploitation Of Student . 855* -.304 Faculty Steals Student Paper .916* -.206 Failing To Report Sample Bias ,661 -. 547 Slight Intentional Data Errors . 826* -.386 Refusing To Work With Minority .692* -. 367 Lying About Significance Level .718* -.448 Fail To Disclose Original Data .579 -.512 Colleague Steals Discussed Idea . 550* -. 296 Failing To Devote Time To Project . 196 -.617* Untrue Allegation About Idea Theft .753» -. 397 Stealing Colleague's Computer .836* -.314 Misappropriation of Research Funds . 838* -.265 Conspiracy to Falsify Data .921* -. 159 • denotes variables used to define the factor. 61 Ae can been seen in Table 5, tvo dimensions of ethical misconduct emerge from the intercorrelations. The first, the Miapresentation Factor, is comprised of acts which, for the most part, are on the upper end of the seriousness scale. These include the serious breaches of trust such as theft of property and ideas, the falsification of date, lying about having degrees and about using ghostwriters, as well as other more extreme forms of deceit. Interestingly enough, this dimension also includes acts which do not necessarily bespeak a lack of trust, namely, the refusal to work with a racial minority and the sexual exploitation of a student. Once again, perhaps the common thread that holds these more serious behaviors together is a general sense that they are wrong in any social milieu rather than just in the realm of academic science. The second factor, termed the Propriety Factor, bespeaks of behavior which, although perhaps somewhat unethical, has more to do with the lack of courtesy, the telling of harmless "white lies,” and other acts which some academic scientists may frequently engage in without suffering pangs of guilt. For example, failing to devote the required amount of time to a research project may be the norm rather 62 than the exception. When a scientist commits a specified amount of time in a grant proposal, he or she may simply consider it a rough estimate of vhat vill be required when the study is underway. The diligent scientist may consider much more important that the research is performed correctly according to the grant's timetable. Much the same could be said about behaviors such as writing textbooks for income. In fact, one respondent wrote on the questionnaire that "it's a free country." Despite the image of the scientist working long hours in a laboratory on pathbreaking research, it is probably the case that scientists reserve the right to engage in more profitable enterprises such as writing textbooks and consulting. One act which surprising loaded on the Propriety Factor is the submission of favorable evaluations. Academic scientists who are being considered for tenure and promotion have to tender their teaching evaluations. While quality teaching may not be the moat important factor in tenure decisions, it is one of several taken into consideration. To include only those evaluations by students which are complimentary is overtly deceitful and would seem to be the equivalent of publishing only those data which made the 63 author look good. Nevertheless, the fact this vignette loaded on the Propriety Factor suggesta that academic scientists simply do not consider this kind of deceit very serious. The Explanation of Seriousness Having determined the dimensionality of ethical raiecondUGt represented by the vignettes, it now possible to try to explain the variance in each factor. In fact, one of the reasons for performing factor analysis is to develop factor-based indices. The new index variables can then bo used in subsequent analyses as either dependent or independent variables. To compute a factor-based index it was first necessary to multiply each respondent's score on a particular variable by that variable's loading. This weights each variable in the factor; otherwise, one would have to make the assumption that each variable in the factor contributes equally. Once the scores are multiplied by the loadings, they are all summed. The result is a new variable which represents the whole factor. The two new variables, one of which represented the Misrepresentation Factor, the other which 64 repramented the Propriety Factor, sere used as dependent variables in two stepwise regression analyses. In stepwise regression, only those variables which contribute significantly to the multiple R-«quare are retained in the equation. Twenty-two independent variables were used in the analyses. In addition to the sociodeaographic variables of age, sex. religion, political party, and political attitude, professional variables relating to school size and tenure status were also employed. Variables relating to whether the respondent had been plagiarized, had had an idea used without permission, or had personally known a data falsifier were also included. Dummy variables were created for all nominal variables included in the analysis. TABLE 6 STEPWISE REGRESSim: SUMMARY FOR MISREPRESENTATION FACTOR Step Variable R R2 Increase 1 Productivity .1233 .0152 .0152 2 V50 TABLE 7 STEPWISE REGRESSION SUMMARY FOR PROPRIETY FACTOR Step Variable R R2 Increase 1 V50 (Satisfied) .1531 .0234 .0234 2 Male , ISIS .0329 .0095 The results of the two stepwise regression analyses can be found in Tables 6 and 7. The variables which set significance and thus were kept in the equation -do little to explain the variance of either the Misrepresentation Factor or the Propriety Factor. In Table £, for examnple, the total R2 is less than four percent. That is, the total asount of variance explained by the independent variables kept in the equation is sinisal. Much the same can be said for the results of the regression with the Propriety Factor as dependent variable. Just over three percent of the variance in that factor is explained by the two independent variables kept in the equation. . The failure of the.independent variables to explain the variance could be due to a couple of reasons. It is possible, for example, that the items from the questionnaire used as independent variables simply were not good predictors of seriousness. Future such studies 66 should Include items' which promise to -explein more -variance then those used in the present study* .. If one were to subscribe to Merton s view* it would be easy to argue that the scientists were in agreement on the oeriousness of these acts beoause they had internalized the norms, of science. But what must be kept in mind is that the two dimensions of ethical misoonduct which emerged from the analysis contained behaviors which are not peculiar to -academic science. One way to answer the question would be to administer the survey instrument to -a random sample.of lay persons. If they ranked the vignettes in the same way as did the scientists* it might suggest that notions about what is right and wrong may transcend the boundaries of a particular occupational milieu. CHAPTER VI THE PERCEIVED INCIDENCE OF SCIENTIFIC MISCONDUCT Deviance in Science: How Much? As suggested earlier, neither the "fev bad apples In the barrel” camp nor the "tip of the Iceberg” camp actually knows how often deviant acts occur In academic science. Representatives of both camps continue to speak with authority on they believe to be the amount of scientific misconduct. In the last century, Babbage <1830:177) asserted that "Fortunately Instances of the occurrence of forging are rare.” Robert K. Merton, one of the most prominent sociologists of science as well as one the staunchest defenders of science's reputation, while stating that known Instances of fraud are rare, admits that "an accurate estimate of frequency Is Impossible." 1957). More recently, Woolf <1981) has Indicated that her Inquiries into the subject of scientific misconduct had 67 68 yielded an average of one or two caaes per year. Brandt (1983) referred to a National Institutes of Health review which turned up only 45 oases of alleged or suspected misconduct out of more then 20,000 HIH awards and contracts. But since the figures of both Woolf and Brandt seem to be based on reported cases, the numbers may well be a fraction of total amount of misconduct that occurs. In their survey of scientists, Mahoney and Klmper (1976) found that the percentage of respondents knowing of an Incident of fabrication In their field ranged from 30.8 for physicists to 57.1 for biologists. It should be noted, however, that at least some respondents could have been referring to the same Incidents, making the resulting Incidence estimate somewhat high. In order to provide better estimates of fraud, plagiarism, and related forms of misconduct, survey respondents were presented with several questions designed to assess whether they perceive deviance In science to be a problem. The first such question asked them to estimate the frequency with which scientists In their respective fields steal the work of colleagues. Table 8 shows that a negligible number believe that It never happens. 69 TABLE 8 PERCEPTIONS OF HOW OFTEN SCIENTISTS AND SCHOLARS STEAL THE WORK OF THEIR COLLEAGUES Perceived Frequency Number Percent Often 15 2.2 Sometimes 278 41.1 Rarely 375 55.4 Never 9 1.3 Total 677 100. 0 The respondents were also asked to report if their own work had ever been stolen or plagiarized. Of the 455 scientists answering the question, 40.7% indicated they had been victimized. Whether or not this finding supports the "tip of the iceberg" camp is debatable. For one, it is not possible to calculate an offense rate with such data since there might be overlap in offenses. That is, some of the respondents could be reporting the same incidents which would inflate the apparent rate. Further, one has to bear in mind the effect of non-response in surveys. There is always the possibility that non-respondents differ in one or more significant respects from those who completed and returned the Instrument. Those who 70 have a complaint to air may be more prone to vent their frustration by filling out a questionnaire on the subject. Consequently, caution is necessary in interpreting survey results. The incidence variables were cross-tabulated with a variety of sociodemographic and professional variables. These included gender, rank, tenure status, political party, political attitude, and productivity. Since there is little theoretical or empirical work to suggest hypotheses, much of these analyses were necessarily inductive. 71 TABLE 9 PERCEPTIONS OF WHETHER RESPONDENTS' OWN WORK HAS BEEN STOLEN OR PLAGIARIZED: BY GENDER Male Female Response No. X No. X Yes 152 38.9 33 56. 6 No 239 61.1 31 48.4 chi-square=3.693 d.f.=1 p<. 10 The findings in Table 9 above may be revealing in light of vhat many sooiologists already believe about sex-rolea and the probable exploitation of women. It very may be that due to a somewhat subordinate status in academic science, women are more likely to be victimized than are their male counterparts. The chi-square is not significant, but the closeness serves as a justification to test hypotheses on the effect of gender with other incidence variables. Other variables, however, were found to be significantly related to whether or not the respondents' own work had been stolen. Crosstabulations of perceived plagiarism with productivity and rank are shown in Tables 10 and 11. Similar analyses using political 72 party, political attitude, ar&d tenure status yielded non-significant findings. TABLE 10 PERCEIVED PLAGIARISM BY PRODUCTIVITY LEVEL Lov Medium High " Response No. % No. X No. X Yes 43 31. 4 55 36. 2 80 54.0 No 94 6 8 . 6 97 63.8 68 46.0 chi-square«17.404 d.f.*2 p <.05 TABLE 11 PERCEIVED PLAGIARISM BY PROFESSIORAL RANK Assistant Associate Professor Response No. X No. X No. X Yes 18 30.O 49 35.5 107 47. 1 No 42 70.O 89 64.5 120 52.9 chi-square=8.577 d.f.«2 p<.05 73 The findings presented in the tables above suggest that academic scientists vho have attained the rank of professor and who give evidence of high productivity are more likely to perceive themselves as having had their work stolen. This could in part be a function of time. That is, those who have attained the rank of professor usually have been faculty for a number of years. It could also be the case that those who are productive and are perceived as such by their peers are those whose ideas are deemed worth stealing. Of perhaps greatest interest in the controversy over scientific ethics is the falsification of data. Not only is it referred to as science's "capital crime," it is also the offense which draws the most attention in both the scholarly end popular press. Naturally, the discussions usually move to how much falsification occurs in science. As discussed earlier, most of the "experts" who assert their opinions on the incidence of fraud in science do so in the absence of empirical data. It is this increased attention to scientific misconduct, coupled with so many unsupported assertions, that makes the incidence of fraud as perceived by the scientists in this study especially interesting. Table 12 gives the numbers and percentages of those who reported personally 74 knowing someone vho had falsified data and then passed it off as legitimate. TABLE 12 HAVE YOU PERSONALLY KNOWN SOMEONE WHO HAS FABRICATED DATA AND PASSED THEM OFF AS LEGITIMATE? Response Number Percent Yes 156 23 No 523 77 Total 678 100 Once again, the appropriate caveats need to be issued about the generalizability of the findings to the whole of academic science, or, for that matter, to the six populations from which the samples were drawn. Still, in the absence of reliable official statistics or more complete survey data, these numbers provide a sounder basis for discussion thnn previously has been available. The same set of independent variables were used in cross classifications with the falsification variable. Only one, professorial rank, proved to be significantly 75 related at the .05 level. Here, rank Is probably related due to Its relationship to time. The longer an academic eclenltlst has been in that career, the more likely he or she la to be a full professor and, consequently, the more likely will he or she have encountered a data falsifier. One somewhat ambiguous area of scientific ethics Is the proprietary rights governing unpublished Ideas. Unlike plagiarism, which Involves the misappropriation of one's written work, the theft of unpublished Ideas Is less well-defined. The situation Is complicated by Hertonlan norms which make secrecy an offense of sorts. According to Merton (1973), It Is only In the making public of an Idea or finding that the scientist can legitimately lay claim to It. But as Ben-Yehuda (1985) has observed, the free exchange of Ideas with unscrupulous colleagues can result In "an Intellectually castrating experience." To assess the extent to which the study's respondents had shared Ideas with colleagues only to have those Ideas used without permission, that very question was posed. Based on the serendipitous finding above that pointed out the exploitation of female scientists. It was hypothesized that they would be disproportionately represented as victims of the theft 76 of Ideas. The results of that analysis are shown below in Table 20. TABLE 13 SCIENTISTS REPORTING THAT IDEAS THEY SHARED HAD BEEN USED WITHOUT THEIR PERMISSION BY GENDER Male Female Response No. % No. % Yes 217 37.6 48 48.5 No 360 62.4 51 51.5 chi-square=4.20198 d.f.=l p<.05 Of the five independent variables other than gender which were used in these cross classifications, only productivity met statistical significance. The findings, mirroring those reported in Table 10, indicate that the more productive the scientists are, the more likely they are to perceive themselves to have had an idea used by another without their permission. Another way in which academic scientists can be victims of ethical misconduct is in co-authoring 77 manuscripts. Co-authorship does not always reflect an equal contribution to the effort. This is acceptable as long as both parties agree on the allocation of work and rewards. However, occasions arise wherein scholars fail to receive the credit they feel they deserve. And sometimes they are not in a position to object, especially if the exploiter has more power than the individual who perceives himself or herself to be a victim. In response to this very type of circumstance, a question was posed to respondents to assess their experiences as victims of inequitable allocations of authorship credit. However, the question was designed to differentiate those who received less credit and were dissatisfied from those who were for the most part satisfied with less authorship credit. TABLE 14 HAVE TOU EVER RECEIVED LESS AUTHORSHIP CREDIT THAN YOU BELIEVE YOU ACTUALLY DESERVED? Number Percent Yes, but satisfied 182 27 Yes, and dissatisfied 135 20 No 357 53 Total 674 100 78 As can be seen from the data in Table 14, fever than half of those responding to the question on authorship credit felt they had received less credit than they deserved. Interestingly enough, however, the majority of those vho got leas than they deserved vere satisfied vith the allocation. This suggests that there are informal rules for the allocation of credit. One practice that may account for scientists graciously accepting less authorship credit than they deserve is vhat has termed noblesse oblige, the tendency of those vith status to behave generously toward those in subordinate positions. There are times when a senior scholar throws senior authorship to a co-author when the former knows it is important to the letter's prospects for tenure and promotion. The data presented above on the perceived incidence of misconduct suggest that some of the respondents at least perceive that violations do sometimes occurs in their fields. Further, it is the perception of some respondents that they have been victimized and/or have known offenders. These findings lead us to believe that the incidence of ethical misconduct in academic science is to a certain, albeit unknown degree, greater than that suggested by the handful of cases which are eventually aired in the press. 79 One should be cautious, however, not to infer that the ivory tower is ready to topple over. Some of the incidents to which respondents referred may have been formally proven with incontrovertible evidence, placing the guilt of the alleged offender beyond any reasonable doubt. The perceptions and suspicions of some of the respondents, however, may not be warranted. What they suspected was an incident of falsification or plagiarism may have oeen something quite benign had all the facts come to light. The limitations of these data emphasize the need for official statistics on ethical misconduct in science, academic and otherwise. Until universities, government agencies, and scientific societies keep and make available reliable statistics on the incidence and prevalence of these breaches of ethics, those concerned with the problem will be forced to support their assertions with less than acceptable data. CHAPTER VII DISCUSSION AND IMPLICATIONS Malor Findings Confirming what ia auggested in the literature, the falsification of data is deemed more serious than the other forms of scientific misconduct represented in the survey. This is true regardless of the discipline of the academic scientist. In fact, the data reveal that the faking of date is regarded as more serious than felony theft. It was hypothesized that regardless of discipline, academic scientists are in agreement on their perceptions of the seriousness of ethical misconduct. This is true not only for the most serious acta such as the falsification of data and the theft of ideas, but also for minor ethical breaches such as failing to footnote the assistance of reviewers. One curious finding, however, is that the group of most serious ethical breaches contains behaviors not solely the province of academic science. The refusal to 80 81 work with a minority and sexual exploitation could occur In virtually any work setting. This suggests a dimension not of scientific misconduct, but of wrongful behavior. While the current study falls to unequivocally support either the "few bad apples” camp or the "tip of Iceberg" camp. It leads us to believe that the proportions of respondents reporting knowledge of scientific misconduct warrant at least some attention. It has become almost standard for Investigators to conclude their studies with the call for more research. Whether more research on the seriousness and Incidence of scientific deviance Is justified Is a matter of debate. From a policy standpoint, we know such violations occur at least occasionally. This knowledge serves as justification for policies designed to prevent misconduct, to punish confirmed violators, end to protect whistleblowers and other Innocent parties. And such policies have been In the making for some time. It Is unlikely, then, that additional data would alter the swing of the pendulum. 82 Suggestion# for Future Study One direction that seems to emerge from discussions of ethical behavior in science is whether or not the norms outlined by Merton <1973), Barber (1952), and others are correct. The issue is especially important, particularly if one defines deviant behavior in science as that which violates the norms of science. Perhaps more useful than the norms of science are more general norms such as trust, discussed in Chapter III, which pervade spheres of life other than academic science. If we agree that a certain set of norms -- Hertonian or otherwise -- are in part validated by the high rate of agreement among the six scientific disciplines, a second question asks just how these norms are communicated. Does graduate training provide for the formal or even informal promulgation and transmission of science's dos and don'ts? Where in fact are scientists supposed to learn these norms, their importance, and the consequences of violating them? And do those seeking the Ph.D., traditionally a research degree, stand a better chance of learning the canons of science than H.D.s? Another question which is more related to the sociology of knowledge than the sociology of science or 63 deviance is vhy so-called "experts" are so eager to rush to the fore when a new social problem emerges. In the wake of the 1974 Summerlin affair and other publicized cases, a number of writers seemed to take advantage of the void and consequently offered estimates of incidence and prevalence, etiological explanations, and suggestions for changes in policy, all in the absence of empirical data. Theoretical Implications Although empirical work in a new field of sociological endeavor is a good place to begin, it is perhaps a poor place to finish. Simply mapping the contours of a new form of deviance does not make the sort of contribution which will advance theoretical understanding, particularly etiological theory. Social scientists, by definition, are obliged to strive toward explanation and prediction of the phenomena under study. If they fail to assume this second role, they may also fail to adequately distinguish themselves from journalists and other collectors of social facts. And the role of sociologist, at least according to Mill (1959), is the greater intellectual endeavor. 84 The current perspectives on deviance seem Inadequate to explain ethical misconduct in science. Although the discussion in Chapter III argued that deviant behavior in academic science can be considered yet another form of violation of trust, the literature is less specific about vhy individuals betray trust. One could adopt Cressey’s notion of the unshareable problem in spawning a violation of trust. But in academic science, the looming problem for virtually all faculty -- tenure and promotion -- should be shareable simply because everyone has it in common. Recently it has been suggested that the paradigms in criminology may be exhausted again rediscover old ideas, only to perpetuate the cyclical nature of criminological thought? The ptudy of deviant behavior in science underscores the need for criminologists to develop a theoretical perspective that will explain misconduct by those in both the upper and lower strata in society. It certainly is to Sutherland's lasting credit that he made ouch an attempt; that he was unsuccessful should not be held against him. Further, there appears to be some justification for developing a perspective which reconsiders the 85 individual as one who Is possessed of free will and who can thus choose from an array of possible courses of behavior, despite structural or subcultural pressures to depart from conventional norms. But Instead of asking criminologists to abandon a structural or social psychological posture. It urges them to reconcile the two with a stronger, more encompassing hybrid. Whereas analysts of white-collar crime have demonstrated that the milieux In which organizational deviance occurs are conducive to deviance. If not downright criminogenic (Cllnard, 1983), It Is difficult to make the same claim regarding the world of academic science. In the publicized cases of Summerlin, Alsabtl, Darsee, and Breunlng, there emerged only single offenders who had perpetrated the unethical acts. Regardless of the fact that John Darsee's co-authors should have been more diligent In discharging their responsibilities as collaborators, there Is no evidence that they acted as co-consplrators, or wittingly assisted his scheme In any way. Based on what Is known thus far, then, ethical misconduct In science appears to be largely. If not entirely, an offense by Individuals acting alone. John Long, an exposed data falsifier, gave the following explanation before the I). S. House of Representatives: 86 I do not believe that the environment in which I worked was responsible for what I have done. Competition for limited research funds among research investigators is a necessary part of federally funded scientific work. Neither this, nor competition for major rewards in science, can be implicated as an important factor in my particular instance. An honest investigator should be able to deal effectively with the traditional "publish or perish" pressures.... The loss of my ability to be an objective scientist. .. cannot...be linked to defects in the system under which I worked. know this through the successful replication of countless scientific studies. Any general theoretical perspective on deviant behavior, then, must answer the age-old question: Why do some persons engage in deviant behavior and others do not? (Hirschi, 1969). A second theoretical question has to do with the labeling perspective. Several theorists (Becker, 1963; Lemert, 1951; Scheff, 1966; Schur, 1971) have suggested that labels are often unnecessary and, in fact, may even spawn additional or secondary deviance. We have seen 87 that In the case of academic scientists, the label applied by the scientific community seems to be warranted due to the extreme harm caused by these breaches of trust. Having to bear auch a label, and being forced to leave scientific research altogether, the deviant so labeled is effectively cut off from opportunities to engage in further (secondary) scientific deviance. Should not this prompt criminologists, then, to analyze the labels applied to various deviants to differentiate those which are undeserved and unnecessary from those which agents of social control have a right -- perhaps even an obligation -- to apply? Policy Implications It seems clear from this study that ethical misconduct in science is a problem in need of attention. Exactly what should be done about the problem, however, does not necessarily flow from these data. In the case of sharing ideas with colleagues, are we to suggest that academic scientists should no longer breathe a word of their ideas to others? Such a conclusion is not only impractical, it also flies in the face of what Merton (1973) has told us about the necessity of communicating 88 scientific ideas. The data do indicate that ethical misconduct is a more serious problem than some analysts would have us believe. Short of eroding the trust implicit in scientific work, what can the scientific community do to reduce the likelihood of ethical misconduct? The significant agreement on what is and what is not serious suggests that the respondents know what is wrong regardless of the existence of formal ethical standards. Not all the groups under study have written codes of ethics governing their behavior; however, they ere in agreement on what is wrong and what is right. Why, then, are written standards necessary? Formal ethical standards would serve several purposes. One, written standards could define those behaviors which currently fall into the grey area between the extremes of right and wrong. With formally adopted guidelines, there would be less room for would-be offenders to take advantage of ambiguous norms. Two, behind these formalized statements should be procedures designed to safeguard both the accused and the whistleblower; the prospective victims must know what recourses are available to them. On an individual level, professors, students, and other academic scientists engaged in collaborative work 89 should openly discuss the authorship issue before the work is undertaken. While it may seem like an extreme and perhaps unnecessary measure, academic scientists might even consider drawing up a formal contract which specifies exactly how and what each participant is obligated to perform and in turn what he or she can expect to get in return. One of the reasons this study was necessary was the lack of statistical record-keeping with regard to ethical misconduct in science. Recordkeeping on the subject is unsystematic, consisting primarily of lists of publicized accounts. Because of the tendency of university officials to minimize publicity over incidents of scientific fraud occurring in academe, there is reason to believe that the available accounts are an inadequate measure of official reports. Perhaps with the increased attention the topic is likely to receive, even those whose reputations are tinged by such incidents will demonstrate a greater willingness to record and disseminate meaningful statistics. APPENDIX A DATA COLLECTION INSTRUMENT 90 91 Ethical Issues In Academic Science: A Survey T U i praiccl it funded by the National Science Foundation to turvey tcicntitu' atUtudet concerning proper and impioper Klentific conducL V mi have been «elected from a list of ccientita from throughout the country. \bur participation will be greatly appreciated, and pour answers will remain confidential and anonymous. PART A Below ere a number of vignettes describing various types of scientists' behaviors which some may consider appropriate and others may consider inappropriate. Masculine gender has been used throughout only for ease of construction. We would like you. io evaluate the relative propriety.'impropriety of the behavior described in each vimette from your own perspective. ‘That is, evaluate them according to your own values, not according to what you think others would think. In evaluating the propriety impropriety of each act, please record your evaluation on the line to the right of each vignette. The first one has been done as an example for you. It shows an act which is given a score of 10. Use this act as a standard. Each vignene should be scored in relation to this standard act. For example, if any act described below seems ten times as serious as the standard, write in a score of 100. If an act seems half as serious as the standard, write in a score of 5. You may use any whole or fractional numbers that are greater than zero no trrarter how small or large they are. Just so long as they represent how serious you consider this act compared to the standard act. A acim tU t sums cocisiatm lv Hv« or ten mlnrrte# late to hi* class 10 1. When A e funds for a research project arrived at the institution, the scientist was not yet ready to commerrce work on the funded project Instead, he used the grant money for a related research project wlthtvit permission of the funding agency. 2. A scientist performed a number of statistical tests on his data. He then reported only the few statistically significant tests without noting the non-significant differences. 3. faittead of collecting b >na fide data for a study, the scientist simply made them up. 4. A scientist intentionally did not report several thousand dollars on his federal income tax return which he had received from consulting. 5. A scientist's paper was accepted and placed on the pfogram of a professional society's annual conference. He neither attended the meeting nor had anyone read the paper for him. However, the author placed the presentation on his curriculum vitae as though It had been presented. 6. A scientist secretly look several reams of paper, boxes of pens, staples, paper clips, and other office supplies from his research center for his own personal use. 7. Cn writing a paper for publication, a scientist consciously chose not to cite the relevant work of others who had previously written on the subject. 8. The editor of a scientific journal published his own paper in the journal without subjecting it to the required manuscript review process. 9. A scientist consciously chose to report only that portion of his data which supported his thesis. 10. A scientist fabricated data in order to meet his funded research obligation. 11. A scientist lied about having an advanced degree ssfioi applying for aJob. 12. On his curriculum virae. a scientist listed as publications papers he had neither written nor published. 13. A scientist enlisted the services of a ghostwriter to author his book. Nowhere In the book did the scientist acknowledge that the writing was done by arwther. 14. A scientist requested examination and desk copies of books in order to sell them for additional personal income. . 15. After publishing a nranuscript in oiM Journal a scientist submitted an almost idendca] article to another Jotrmal without notifying me Journal's editor that the paper had been published elsewhere. 16. The director of a research center demanded authorship on all papers written by research center employees even though he was not involved in the hypotheses formulation, data collection, analysis, or actual writing of the papers. 17. A scientist took three of his manuscrfpts and published each In Journals from three different countries, yielding film a to ttl of nine published articles. Nowhere did the scientist Irrdlcate that these were nimply rep rin t^ 18. A scientist asked several colleagues to read a manuscript prior to submitting it for publication. The colleagues invested considerable time and offered helpful suggestions which he incorporated in the manuscript. Nevertheless, tire scientist failed to acknowledge their assistance or contributions. 19. A «dentist cceiadously cbose to write lextliooks instead of adtolarfy papers hr order to hcremse his tocsscne. Fige I 92 A scisiitUt m a coasUtaatly Rv* or tria abiBtea latac Utom Us. ______20. Two scientists worked jointly on a paper. Eventually one ol (he two lost interest In the project and stopped working on it...... The other scientist finishedlished the the paper 1 and later published It under his name alone. 21. Upon completing aresearch piDjcct ascientlsipubUshsdflvcntiMTbitefpapenwtwn an th« data oouUhavs been published In one somewhat longer paper _ 22. A scientist located rather obscure articles which he revised and resubmitted to journals as though they were his original work. _ 23. A scientist taught only his own peisonal point of view In the classroom. Ignoring alternative viewpoints as though they did not exist. _ 24. Having had the opportunity to preview another scientist's work, a Journal referee recommended against publication. The referee then re-wrote the paper based on the other scientist s ideas, passing the ideas off as his own original work. - 25. A governmental grant-giving agency asked several scientists to examine a icseaidi proposal. One of the scientists took the idea in the proposal and submitted h to another grant-giving agency for funding. 26. A scientist being considered for promotion and tenure submitted only his favorable student evaluations. 27. Upon finding evidence that acolleague had engaged In unethical research practices, a scientist went to the press without first discussing it with the colleague or attempting to deal with the problem within the department or university. 28. A scientist alleged that a colleague engaged in unethical research practices, even though he knew that the allegation was not true. which support was being sought, even though required to no so by the prospective funder. 30. When questioned about his research findings, a scientist destroyed all the original data. 31. An assistant working for a scientist made a significant discovery. The sdertdst took total credit for die discovery. . 32. A scientist conducting experiments with laboratory animals did not actually conduct the experiments but instead published fabricated data. 33. A scientist implied to a graduate student that the student could progress through the program more easily If the student would grant the scientist sexual favors. 34. Two students wrote what they thought was a strono scientific paper. They asked a faculty member to review it. After he discouraged them from submitting it for publication, he re-wrote the paper and published it as his own original work. 35. Despite the biasing effects of his sample selection procedures, a scientist conducted a study artd reported the results as though they were valid, without describing his sample and its limitations accutatelyi 36. In recording data, a scientist intentionally made slight errors so that the findings would better support hit theory. . 37. A scientist refused to work with a colleague solely because the colleague was a member of a racial minority . 38. A scientist reported that his data findings were significant at the p <.05 level when in fact he knew they were actually significant at only the p < 07 level. 39. A scientist whose research practices were under Irwestigatlon refused to allow anyone else to examine his original data. 40. A scientist discussed one of his new ideas with a colleague. The colleague conducted an experiment based on the idea and published a paper reporting the findings. 41. A scientist received a multl-ycar grant which paid for 80% of the scientist's time. Instead of devoting the required amount ol time to the research project, the scientist used part of the time to work on an unrelamd study. 42. Two scientists simultaneously and independently made the same discovery. Even though one scientist knew that the other had performed original work, he openly charged the other with stealing his Idea- 43. A scientist biokelntoacoUcagia'soffloe and stole his peraonal computer hi order to be mot* prtxhictlveedien he was working at home. 44. A scientist misappropriated research funds lor his own personal use. 45. Severs! scientistx conqthod to falsify data. END OF FART A f b je 2 93 PART B PLEASE WRITE YOUR ANSWER IN THE APPROPRIATE BLANK UNE. 46. Some tcientlits and scholare have been accuied of "ctealing" the worit ol their colleagues. How often do you diink this occurs in your field? I Ohcn 2. Sometimes 3 Rarely 4 Never------47. Has your own work ever been "stolen" or plagiarized? 1. \b s 2 No 3. Don't Know------[IF YES] How often has this happened? times 48. Have you ever personally known someone who has fabricated data and then passed it off as legitimate data? 1 't e 2 No------(IF YES] How often has this happened? times 49. Have you ever shared an original Idea with a professor, colleague, or student only to discover later tfiat that person had used the Idea without your permission? 1 t e 2. No------[IF YES] How often has this happened? times 50. In co-authoring a publication (book, monograph, article, etc.) with one or more individuals, have you ever received less authorship credit than you believe you actually deserved? 1 t e but i was more or less satisfied with the aliocaaon 2 te . and I was dissaasfied with the allocaaon 3 No______51. Have you ever found that another scientist or scholar has published results you published earlier without icferring to your work? 1 t e . author probably didn't ioiow of my work 2 t e . author probably did know of my work 3. No ------52. Have you ever personally known someone who has intentionally manipulated data in order to make it seem more Interesting or important? 1 t e 2 No ------(IF YES] How often has this fiappened? times END OF PART B PART C 53. Sex 1. Male 2 female ______54. in what year were you born? ______55. if currently employed in acollege or imlvenity, wftat Is your position or tank? 1 Lecturer 2. instructor 3. Aastsant Professor 4 Assocsate Professor 5 Professor 6. Other—plaase speedy ...... _____ 56. Do you consider yourself to be a 1 Republican 2. Donocrai 3 Independent 4 Something else'’ ______57. Would you describe your attitudes on most poUdcal Issues as 1. very conservative 2. ixmservaUve 3. bberal 4. very ilbral? 58. What Is the highest degree you have earned? l.B A orB S 2 MA or MS 3 Ph D 4 MD 5 M D /Ph D 6 Other — please cpenfy 59. in ivfaat year did you ncafvt yosir highest canwd depee? f tj e 3 94 60. In what field of specialization did you receive your highest degree? (Please choose from the specialties list enclosed.) 6L If currently employed ina college or university, what is your status? 1. Tenured Z Tmure track Not yet tenured 3. Non-tenure track 4. Other—please specify _ 62. If currently employed in a college or university. u4iat is the total student enrollment on your particular campus? 1. Fewer than 2.5(X) studens 2.2.500 to 4.999 students 3.5.000 to 9.999 students 4.10.000 to 19.999 students 5.20.000 to 29.999 students 6.30.000 or more students 63. Since receiving your hiÿsest earned degree, how many articles have you published in refereed Journals? 64. How many articles have you had accepted for publication in refereed journals within the past 24 months? . 65. How many professional meetings have you atterxled In the past 24 months? 66. How many papers have you presented at professional meetings in the past 24 months? 67. What state do you reside In?______. 68. How many years have you been practicing your current profession? 69. How many years have you been in your current Job? 70. How many years have you been employed by your present employer? 7L What is your religious preference? 1. Protesant 2. Catholic 3. Jewish 4. None 5 Other—;^ease specify , 72. How often would you say you attend religious services? 1. ai least once a week 2 once or twice a month 3 a few time: a year 4 almost never 73. How religious do you consider yourself to be? 1. Very religious 2. Somewhat nthgtous 3. Not very rdi0ous 4. Not rdtgious at all 74. How many thousands of dollars have you earned from outside consulting in the past 24 months? 75. Could you please describe your current area of researdi specialization? (e.g. immunology, criminology, cytology, etc.)------ END OF PART C AND THE SURVEY...THANK YOU FOLD HERE AND RETURN —STAPLE BELOW NO POSTAGE n e c e ssa r y IF mailed IN THE UNITED STATES BUSINESS REPLY MAIL FIRST CLASS PERMIT NO 2965 COLUMBUS. OHIO POSTAGE WILL BE PAID BY ADDRESSEE Ethics in Science Project Bricker Hall. Room 316 The Ohio State University 190 North Oval Mall Columbus, Ohio 43210 STAPLE HERE APPENDIX B SUPPLEMENTAL ENCLOSURE 95 96 FRAUD IN SCIENCE Just a Few Bad Apples? Only the Tip of the Iceberg? Does Anyone Really Know? W e d o k n o w that: • there are few empirical studies on which to hang our suppositions about fraud in science. Most of the dialogue to date has centered around a handful of highly publicized cases. While these may be informative, they are no substitute for more comprehensive data on the contours of ethical misconduct in science. • policies on fraud in science seem to be in the making. Recent Congressional subcommittee hearings suggest that non-scientists have now taken an interest in these issues. It may be to the benefit of the entire scientific community to see that policy makers are supplied with better information as they promul gate guidelines and legislation. You can help fill this void in knowledge about scientific misconduct by completing and retunüng the enclosed survey form. Your participation in this study will be greatly appreciated. Mark S. Davis Ethics in Science Project The Ohio State University Bricker Hall, Room 316 190 North Oval Mall Columbus, Ohio 43210-1353 APPENDIX C CHARACTERISTICS OF THE SIX SAMPLES 97 98 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE PHYSICS AND ASTRONOMY SAMPLE (n=71) Number Percent Sex Male 67 94 Female 4 6 Tenure Status Tenured 44 63 Not yet tenured 9 13 Non-tenure track 14 20 Other 3 4 University Size <2,500 Students 4 6 2,500-4,999 8 11 5.000-9,999 10 14 10.000-19,999 20 28 20.000-29,999 16 23 30,000 or more 13 18 Religious Preference Protestant 23 33 Catholic 10 14 Jewish 8 12 None 24 35 Other 4 6 9 9 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE CHEMISTRY SAMPLE (n=78) Number Percent Sex Male 71 93 Female 5 7 Tenure Status Tenured 58 75 Not yet tenured 11 14 Non-tenure track 6 8 Other 2 3 University Size <2,500 Students 0 10 2,500-4,999 3 4 5.000-9,999 13 17 10,999-19,999 22 28 20.000-29,999 16 20 30,000 or more 16 20 Rellalouia Preference Protestant 26 34 Catholic 15 20 Jewish 7 9 None 22 Other 6 8 100 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE EXPERIMENTAL BIOLOGY SAMPLE Number Percent Sex Male 155 89 Female 20 11 Tenure Statue Tenured 121 70 Not yet tenured 35 20 Non-tenure track 12 7 Other 4 2 University Size SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE ECONOMICS SAMPLE (n=57) Number Percent Sex Male 54 96 Female 2 4 Tenure Status Tenured 51 93 Not yet tenured 4 7 Non-tenure track Other University Size <2,500 Students 1 2 2,500-4,999 1 2 5.000-9,999 5 9 10.000-19,999 15 27 20.000-29,999 17 31 30,000 or more 16 29 Religious Preference Protestant 32 56 Catholic Jewish 7 12 None 15 26 Other 3 5 102 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE SOCIOLOGY SAMPLE Number Percent Sex Male 81 76 Female 25 24 Tenure Status Tenured 78 76 Not yet tenured 23 22 Non-tenure track 1 1 Other 1 1 University Size <2,500 Students 3 3 2,500-4,999 1 1 5.000-9,999 16 16 10.000-19,999 31 31 20.000-29, 999 33 33 30,000 or more 17 17 Religious Preference Protestant 28 27 Catholic 9 9 Jewish 11 11 None 46 44 Other lO 10 103 SOCIODEMOGRAPHIC AND PROFESSIONAL CHARACTERISTICS OF THE PSYCHOLOGY SAMPLE (n=202) Number Percent Sex Male 157 78 Female 44 22 Tenure Status Tenured 156 80 Not yet tenured 15 8 Non-tenure track 11 8 Other 13 7 University Size <2y500 Students 29 15 2,500-4,999 xo18 9 5.000-9, 999 30 16 10.000-19,999 53 28 20.000-29, 999 32 17 30,000 or more 30 16 Religious Preference Protestant 58 29 Catholic 25 13 Jewish 38 19 None 60 30 Other 17 9 APPENDIX D GEOMEANS FOR THE SIX SAMPLES 104 105 RANK-ORDERED SERIOUSNESS RATINGS OF PHYSICS SAMPLE Abbreviated Vignette Geomean Rank Making Up Data 1768. 4 1 Publishing Fabricated Data 1490.5 2 Conspiracy to Falsify Data 1322.0 3 Fabrication Of Data 1061.4 5 Faculty Steals Student Paper 1111.3 4 Referee Steals Other's Idea 646. 0 6 Sexual Exploitation Of Student 755.6 7 Reviewer Takes Idea For Proposal 549.6 9 Bogus Papers On Vitae 476.9 10 Makes Untrue Ethics Allegation 422. 0 11 Stealing Colleague's Computer 419.3 12 Misappropriation of Research Funds 565. 6 6 Pirating Others' Papers 270. 2 19 Lying About Degree To Get Job 416. S 13 Suspect In Faking Destroys Data 363.6 14 Slight Intentional Data Errors 376. 5 15 Untrue Allegation About Idea Theft 343. 4 16 Assistant Fails To Get Credit 372. 3 16 Failing To Report Sample Bias 226.1 20 . Refusing To Work With Minority 370.0 17 Lying About Significance Level 95. 5 26 Fail To Disclose Original Data 169.6 22 Using Ghostwriter Without Honesty 147.4 24 106 RANK-ORDERED SERIOUSNESS RATINGS OF PHYSICS SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 153. 0 23 Director Demanding Authorship 138. 2 25 Selectively Reporting Of Data 216. 3 21 Second Submission Of Paper 84.7 27 Colleague Steals Discussed Idea 76.4 30 Skirting Manuscript Review Process 83. 5 28 Falling To Disclose Grant Sources 75.6 31 Not Reporting Income For Taxes 67. 3 32 Selling Desk Copies For Income 76.8 29 Falling To Cite Relevant Sources 61. 2 33 Whistleblower First Goes To Press 38. 3 39 Teaching Only Personal Viewpoint 44. 8 36 Placing Unread Paper On Vitae 39. 1 38 Reporting Only Significant Tests 50. 3 34 Falling To Devote Time To Project 45. 3 35 Submitting Favorable Evaluations 39. 5 37 Using Funds For Unrelated Project 31. 1 40 Collaborator Finishes Paper Alone 23. 3 42 Taking Supplies From Office 23.6 41 Five Papers Instead Of One 14.3 43 Writing Textbooks For Income 4. 5 44 Falling To Acknowledge Assistance 1.0 45 107 RANK-ORDERED SERIOUSNESS RATINGS OF CHEMISTRYSAMPLE Abbreviated Vignette Geomean Rank Making Up Data 4048.5 1 Publishing Fabricated Data 3363.7 2 Conspiracy to Falsify Data 3161.5 3 Fabrication Of Data 2918.4 4 Faculty Steals Student Paper 1914.3 5 Referee Steals Other's Idea 1069.3 9 Sexual Exploitation Of Student 954. 7 11 Reviewer Takes Idea For Proposal 1211.4 6 Bogus Papers On Vitae 947. 5 12 Makes Untrue Ethics Allegation 1135. 5 7 Stealing Colleague's Computer 1001.9 10 Misappropriation of Research Funds 901. 4 13 Pirating Others' Papers 398. 1 16 Lying About Degree To Get Job 811. 0 14 Suspect In Faking Destroys Data 1127.7 8 Slight Intentional Data Errors 536. 2 18 Untrue Allegation About Idea Theft 623. 0 15 Assistant Falls To Get Credit 570. 0 17 Falling To Report Sample Bias 276. 5 20 Refusing To Work With Minority 194. 5 25 Lying About Significance Level 239. 7 23 Fall To Disclose Original Data 259. 8 21 Using Ghostwriter Without Honesty 284.0 19 108 RANK-ORDERED SERIOUSNESS RATINGS OF CHEMISTRY SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 167.9 26 Director Demanding Authorship 161. 3 27 Selectively Reporting Of Data 253.6 22 Second Submission Of Paper 114.9 30 Colleague Steals Discussed Idea 225. 6 24 Skirting Manuscript Review Process 124. 5 28 Falling To Disclose Grant Sources 91. 2 33 Not Reporting Income For Taxes 123. 1 29 Selling Desk Copies For Income 87.0 35 Falling To Cite Relevant Sources 92. 2 32 Whistleblower First Goes To Press 61.9 37 Teaching Only Personal Viewpoint 88.6 34 Placing Unread Paper On Vitae 95. 9 31 Reporting Only Significant Tests 74.8 36 Falling To Devote Time To Project 43. 1 39 Submitting Favorable Evaluations 49, 7 38 Using Funds For Unrelated Project 29. 5 42 Collaborator Finishes Paper Alone 38. 6 40 Taking Supplies From Office 31.2 41 Five Papers Instead Of One 17. 2 43 Writing Textbooks For Income 5. 3 44 Falling To Acknowledge Assistance 1.0 45 109 RANK-ORDERED SERIOUSNESS RATINGS OF BIOLOGY SAMPLE Abbreviated Vignette Geomean Rank Making Up Data 2064.6 4 Publishing Fabricated Data 2126.1 3 Conspiracy to Falsify Data 2261.6 2 Fabrication Of Data 2365.4 1 Faculty Steals Student Paper 1562.3 5 Referee Steals Other's Idea 1312. 5 7 Sexual Exploitation Of Student 1346.5 6 Reviewer Takes Idea For Proposal 1000.1 11 Bogus Papers On Vitae 997. 4 12 Makes Untrue Ethics Allegation 906. 2 14 Stealing Colleague's Computer 1023.6 9 Misappropriation of Research Funds 1019.7 lO Pirating Others' Papers 1090.7 6 Lying About Degree To Get Job 947. 0 13 Suspect In Faking Destroys Data 600. 3 16 Slight Intentional Data Errors 670. 3 15 Untrue Allegation About Idea Theft 462.6 17 Assistant Fails To Get Credit 440. 5 16 Failing To Report Sample Bias 315. 4 22 Refusing To Work With Minority 320, a 21 Lying About Significance Level 324. 5 20 Fail To Disclose Original Data 269.7 23 Using Ghostwriter Without Honesty 214. 5 25 110 RANK-ORDERED SERIOUSNESS RATINGS OF BIOLOGY SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 409.6 19 Director Demanding Authorship 202. 6 26 Selectively Reporting Of Data 177.9 27 Second Submission Of Paper 272. 7 24 Colleague Steals Discussed Idea 172.0 28 Skirting Manuscript Review Process 135. 9 30 Falling To Disclose Grant Sources 131.8 32 Not Reporting Income For Taxes 133. 4 31 Selling Desk Copies For Income 155. 7 29 Falling To Cite Relevant Sources 76.4 35 Whistleblower First Goes To Press 101. 1 33 Teaching Only Personal Viewpoint 86.2 34 Placing Unread Paper On Vitae 71.7 36 Reporting Only Significant Tests 66. 6 37 Falling To Devote Time To Project 44.9 40 Submitting Favorable Evaluations 47. 5 39 Using Funds For Unrelated Project 25.9 42 Collaborator Finishes Paper Alone 53. 5 38 Taking Supplies From Office 37.6 41 Five Papers Instead Of One 18.9 43 Writing Textbooks For Income 9.0 44 Falling To Acknowledge Assistance 1.0 45 Ill RANK-ORDERED SERIOUSNESS RATINGS OF ECONOMICS SAMPLE Abbreviated Vignette Geomean Rank Making Up Data 743. 9 1 Publishing Fabricated Data 597.4 3 Conspiracy to Falsify Data 540.9 4 Fabrication Of Data 644.9 2 Faculty Steals Student Paper 475. 1 5 Referee Steals Other's Idea 373. 2 10 Sexual Exploitation Of Student 391.8 8 Reviewer Takes Idea For Proposal 314. 1 16 Bogus Papers On Vitae 465. 8 6 Makes Untrue Ethics Allegation 331. 9 14 Stealing Colleague's Computer 350. 6 11 Misappropriation of Research Funds 375.0 9 Pirating Others' Papers 340. 8 13 Lying About Degree To Get Job 297. 2 18 Suspect In Faking Destroys Data 346. 6 12 Slight Intentional Data Errors 412.0 7 Untrue Allegation About Idea Theft 316. 8 15 Assistant Falls To Get Credit 300. 6 17 Falling To Report Sample Bias 203. 5 21 Refusing To Work With Minority 215. 3 19 Lying About Significance Level 205.9 20 Fall To Disclose Original Data 182. 6 22 Using Ghostwriter Without Honesty 175. 5 23 112 RANK-ORDERED SERIOUSNESS RATINGS OF ECONOMICS SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 127. 3 26 Director Demanding Authorship 136. 3 24 Selectively Reporting Of Data 124. 3 26 Second Submission Of Paper 109. 9 29 Colleague Steals Discussed Idea 92.7 31 Skirting Manuscript Review Process 125. 3 27 Falling To Disclose Grant Sources 102. 3 30 Not Reporting Income For Taxes 135. 5 25 Selling Desk Copies For Income 92. 3 32 Failing To Cite Relevant Sources 61.4 36 Whistleblower First Goes To Press 74.8 33 Teaching Only Personal Viewpoint 56.9 38 Placing Unread Paper On Vitae 66. 4 35 Reporting Only Significant Tests 47. 9 40 Failing To Devote Time To Project 71.2 34 Submitting Favorable Evaluations 57.2 37 Using Funds For Unrelated Project 50.0 39 Collaborator Finishes Paper Alone 17.0 42 Taking Supplies From Office 40.3 41 Five Papers Instead Of One 10.0 43 Writing Textbooks For Income 4. 3 44 Failing To Acknowledge Assistance 1.0 45 113 RAHK-QRDERED SERIOUSNESS RATINGS OF SOCIOLOGY SAMPLE Abbreviated Vignette Geomean Rank Making Up Data 554. 4 2 Publishing Fabricated Data 535.7 4 Conspiracy to Falsify Data 570. 6 1 Fabrication Of Date 492.0 6 Faculty Steals Student Paper 536. 1 3 Referee Steals Other's Idea 455. 5 7 Sexual Exploitation Of Student 499. 5 5 Reviewer Takes Idea For Proposal 398.6 10 Bogus Papers On Vitae 399.4 9 Makes Untrue Ethics Allegation 365. 7 13 Stealing Colleague's Computer 388. 7 11 Misappropriation of Research Funds 334. 8 16 Pirating Others' Papers 424. 1 8 Lying About Degree To Get Job 347. 1 15 Suspect In Faking Destroys Data 313. 2 18 Slight Intentional Data Errors 352.0 14 Untrue Allegation About Idee Theft 366. 9 12 Assistant Falls To Get Credit 330. 6 17 Falling To Report Sample Bias 237. 1 20 Refusing To Work With Minority 254. 2 19 Lying About Significance Level 219. 2 21 Fall To Disclose Original Data 191. 9 24 Using Ghostwriter Without Honesty 209. 9 22 114 RANK-ORDERED SERIOUSNESS RATINGS OF SOCIOLOGY SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 183. 1 25 Director Demanding Authorship 207. 7 23 Selectively Reporting Of Data 143. 1 28 Second Submission Of Paper 170. 7 26 Colleague Steals Discussed Idea 110. 2 30 Skirting Manuscript Review Process 156. 8 27 Falling To Disclose Grant Sources 136. 2 29 Not Reporting Income For Taxes 93. 8 31 Selling Desk Copies For Income 80. 2 35 Falling To Cite Relevant Sources 80. 5 34 Whistleblower First Goes To Press 70.4 37 Teaching Only Personal Viewpoint 83. 3 33 Placing Unread Paper On Vitae 83. 5 32 Reporting Only Significant Tests 63.7 39 Falling To Devote Time To Project 7 3 . 0 36 Submitting Favorable Evaluations 53.9 40 Using Funds For Unrelated Project 6 8 . 5 38 Collaborator Finishes Paper Alone 33.0 42 Taking Supplies From Office 38.2 41 Five Papers Instead Of One 13.4 43 Writing Textbooks For Income 5. 1 44 Falling To Acknowledge Assistance 1.0 45 115 RANK-ORDERED SERIOUSNESS RATINGS OF PSYCHOLOGY SAMPLE Abbreviated Vignette Geomean Rank Making Up Data 503.4 3 Publishing Fabricated Data 566. 2 1 Conspiracy to Falsify Data 498.8 4 Fabrication Of Data 525. 5 2 Faculty Steals Student Paper 445. 1 6 Referee Steals Other's Idea 455. 5 5 Sexual Exploitation Of Student 435. 8 7 Reviewer Takes Idea For Proposal 369. 1 8 Bogus Papers On Vitae 368. P. 9 Makes Untrue Ethics Allegation 359. 4 10 Stealing Colleague's Computer 310. 6 15 Misappropriation of Research Funds 263. 9 17 Pirating Others' Paper# 343. O 11 Lying About Degree To Get Job 325. 7 12 Suspect In Faking Destroys Data 309. 5 16 Slight Intentional Data Errors 320. 4 14 Untrue Allegation About Idea Theft 324. 4 13 Assistant Fails To Get Credit 231. 7 18 Failing To Report Sample Bias 209. 5 21 Refusing To Work With Minority 165. 4 24 Lying About Significance Level 226.4 19 Fail To Disclose Original Data 219. 4 20 Using Ghostwriter Without Honesty 208. 0 22 116 RANK-ORDERED SERIOUSNESS RATINGS OF PSYCHOLOGY SAMPLE Abbreviated Vignette Geomean Rank Multiple Publication 145.9 25 Director Demanding Authorship 171.8 23 Selectively Reporting Of Data 130. 2 26 Second Submission Of Paper 116. 7 27 Colleague Steals Discussed Idea 100. 3 29 Skirting Manuscript Reviev Process 101. 7 28 Failing To Disclose Grant Sources 100. 3 30 Not Reporting Income For Taxes 77. 5 34 Selling Desk Copies For Income 81. 8 32 Failing To Cite Relevant Sources 78. 5 33 Whistleblower First Goes To Press 84.2 31 Teaching Only Personal Viewpoint 65. 5 37 Placing Unread Paper On Vitae 73. 5 35 Reporting Only Significant Tests 72. 2 36 Failing To Devote Time To Project 62. 1 39 Submitting Favorable Evaluations 59. 3 40 Using Funds For Unrelated Project 62.4 38 Collaborator Finishes Paper Alone 36. 8 41 Taking Supplies From Office 31. 5 42 Five Papers Instead Of One 15.9 43 Writing Textbooks For Income 4. 8 44 Failing To Acknowledge Assistance 1.0 45 LIST OF REFERENCES Al-Thakeb. Fahad and Joseph E. Scott 1981 "The perceived seriousness of crime in the Middle East." International Journal of Applied end Comparative Criminal Justice 5: 129-143. Babbage, Charles 1830 Reflections on the Decline of Science in England. London. Barber, Bernard 1952 Science and the Social Order. New York: The Free Press. Becker, Howard S. 1963 Outsiders: Studies in the Sociology of Deviance. New York: Free Press. Ben-Yehuda, Nachman 1985 Deviance and Moral Boundaries. Chicago: University of Chicago Press. Beveridge, William 1961 The Art of Scientific Investigation. New York: Vintage Books. Black, Donald 1976 The Behavior of Law. New York: Academic Press. Blackstone, Sir William 1880 Commentaries on the Laws of England. London: Murray. Blalock, Hubert M. 1977 Social Statistics. New York: McGraw-Hill. 117 118 Boffey, Philip M. 1986 Major study points to faulty research at two universities." New York Times, April 22: Cl. Borek, E. 1975 "Cheating In Science." New York Times (January 22) cited In J. Swazey and S. Scher, "The Whistleblower as a Deviant Professional : Professional Norms and Responses to Fraud In Clinical Research," In J. Swazey and S. Scher, Whistleblowing In Biomedical Research. Washington, D.C.: U. S. Government Printing Office. Braunvald, Eugene 1987 "On Analysing Scientific Fraud." Nature 325: 215-216. Bridges, George and Nancy Llsagor 1975 "Scaling Seriousness: An Evaluation of Magnitude and Category Scaling Techniques.' Journal of Criminal Law & Criminology 66 (2) 215-221. Broad, William 1981a "The publishing game: Getting more for less." Science 211: 1137-39. Broad, William 1981b "Fraud and the structure of science." Science 212: 137-141. Broad, William 1981c "Congress told fraud Issue 'exaggerated.'" Science 212: 421. Broad, William 1982 "Crisis In publishing: Credit or credibility." BloSclence 32 (8): 645-? Bread, William and Nicholas Wads 1982 Betrayers of the Truth. New York: Simon and Schuster. Budlansky, Stephen 1985 "New ways of shading the truth." Nature 315: 447. 119 Clinard, Marshall B. 1946 "Criminological theories of violations of wartime regulations. ” American Sociological Review 11: 256-270. 1983 Corporate Ethics and Crime. Beverly Hills, CA: Sage Publications. Coleman, James S. 1974 Power and the Structure of Society. New York: W. W. Norton. Cressey, Dc.iald R. 1953 Other People's Money: The Social Psychology of Embezzlement. New York: The Free Press. Cullen, Francis T., Bruce G. Link, and Craig W. Polanzi 1982 "The seriousness of crimes revisited. " Criminology 20 (1):83-102. Cullen, Francis T. , Bruce G. Link, Lawrence F. Travis, III, and John F. Wozniak 1985 "Consensus in crime seriousness: Empirical reality or methodological artifact?" Criminology 23 (1): 99-118. Culliton, Barbara 1974 "The Sloan-Kettering affair (II): An uneasy resolution." Science 184: 1154-1157. 1983a "Fraud inquiry spreads blame." Science 219: 937. 1983b "Coping with fraud: The Darsee case." Science 220: 31-35. 1983c "Emory reports on Darsee's fraud." 220: 936. Dorfman, D. D. 1978 "The Cyril Burt question: New findings." Science 201: 1177-1186 cited in Nachman Ben-Yehuda, Deviance and Moral Boundaries. Chicago: University of Chicago Press, 1985. Edelhertz, Herbert 1970 The Nature, Impact, and Prosecution of White-Collar Crime. Washington, DC: U. S. Government Printing Office. 120 Erickson, Maynard L. and Jack P. Gibbs 1979 "On the perceived severity of legal penalties.” Journal of Criminal Lav & Criminology 70 <1); 102-116. Ermann, M. David and Richard J. Lundman 1982 Corporate and Governmental Deviance. New York: Oxford University Press. Evans, Sandra S. 1981 Measuring the Seriousness of Crime: Methodological Issues and a Cross Cultural Comparison. Unpublished Ph. D. Dissertation, The Ohio State University. Figlio, Robert M. 1975 "The seriousness of offenses: An evaluation by offenders and nonoffenders." Journal of Criminal Law and Criminology 66 (2):189-200. Form, William 1988 "Editor's comment. " American Sociological Review 53 <3): vii. Garfield, Eugene 1981 "From citation amnesia to bibiographic plagiarism." Current Contents-Life Sciences 23 (23): 5-9. Geis, Gilbert 1967 "The Heavy Electrical Equipment Antitrust Cases of 1961." In Marshall Clinard and Richard Quinney, eds., Criminal Behavior Systems, New York: Holt, Rinehart and Winston. Gottfredson, Stephen D., Kathy L. Young, and William S. Laufer 1980 "Additivity and interactions in offense seriousness scales.” Journal of Research in Crime and Delinquency 17: 26-41. Hirschi, T?ovi« 1969 Causes of Delinquency. Berkeley, CA: University of California Press. 121 Holden, Constance 1988 "Whistle-blowers air cases at house hearings." Science 240: 386-387. Hsu, Marlene 1973 "Cultural and sexual differences on the judgment of criminal offenses: A replication study of the measurement of delinquency." Journal of Criminal Law & Criminology 64: 348-353. Kerlinger, Fred N. 1973 Foundations of Behavioral Research. New York: Holt, Rinehart and Winston. Lemert, Edwin M. 1951 Social Pathology. New York: McGraw-Hill. McCleary, Richard, Michael J. O'Neil, Thomas Epperlein, Constance Jones, and Ronald H. Gray 1981 "Effects of legal education and work experience on perceptions of crime seriousness.” Social Problems 28: 276-289. Mahoney, Michael J. and Terrence P. Kimper 1976 "From ethics to logic: A Survey of Scientists," in Michael J. Mahoney, Scientist as Subject: The Psychological Imperative. Cambridge, MA. : Ballinger Publishing Co. Makela, Klaus 1966 "Public sense of justice and judicial practice.” Acta Sociologica 1C:42*C7. Merton, Robert K. 1962 "Priorities in scientific discovery: A chapter in the sociology of science.” American Sociological Review 22: 635-659 reprinted as pp. 447-485 in Bernard Barber and Walter Hirsch, eds., The Sociology of Science. New York: The Free Press, 1962. 1973 The Sociology of Science: Theoretical and &mpiricaJ Investigations. Chicago: University of Chicago Press. 122 Mills, C. Wright 1959 The Sociological Imagination. New York: Oxford University Press. Panati, C. with M. McPherson 1976 "An epitaph for Sir Cyril?" Newsweek 88 Petersdorf, Robert 1986 "The pathogenesis of fraud in medical science." Annals of Internal Medicine 104: 252-254. Price, June 1985 "A survey of researchers' attitudes toward scientific fraud. " Paper presented at t';. 1985 meetings of the American Associatio- for the Advancement of Science, Los Angeles. fcenniii, Ysnbei 1978 The Search for Criminal Man. Lexington, MA: Lexington Books. Riedel, Marc 1975 "Perceived circumstances, inferences of intent and judgments of offense seriousness." Journal of Criminal Law & Criminology 66: 201-208. Roberts, Leslie 1983 "Harvard's handling of fraud: Good intentions are not enough." BioScience 33: 358-364. Rossi, Peter H., Emily Waite, Christine E. Bose, and Richard E. Berk 1974 "The seriousness of crimes: Normative structure and individual differences. " American Sociological Review 39: 224-237. 123 Roth, Jeffrey A. lS7w "ProÊëoutor perceptions of crime seriousness." Journal of Criminal Lav & Criminology 69: 232-242. Scheff, Thomas J. 1966 Being Mentally 111. Chicago: Aldine. Schmaus, Warren 1983 "Fraud and the norms of science." Science, Technology, and Human Values 8: 12-22. Schrager, Laura Shill and James F. Short, Jr. 1978 "Toward a Sociology of Organizational Crime." Social Problems 25: 407-419. 1980 "How serious a crime? Perceptions of organizational and common crimes." In Gilbert Geis and Ezra Stotland (eds.>, White-Collar Crime: Theory and Research. Beverly Hills, CA: Sage Publications. Schur, Edwin M. 1971 Labeling Deviant Behavior: Its Sociological Implications. New York: Harper & Row. Secrest, Dale K. 1969 "Comparisons of inmates' and staffs' judgments of the severity of offenses." Journal of Research in Crime and Delinquency 6:41-55. Sellin, Thorsten and Marvin E. Wolfgang 1964 The Measurement of Delinquency. New York: John Wiley & Sons. Shaw, Peter 1982 "Plagiary." The American Scholar 51: 325-337. Shinn, A. 1974 "Relations between scales." In Hubert Blalock (ed. ), Measurement in the Social Sciences. Siegel, Sidney 1956 Nonparametric Statistics for the Behavioral Sciences. New York: McGraw-Hill. 124 Smith, R. 1985 "Scientific fraud probed at AAAS meeting." Science 228: 1292-1293. Steneck, M. 1984 "Commentary: The university and research ethics." Science, Technology, and Human Values 9: 6-15. Stevens. S. S. 1986 Psychophysics. New Brunswick, NJ: Transaction Books. Stewart, Walter and Ned Feder 1986 "Why research fraud thrives." Boston Sunday Globe, November 30: A21, A24. 1987 "The integrity of the scientific literature." Nature 325: 207-214. St. James-Roberts 1976 "Cheating in science." New Scientist 72: 466-469. Sutherland, Edwin H. 1940 "White-collar criminality." American Sociological Review 5: 1-12. 1949 White Collar Crime. New York: Dryden Press. Swazey, Judith P. and Stephen R. Scher 1982 Whistleblowing in Biomedical Research. Washington, D.C: President's Commission for the Study of Ethical Problems in Medicine and Biomedical and Behavioral Research. Tangney, June Price 1987 "Fraud will out — or will it?" New Scientist August 6: 62-63. Wade, Nicholas 1976 "IQ end heredity: Suspicion of fraud beclouds classic experiment." Science 194: 916-919. 125 Wagner, Hugh and Kenneth Pease 1978 "On adding up scores of offence seriousness." British Journal of Criminology 18: 175-178. Walker, Monica A. 1978 "Measuring the seriousness of crimes." British Journal of Criminology 18: 348-364. Weis, Joseph G. 1987 "From the editor: Special issue on theory." Criminology 25 <4): 783-784. Westin, Alan F. 1981 "Commentary: Whistleblowing, Due Process, and 'Institutional Tarpaper." In J. Swazey and S. Scher, eds., Whistleblowing in Biomedical Research. Washington, D. C. : President's Commission for the Study of Ethical Problems in Medicine and Biomedical and Behavioral Research, 1982. wheeler, David 1987 "2 universities chastised on fraud investigations." The Chronicle of Higher Education 33 <38): 1,7. 1988 "Lawmakers question efficiency of probes of scientists' conduct." The Chronicle of Higher Education 34 (32):A1,8 Wilson, Logan 1942 The Academic Man: A Study in the Sociology of a Profession. New York: Oxford University Press. Woolf, Patricia 1981 "Fraud in science: How much, how serious?" The Hastings Center Report 11 (5): 9-14. Zuckerman, Harriet 1977 "Deviant behavior and social control in science." In Edward Sagarin, ed., Deviance and Social Change. Beverly Hills, CA: Sage Publications. 1984 "Norms and deviant behavior in science." Science, Technology, and Human Values 9: 7-13.