Networks, Creativity and the Finest in Jazz 1939-1979

David Grandadam* BETA, Université de Strasbourg, France

Abstract

Creativity is commonly viewed as a collective process involving the coordination of a variety of individuals who interact in a dense network and influence one another through time. In this paper, the evolution of the network of collaboration among artists in the particular case of the Blue Note jazz label is studied. By analyzing the extent to which the collaboration structure relies on a star production model and the extent to which it relies on integrated and cohesive groups, the question raised is how the label has matched its artistic efforts with its commercial preoccupations. The results show that, over time, the Blue Note label has been able to ideally combine creative talents as well as established stars, by relying on an important “family” of musicians. These artists have all played a major role in connecting the Blue Note network, and have all widely contributed to shape the evolution of jazz.

* Direct correspondence to David Grandadam, BETA, Université de Strasbourg, 61 Avenue de la Forêt Noire, F-67085 Strasbourg Cedex. Email: [email protected] An earlier draft of this paper has been presented in London and in Paris to members of the DIME network. The author would like to thank all those who contributed to enhance this paper with their helpful comments. I'm gonna stay with the youngsters. When these get too old, I'm gonna get me some younger ones… Keeps the mind active.

Art Blakey, A Night at Birdland, Blue Note, 1954.

INTRODUCTION

Jazz, maybe more than any other musical genre, is characterized by a wide diversity of styles.1 Swing, bebop, cool, free, funk-soul, or fusion, are just a few of them, among many others. Famous pioneers such as Louis Armstrong, Duke Ellington, Charlie Parker, Miles Davis, or John Coltrane have played an important part in changing the trajectories of jazz. However, they could not have fully succeeded without the efforts of many fellow musicians, and without the support of labels such as Riverside, Prestige or Savoy, which have all contributed to the expansive institutionalization of the various jazz styles. As it is the case for most art forms, the ongoing creativity characterizing jazz is truly the result of a collective process involving the coordination of many different entities (Becker, 1982; Bourdieu, 1993; White, 1993).

One label in particular stands out in jazz history: the well-known Blue Note label – with its wide range of talented musicians, its genuine and influential cover art, and, most importantly, with its beloved and characteristic sound. The Blue Note story ideally illustrates how a label has been able to successfully promote many different styles and significantly change jazz music, by bringing together, in a broad network of collaboration, many of the most creative musicians of the post-war jazz scene. This network directly reflects the label’s musical endeavors, and, therefore, can serve as an example to better understand the general mechanisms of cultural production.2 We analyze this network throughout this study.

Labels play a major role in defining the evolutionary paths of music genres and styles, throughout the artists they represent (Peterson, 1997; Dowd, 2003; Lena, 2006; Negus, 1999; Tschmuck, 2006). On one hand, they enable these artists to connect to each other, share their ideas, influence each other and perform together in sessions, and therefore are main repositories for the accumulation, combination, enrichment, and renewal of creative expression. On the other hand, because they are responsible for the creations launched on the market, labels behave as traditional profit-oriented organizations and will therefore try to benefit from the work of the most prolific artists. In this perspective, understanding how artists are pooled together in time, as well as the mechanisms driving the creation of links, is the key to understanding the extent to which the label is driven by the artistic exploration of

1 In reference to the work of Neale (1980) on the film industry, we use the word genre to refer to distinctive categories of music, such as rock, rap, dance, world music, jazz and so on. We use the term style to describe different subgenres. 2 Systems of cultural production have been studied by several authors, who propose to view these systems as driven by symbolic representations, in which innovative forms progressively replace the older ones, therefore leading to cycles of creation (Hirsch, 1972; Peterson and Berger, 1975; DiMaggio, 1987; Lena and Peterson, 2008).

1 new talents, and the extent to which it is driven by the commercial exploitation of existing stars.3

In this study, we analyze the evolution of the Blue Note collaboration network among artists, by focusing on how the label has been able to overcome the problem of balancing both artistic and economic logics of practice. In order to do so, we examine how the different artists were combined in time, by testing two different models of network evolution, which each rely on different structures of interaction. Our aim is not to solely test the efficiency of specific network architectures in an industry, but rather to study how individual prestige and collective behavior can be blended in order to ensure the successful exploration and exploitation of creative ideas. In other words, using the example of the Blue Note label, we focus on the structural processes allowing for common understandings as well as creative sparks to emerge within a competitive context.

The evolving topology resulting from the multiple interactions among these individuals points out to several mechanisms that may explain the emergence of specific patterns of collaboration in the world of music. The network structure directly reflects the label’s attempts to promote a large number of artists with very different musical expressions, which all remain, however, very much linked to each other. Over time, the Blue Note network exhibits higher levels of relative cohesiveness and integration, with the progressive rise of highly connected artists. These stars occupy a central position in the network, and have played a major role in the creation, diffusion and success of jazz. We discuss their structural characteristics throughout this work.

COLLABORATION AND CREATIVITY

Since the seminal work of Granovetter (1973, 1985), social embeddedness is considered as a major driving force of economic action. This assumption has led to an important body of theoretical and empirical research, which has helped uncover steady generic properties of real networks, and which has contributed to show the importance of social structure on the acquisition and allocation of resources (see Feld, 1981; DeNora, 1991; Padgett and Ansell, 1993 for examples).

Several researchers have studied art worlds using social network analysis. In their work, Gleiser and Danon (2003) for example, who focus on the collaborations among artists during the swing era, observe significant correlations between recording locations, racial segregation and community structure. Smith (2006), who analyzes the collaboration network for rap music, finds evidence of rivalry among the highly connected (and most popular) artists, in contrast to most social networks. These art worlds share strong similarities with the scientific networks of collaboration, as portrayed by Newman (2001) in physics, Moody (2004) in sociology, Powell et al. (2005) in the life sciences, and Goyal et al. (2006) in economics.4 We

3 The tension existing between the world of art and the world of commerce, as well as the role of labels as intermediate structures linking the artists to the market for creative goods and services, are described by Caves (2000). 4 Creativity in the worlds of art and science share strong similarities one with another, as depicted, for example, in the works of Koestler (1964), Rothenberg (1979), or Sawyer (2006).

2 rely on their findings in order to carry out our analysis.

Drawing more specifically on the work of Moody (2004), we expect two major mechanisms to drive the evolution of networks of collaboration in the particular case of jazz labels. The first mechanism driving this evolution is related to the label’s economic and commercial motivations, while the second mechanism is related to its artistic motivations.

Some individuals are generally much more favored than others. Art worlds, and labels in particular, commonly rely on major ‘stars’ with a considerable reputation. In most cases, these artists appear on more sessions, sell more records, and therefore are relatively advantaged in terms of revenue (Rosen, 1981; MacDonald, 1988; Anderson, 2006). These stars would be expected to occupy a central position in the collaboration network, which would allow them to be much more influential than their poorly connected counterparts. Through time, more and more artists would be expected to collaborate with these high status artists in order to increase their own status, as it is the case for academic researchers (Merton, 1973; Allison et al., 1982). The connected stars should therefore progressively reinforce their position, leading to important inequalities among the different individuals. This mechanism, also known as preferential attachment, is the main feature of scale-free networks (Barabasi and Albert, 1999). If the label relied exclusively on a star system, the resulting network would be expected to behave as a scale-free network, favoring a small number of artists responsible for connecting the network and guaranteeing the economic viability of the label with their success.

By contrast, as artists gradually contribute to create new styles, they often turn to fellow musicians who share similar tastes and expressions. Artists should therefore be expected to have strong links with a small group of individuals, with whom they share the same desire to pusjh the boundaries of their art, while keeping weak links with more distant individuals in order to stay connexcted to what is done on the outside. In other words, the resulting network should therefore be made up of important clusters (or ‘islands’) encompassing each style, with a few connections between these clusters uniting the different artistic areas together. This phenomenon is well illustrated in the small world model, which has proven to be efficient fostering creative activities (for specific examples, see Watts and Strogatz (1998); Kogut and Walker, 2001; Baum et al., 2003; Davis et al., 2003). The power of these networks relies on their ability to bridge different groups together, in such a way that close-knit clusters can benefit from the necessary connectivity to nurture their new ideas on one hand, and from their proximity with other clusters to reach creative material on the other hand (Burt, 2004; Uzzi and Spiro, 2005). These small-world networks should offer each label the possibility to develop variety and specialization simultaneously and should therefore be expected to greatly influence the collective process of creation.

In short, we analyze the extent to which a star production model governs the evolution of a creative network in a specific organization, in which case the label is rather committed to its commercial ambitions, and the extent to which this evolution is dependent on small-world behavior, in which the case the label is more oriented towards artistic achievement. In other words, we examine how a successful label has combined artistic and economic values – which are generally considered to be incompatible – by matching individual reward and prestige with collective action and creativity.

Both these worlds rely on the development of new esthetic forms, through the exploration and exploitation of a broad body of knowledge dispersed in social structure.

3

THE BLUE NOTE SUCCESS STORY

Blue Note is probably the most representative label of the evolution of jazz, not only because most of the main jazz artists have recorded for the label, but also because it has captured a diversity of styles that no other jazz label can claim to have fully reviewed (Cook, 2003). Blue Note has been a benchmark label throughout the 20th century, and is still, to this day, an active player on the jazz scene – as suggested by the enormous success of Grammy award winner Norah Jones, in 2002. In fact, it is one of the only jazz labels to have frequently reached the Top 200 Billboard charts in the sixties and in the seventies, at a time where the rock n’roll business far outweighed the jazz sales.

Blue Note was founded in 1939, in New York, by German migrants Alfred Lion and Francis Wolff. Originally focusing on traditional hot jazz and swing, with artists like Albert Ammons and Meade Lux Lewis, Blue Note released its first hit a few months after its establishment with a performance by clarinetist Sidney Bechet. The label rapidly became known for treating musicians particularly well, allowing them to intervene in all aspects of production. The way the label honored the artists soon became the Blue Note landmark, and translated into an unconditional passion and devotion for jazz. This commitment to the music, as well as the desire to document at best the evolution of jazz, has always been the main goal of the label, as illustrated on a 1939 flyer for one of Blue Note’s early releases:

“Blue Note records are designed simply to serve the uncompromising expression of hot jazz and swing, in general. Any particular style of playing which represents an authentic way of musical feeling is genuine expression. By virtue of its significance in place, time and circumstance, it possesses its own tradition, artistic standards and audience that keeps it alive. Hot jazz, therefore, is expression and communication, a musical and social manifestation, and Blue Note Records are concerned with identifying its impulse, not its sensational and commercial adornments.”

By the end of World War II, after having ceased to record for a few years, and despite the critics, the Blue Note label started to focus on bebop with artists like Ike Quebec, Tadd 5 Dameron, Fats Navarro, Howard McGhee, and James Moody. These artists were not the main innovators of the era, which is why the label was never really associated to the style created by Charlie Parker and Dizzy Gillespie (who both had contracts with other labels, like Dial, Savoy and Verve). Between 1947 and 1952, however, Blue Note released the first recordings of pianist Thelonious Monk as a leader, which did not sell well at the time, but have since come to be considered as some of the most important records of the bebop style. Until 1954, Blue Note recorded sessions with other important bebop artists, such as Bud Powell, J.J. Johnson or Miles Davis, but by then, hard bop, which Blue Note is most commonly affiliated to, was diffusing rapidly, with several releases from The Jazz

5 The progressive transition from swing to bebop has been extensively described by Lopes (2002) and DeVeaux (1997). This was not achieved easily as many of the swing artists and their disciples strongly criticized the new art form developed by Charlie Parker among others. In fact, bebop did not suddenly emerge as a new musical expression. Instead, as suggested by Wang (1973), both swing and bebop coexisted together all through the forties, with artists like Charlie Parker or Dizzy Gillespie participating in swing sessions while integrating new elements in their solos. These artists were able to blend together two musical traditions, therefore contributing to the unity and cohesiveness of jazz.

4 Messengers, a group led by drummer Art Blakey and pianist Horace Silver, both considered as the founders of the movement. Art Blakey and Horace Silver soon became the main artists of the label and were to remain devoted to Blue Note for many years (Rosenthal, 1992).

During the fifties, new talents, such as Milt Jackson (founder of the Modern Jazz Quartet), or Clifford Brown (who first recorded with the Jazz Messengers) were starting to emerge. With the help of sound engineer Rudy Van Gelder (who contributed to most records of the fifties and the sixties), Blue Note distinguished itself from other independent jazz labels of the time, such as Prestige or Riverside, by paying for rehearsals prior to the recording sessions. This allowed Blue Note to considerably enhance the quality of its recordings and has probably contributed to its success.

The organist Jimmy Smith, who began as a leader in 1956, was the first Blue Note artist to enter the charts in 1962. This eventually opened the way to several other hard bop musicians like Lee Morgan, Donald Byrd, Lou Donaldson, or Stanley Turrentine, among the most successful. All through the late fifties and early sixties, some of the most important artists of the era recorded their debut albums for the label (among which Cannonball Adderley, Sonny Rollins, Dexter Gordon, Kenny Burrell, Kenny Dorham, Hank Mobley, Jackie McLean, Freddie Hubbard, Herbie Hancock, Wayne Shorter, Ron Carter, Grant Green, Joe Henderson and many others). These artists are all considered to be part of the Blue Note ‘family’. They often started off as sidemen for the Jazz Messengers, before recording their own work as leaders, and would commonly participate on each other’s albums (Goldsher, 2002). This process gave the label the opportunity to benefit from an important pool of successful artists, who played an important part in the institutionalization of hard bop. During that period, the label scored several major hits, and therefore also benefited from its wide exposure to enrich its catalog. The label could thus focus on the acts of established musicians, as well as the recordings of more novel artists, who all contributed, in their own way, to create the Blue Note sound and signature.6

Lion thought it was important to document the new developments in jazz, and therefore also recorded some of the leading artists of the avant-garde and free jazz movement. After having released the first album by John Coltrane as a leader (the well-known Blue Train), the label recorded musicians such as Andrew Hill, Eric Dolphy, Ornette Coleman, Cecil Taylor or Bobby Hutcherson. These artists did not sell like some of the hard bop records, but have made some major pieces of work, which have significantly altered the history of jazz.

In 1965, the Blue Note label was sold to Liberty Records, and therefore ceased to be independent. Soon after, in 1967, Lion retired, leaving Francis Wolff and pianist Duke Pearson as the main producers. Liberty Records was purchased by United Artists two years later. All through the seventies, although Blue Note still benefited from a certain commercial success, some of the main rules that had helped characterize the label’s specificity were being questioned. Many critics have considered this period as a rather uncreative era in terms of artistic achievments. This is probably what led the EMI executives to phase out the Blue Note label in 1979, after having acquired United Artists. The label was however revived six years

6 The well-known cover art of Reid Miles, who started working for the label in 1956, has significanty contributed to forge the image of Blue Note. In fact, because of their unique character, most Blue Note releases are easily recognizable and have gained an important reputation among collectors, fans and many others. The Blue Note artwork has since influenced the covers of many recordings.

5 later, in 1985, and has since released the work of several new artists, as well as a series of re- issues of past recordings.

The Blue Note label has recorded a variety of young talents and well-established musicians, who can all be associated to several different styles, but who have all contributed to define the Blue Note specificity. By frequently interacting together in various sessions, these artists have all benefited from the influence of many others to individually and collectively develop specific artistic expressions. For this reason, the Blue Note label should be considered as having evolved according to the changes in the collaboration pattern among artists, as some were replaced in time, while others were gradually reinforced. This process of creation is expected to be the main reason for the Blue Note success.

DATA AND METHODS

We analyze the evolution of the Blue Note network during the period from 1939 to 1979, using data we collected from the Jazz Discography Project.7 The dataset was modified to prevent different individuals from appearing with the same name or the same individual from appearing with different names.8 Overall, a total of 1349 sessions and 1942 individuals were included in our dataset. For each year, we constructed a cumulated network of collaboration, where the different artists who have recorded for the label represent the nodes in the network, and a link exists between two artists if they both played together in the same session. In other words, we constructed the affiliation network, in which artists are connected to each other by common membership in sessions, also known as the unipartite projection of the bipartite graph linking the artists to the sessions they participated in. As we consider the cumulated network, once a link is established, it remains active for the entire period.9 At each time step, we therefore obtain a single network characterizing the multiple interactions that each artist has had with others since the label’s foundation in 1939.

The set of individuals with whom an artist has collaborated forms the artist’s neighborhood. The number of artists an individual is linked to is referred to as the individual’s degree. The average degree of the network, at a specific time, is simply the average size of all the artists’ neighbordhoods. We can compute the degree distribution by measuring the probability that an individual has a degree higher than a specific value. The collaboration network behaves as a scale-free network if this distribution decays with a power law tail. In this case, the distribution should appear as a straight line in a log-log scale, suggesting that the probability of having a very small number of connections is very high, whereas the probability of having a very large number of connections is very low.

7 http://www.jazzdisco.org 8 In order to correct our dataset, we relied on the information available in the Allmusic Guide to Jazz (Bogdanov et al., 2002), as well as in The Encyclopedia of Jazz (Feather, 1960, 1966; Feather and Gitler, 1976). 9 Considering the cumulated network enables us to have a clear view of how artists connect to each other on a fairly long term, which could not be possible if we had studied an evolving time frame. The cumulated network, because it represents more individuals, is also more representative of the global interaction structure characterizing jazz, and therefore contains some information, which we would probably lose if we progressively suppressed the older nodes.

6

At a specific time, the (geodesic) distance between two individuals in a network is given by the length of the shortest path between them, corresponding to the shortest number of intermediate artists linking both of them. In other words, if two artists participated in the same session, the distance between both individuals equals 1. If both individuals have collaborated with a third individual, but have not played together, then the distance between the two artists is 2, and so forth. The maximum distance separating two individuals is called the diameter of the network. Two individuals are said to belong to the same component if and only if a path exists between them. The main component in the network is the one that connects the highest number of individuals. When the network is fully connected, we can compute the weighted average path length of the network for each period, which is simply the average number of steps along the shortest paths for all possible pairs of nodes in the network.

The clustering coefficient shows the extent to which the neighbors of an individual collaborated among each other. In other words, it defines the percentage of transitive triads in a network, where transitivity represents the fact that if a tie exists between artists A and B and between A and C, then B and C are connected together. The clustering coefficient for the entire network corresponds to the number of closed triangles in the network (such that three links can be found among three artists) over the number of connected triples in the network (with only two links connecting three individuals). If the actual clustering coefficient is equal to 0, then there is no clustering, and if it is equal to 1, the network is fully clustered. As we study the unipartite projection of a bipartite graph, this coefficient describes whether artists tend to participate in sessions with the same individuals, or whether these artists play with many different individuals in each session. The level of clustering therefore indicates the extent to which sessions overlap.

In order to study whether the collaboration network is a small-world, we compare the observed level of clustering and the average path length with the same parameters in the case of a random network of equal size (for which clustering and distances are expected to be low) as suggested by Watts (1999). We rely on the Newman et al. (2001) solution to correct the estimates of these parameters for random bipartite graphs, as in the work of Uzzi and Spiro (2005). The network will be said to exhibit increasing small-world behavior, the lower the relative average path length and the higher the relative clustering level. We therefore compare the values we obtain for these coefficients in our empirical analysis with those obtained for the random network by calculating a path length ratio, as well as a clustering coefficient ratio. The closer the path length ratio is to 1, the shorter distances are among connected artists. In the same way, the more the clustering coefficient exceeds 1, the higher the amount of clustering in the network. These two ratios are finally combined to measure a small-world quotient. As this quotient grows and exceeds 1, the network becomes more interconnected, which means that more ties between clusters will form, therefore leading to higher levels of group overlap. We should expect this quotient to increase over time whenever the network of collaboration is driven by the small-world effect.

THE EVOLUTION OF THE COLLABORATION NETWORK

In this section, we present our main results. We begin by presenting the main recording trends characterizing the label and provide descriptive statistics on the artists and sessions in the network. We then turn to the main structural features of the Blue Note network and their

7 evolution in time, by testing whether the network behaves as a scale-free or nework or whether it behaves as a small-world network. Rather than studying each year separately from 1939 to 1979, we concentrate on ten-year intervals, which gives a relatively clear insight on the different trends we observe throughout the entire period of analysis.

RECORDING TRENDS

Over the period we study, the Blue Note has recorded many different sessions, with many different combo sizes. Out of the 1349 sessions that are considered in this study, 23 were solo performances, while 191 sessions grouped more than 10 individuals at the same time. The most frequently used combo is the quintet (with 366 sessions), followed by the sextet (with 207 sessions) and by the quartet (with 200 sessions).

Unsurprisingly, artists have not equally participated to these sessions. Most of them have indeed played in no more than 1 or 2 sessions, and only 197 artists have played in more than 10 sessions. On average, each artist participated in approximately 5 sessions. This number is much higher than the median value of 2, meaning that the most prolific artists have a tendency to be much more so than the majority of other individuals. The artist that played in the largest number of sessions is Lee Morgan, with 103 sessions. He is followed by Art Blakey, who recorded 99 sessions for Blue Note, and by Grant Green, who recorded 96 sessions for the label.

Table 1: Recording trends

Combo size Quantity Percentage Sessions per artist Quantity Percentage All 1349 100 % All 1942 100 % Solo 23 1.7 % 1 746 38.4 % Duo 16 1.2 % 2 346 17.8 % Trio 116 8.6 % 3 199 10.2 % Quartet 200 14.8 % 4 152 7.8 % Quintet 366 27.1 % 5 94 4.8 % Sextet 207 15.3 % 6 65 3.3 % Septet 98 7.3 % 7 60 3.1 % Octet 54 4.0 % 8 23 1.2 % Nonet 44 3.3 % 9 30 1.5 % Dectet 34 2.5 % 10 30 1.5 % Big Combos (> 10) 191 14.2 % 11 and more (> 10) 197 10.4 %

Average 7.01 — Average 5.02 — Std Deviation 5.06 — Std Deviation 9.54 — Median Quintet — Median 2 —

Note: In this table, the figures are those obtained for the entire period of analysis, from 1939 to 1979.

ARTISTS AND SESSIONS

Each year, new sessions are recorded and ‘new’ artists (who have not previously worked for the label) are added to the network. This process significantly affects the global structure of collaboration among individuals, and therefore should be analyzed carefully. We present, in

8 Table 2, the number of new sessions and the number of new artists for each time period.

Although we expected that these two quantities might be correlated in some way or another, the results clearly show that this is not always the case. In other words, more new sessions do not necessarily entail more new artists. From 1939 to 1979, the label recorded on average 32 sessions per year, with a peak in 1969, during which 83 sessions were put together. A majority of sessions were recorded during the sixties, which corresponds to the most prolific era for the label. During that period, Blue Note did not introduce many new artists, generally relying on those individuals that had helped create its specific sound. Hard bop was then at its peak and the main artists were well established in the Blue Note family. For the entire time interval we study, 46 individuals on average were added to the network each year, with the biggest change in 1976, corresponding to a total of 177 new members.

Table 2: Descriptive statistics

1949 1959 1969 1979 Number of sessions 101 411 1011 1349 Percentage of total 7.5 % 30.5 % 74.9 % 100 % Absolute variation over the period 101 310 600 338 Relative variation over the period + 100 % + 306.93 % + 145.99 % + 33.43 %

Number of artists 226 662 1212 1942 Percentage of total 11.6 % 34.1 % 62.4 % 100 % Absolute variation over the period 226 446 550 730 Relative variation over the period + 100 % + 192.92 % + 83.08 % + 60.23 %

Average degree of artists 8.67 11.54 16.07 23.07 Std Deviation 5.5 10.61 18.39 26.56 Minimum degree 0 0 0 0 Maximum degree 33 121 141 250

That the early years did not bring any important modification in contrast to the later years is not surprising. During the forties and early fifties, Blue Note was still a small independent label and, in consequence, probably did not have the necessary financial resources to record a lot of sessions. With its commercial success in the sixties however, Blue Note began to appear as a major actor on the jazz scene and, therefore, benefited from a wide exposure that allowed the label to reinforce its dominant position. During the seventies, after having endured many organizational changes, and given the decreasing popularity of jazz, Blue Note was forced to considerably renew its pool of artists. The label was then under the custody of United Artists, which probably helped finance its restructuring. Even so, this was not sufficient to guarantee economic viability on the short term.

In most dynamic models of network formation, average degree is considered to be independent of the number of active individuals (i.e. the size of the network) and, as a consequence, is supposed to remain relatively constant in time. The fact some individuals have a high degree is compensated, in these situations, by the low degree of newcomers. In the case of the Blue Note network, however, the average degree progressively increases, as shown in Table 2, suggesting that artists have a tendency to multiply and diversify collaborations over the years. The various individuals, therefore, do not always play with the same group of artists, but rather, favor different arrangements and organizational settings

9 throughout time.

Our analysis shows that the values for the average degree range from a minimum of 5 in 1939, to a maximum of approximately 23 in 1979. Considering the fact that the most commonly found ensemble is the quintet, this means that any individual should generally have at least four distinct collaborators. As a result, an artist would have to play in three different quintets with dissimilar people each time to have a degree equal to 12. The hypothesis according to which any individual only collaborates with different people is however quite unrealisitc. In most situations, artists frequently interact with the same musicians over and over again. So if an individual always plays with one similar person each time, and if all the other members of the group change for each session, the individual would have to participate in at least four quintets to have 12 different connections, and this number will increase as the artist continues to regularly play with the same musicians.

Figure 1: The Blue Note network, 1939-1979

In Figure 1, we represent the Blue Note collaboration network, where each node corresponds to an artist, and each line between two nodes indicates a link. The size of the nodes is proportional to the degree. The colors define the time period during which each node and each link appeared for the first time in the network.

10 COLLABORATION AND STAR PRODUCTION

The increasing standard deviation of average degree suggests that the disparity between the most and the least connected individuals tends to amplify in time. In other words, the artists with many links tend to contribute significantly more than others to the increase in average degree, and therefore benefit from a much wider variety of collaborations. In Figure 2, we represent the degree distribution in log-log scale for the different years we study. The same trend is observed throughout the period. Although we do find a certain amount of skewness, the power law behavior of these distributions appears to be truncated, and does not follow a linear progression as it would be the case with scale-free networks. In other words, the averagely linked individuals are relatively important in the network and tend to significantly outnumber the most connected individuals. In consequence, high-status artists will have a tendency to lose some of their attractivity through time, which will significantly alter the preferential attachment process.

Figure 2: Degree distribution of the Blue Note network

This phenomenon may partly be explained by the presence of ageing (Amaral et al., 2000). As we study a fairly long period, we expect those artists who were very active in the early years of the label to cease recording at a given time. This can happen for different reasons, such as new contracts with other labels, retirement, death or simply loss of popularity. At some point, these individuals are therefore replaced by newer artists, who will strengthen their status until they are themselves replaced by other individuals. Art Blakey, for example, who actively worked for the label during a long period and who encouraged many young musicians with his Jazz Messengers, released his last record for Blue Note in 1964, and was

11 gradually superseded by Donald Byrd – one of his numerous students – as the most connected artist. In this analysis, we have not taken into account decay. In other words, important artists may still appear in the network eventhough they are not active any more, therefore introducing a certain bias in our measures. A closer look at the dynamics underlying the evolution process would however be necessary in order to fully comment on that matter.

As we find a highly skewed distribution, we may expect some artists to be much more influential than others, even though we do not observe a scale-free network. Therefore, in order to assess the extent to which the degree of artists’ impacts on the connectivity of the network, we study the component sensitivity. In that respect, we show, in Table 3, the size of the largest component, as well as the diameter of the network, when the 2.5%, the 5%, the 10%, and finally the 20% most connected artists are removed. The results suggest clearly that the network remains well-connected and only collapses when we remove 20% of the most linked individuals. This phenomenon is observed throughout the period we study, although it appears to be more intense during the early years of the label, as stars probably play a more important role given the fewer individuals present in the network. The most connected individuals therefore do not contribute relatively more than others to the general unification of the network. In consequence, these artists may be stars in the sense that they are well connected from a local point of view, but do not however influence the global formation of the network.

Table 3: Star production statistics and sensitivity

1949 1959 1969 1979 Size of main component 200 621 1173 1897 In percentage 88.50 % 93.81 % 96.78 % 97.68 % — Without top 2.5 % 82.3 % 87.31 % 94.22 % 93.61 % — Without top 5 % 74.34 % 82.33 % 90.84 % 91.09 % — Without top 10 % 59.73 % 67.97 % 77.56 % 83.83 % — Without top 20 % 23.45 % 34.59 % 46.04 % 63.9 %

Diameter of main component 7 8 8 8 — Without top 2.5 % 9 8 8 8 — Without top 5 % 11 10 9 8 — Without top 10 % 16 20 11 10 — Without top 20 % 12 26 19 17

Note: The size of the main component corresponds to the number of individuals that form this component. The values in percentage are obtained relatively to the total number of individuals in the network.

THE EMERGING SMALL-WORLD

We examine the small world characteristics of the Blue Note network, by focusing on the average distances, and the average clustering coefficient. Our main results are presented in Table 4.

In most cases, average distances in a network are expected to be a function of its size. Hence, as the network grows, we should commonly observe a relative dispersion among individuals. Our results seem to suggest the opposite, as average distances, after having increased during

12 the label’s first years, tend to stabilize and slightly decrease, eventhough the network continues to expand at a relatively high rate. The decreasing path length ratio supports these findings. In fact, the new individuals that are progressively added to the network, as well as the new links that are created among present artists, contribute to unify the different entities, as suggested by the increase in the relative size of the main component. This process indicates that, over time, the different groups are not necessarily scattered across the network, and therefore appear to be more or less integrated to each other. As a result, distant individuals share an increasing number of common collaborators, which multiplies the various paths between them and shortens the separation among the different artists. Two mechanisms are therefore expected to take place simultaneously. On one hand, new groups integrate the network, probably increasing its decentralization. On the other hand, this greater dispersion is compensated by the creation of new links between old artists, and between old and new artists, which globally results in higher proximity among individuals.

Table 4: Small world statistics

1949 1959 1969 1979 Actual Path Length 3.48 3.65 3.42 3.27 Random Path Length 2.26 2.23 2.15 2.14 Path Length ratio 1.54 1.64 1.59 1.52

Actual Clustering 0.565 0.416 0.366 0.374 Random Clustering 0.327 0.226 0.174 0.170 Clustering ratio 1.73 1.84 2.1 2.2

Small world Q 1.12 1.12 1.32 1.45

Note: Average distances were computed on the main component only.

The average clustering coefficient defines the level of cohesiveness (or interconnectedness) among the different individuals in the network. As we study a unipartite projection of a bipartite graph, this coefficient indicates whether different groups combine common artists (in which case the clustering is high), or whether the ensembles are formed by distinct individuals (leading to low values of concentration). Unsurprisingly, the clustering coefficient appears to be globally decreasing over time, before stabilizing substantially, as suggested in Table 4. In other words, from a global point of view, individuals are less interconnected to others over time. However, if we take into account the network growth, the evolution of the clustering coefficient ratio indicates relatively higher levels of interconnection, in comparison to the random network of equal size. As with path length, we consider the presence of two opposite mechanisms acting simultaneously. On one hand, the addition of perfectly connected cliques contributes to increase levels of clustering from a local perspective. On the other hand, the fact these groupings are not fully connected to the network in general lowers the global clustering, and therefore partly eliminates the previous effect.

Our findings demonstrate important modifications throughout time in the collaboration structure among artists. As we have shown, the Blue Note network has progressively become more and more integrated and interconnected, which is suggested by the relative decrease of average path length and relative increase of average clustering. These structural features have significantly supported the development of the label. Over time, local and global mechanisms therefore add up and allow for a specific equilibrium to emerge, in which artists benefit from

13 their intense interaction in fully connected groups to progressively develop specific styles, but also from their encounters with distant (and nonetheless close) collaborators to reach creative material. These results are consistent with the main hypotheses of the small world model.

SUCCESS AND COLLABORATION

So far, we have focused exclusively on the structural characteristics of the collaboration network, suggesting strong interdependence between local incentives and global behavior. However, we have not taken into account any measure of success whatsoever. It is therefore necessary to ask ourselves to what extent performance is correlated to the structural position of artists. These questions are not easily and straightforwardly answered. We attempt to tackle these problems by using the information we have collected on the Blue Note label. We focus on the artists who reached the well-known Billboard charts, which gathers the best-selling records for each year.

During the period from 1939 to 1979, a total of 41 Blue Note albums appeared in the Top 200 Billboard charts, representing a total of 259 artists, with often the same musicians leading the way. In Table 5, we present the 14 artists who appeared in these charts as leaders, following the Allmusic Guide to Jazz (Bogdanov et al., 2002).10 We have ordered these musicians according to their first recording for Blue Note. Unsurprisingly, all these artists are those that are most commonly remembered as being the main representatives of the label. Albums such as Lee Morgan’s The Sidewinder, Donald Byrd’s A New Perspective, which both reached the charts in 1964, or Horace Silver’s A Song for My Father celebrated in 1965, have all been major acts for the Blue Note label, and have all acquired a wide recognition in the world of jazz. What is probably more surprising is to find the group War, with its album Platinum Jazz, who became the first group to have received a Gold award by the Recording Industry Association of America the year following the album release, in 1977. This group has only recorded one session for the label, which is why its five members do not appear to be central players in the network.

Several generations have contributed to forge the Blue Note success. During the 1960s, the most successful artists had all participated in a large number of sessions, and generally collaborated with many different individuals. In fact, most of these experienced musicians were closely related to the different generations of the Jazz Messengers, and often made their debut recordings with the group. At the time, even though none of the artists really benefited from a star-like status (except maybe for Art Blakey), the label relied on a group of important individuals who helped connect the entire network. During that period, many fairly young talents took part in the different sessions, and progressively reinforced their position in the network by interacting with one another, sometimes as sidemen, sometimes as leaders. All these artists have played a major role in uniting the growing family of Blue Note musicians and should be considered as forming the core of the Blue Note network.

10 This may appear like a very small number of musicians in comparison to the size of the dataset we study. However, given that rewards in the artistic world follow a power law distribution, and given the specific properties of these networks, we suggest that this small sample of artists is quite representative of the styles with which the Blue Note label has founded its success.

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Table 5: The most successful leaders

Charted Charted First session First time in Number of albums as albums as for the label charts sessions leader sideman

Horace Silver 1952 1965 2 0 83 Lou Donaldson 1952 1963 8 2 62 Donald Byrd 1955 1964 7 0 81 Jimmy Smith 1956 1962 6 0 47 Lee Morgan 1956 1964 3 1 103 Duke Pearson 1959 1969 1 3 64 Stanley Turrentine 1960 1967 2 4 71 Brother Jack McDuff 1961 1969 1 0 14 Lonnie Liston Smith 1967 1970 1 3 11 Bobbi Humphrey 1971 1974 3 0 19 Marlena Shaw 1972 1975 1 0 15 Ronnie Laws 1975 1975 1 0 10 Earl Klugh 1976 1976 3 1 15 Noel Pointer 1976 1977 1 1 5 Harold Brown (War) 1977 1977 1 0 1

During the 1970s, many new artists reached the charts. Most of them made their first recording for Blue Note during the late sixties and early seventies, and almost immediately became very successfull. These individuals have not been as active as the previous generation, but still appear to be fairly well connected. However, when we look at it closely, we see that most of them recorded big sessions with more than twenty musicians each time. Earl Klugh, for example, who only participated in 15 sessions, collaborated with 126 other individuals, contrasting with the 103 sessions Lee Morgan participated in and the 143 collaborators he has had throughout his career. This may explain why we observe higher levels of interconnection during the seventies, and why the collaboration structure appears to be less dependent on stars. All through the seventies, the successfull artists have contributed to the promotion of the Blue Note label and have all played an important role in building the label’s reputation. Their commercial success did not however guarantee the label’s viability on the market on a medium-term basis. As a result, when the label was relaunched in 1985, it relied on the first generation of musicians who had created the Blue Note hard bop family, rather than on the funk-soul generation.

In Figure 3, we present the artists that appeared in the charts during the period under study according to their structural characteristics. In this figure, the size of nodes is proportional to degree. Dark nodes represent the leaders, while brighter nodes represent sidemen. The vertical line dividing the figure in two characterizes the average clustering for the entire network. The horizontal line represents the average path length. As suggested by this figure, most of the charted artists have an average path length lower than average, meaning that they almost all occupy a central position in the network. In terms of clustering, individuals behave very differently one from another. Most leaders seem to be characterized by relatively low clustering, suggesting that they have played in various sessions with many different artists. Sidemen, by contrast, are characterized by dissimilar levels of clustering, with those primed in the sixties showing relatively low clustering and those primed in the seventies showing relatively high clustering. Again, this trend clearly illustrates the label’s evolution in time.

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Artists that belong to the bottom left corner in Figure 3, play an essential role in integrating the network. With no surprise, the five former members of the Jazz Messengers (Horace Silver, Donald Byrd, Stanley Turrentine, Lee Morgan and Lou Donaldson) are those with the lowest levels of clustering, suggesting that these artists widely contributed to attract and match different individuals together. The Blue Note label has been able to rely on these core artists in order to ensure its viability all through the 1960s. The artists who arrived later appear to be much less important to structure, and appear to have been incapable of diversifying their relations. These artists made several hits, but these were not enough to guarantee the label’s viability in the eighties.

Figure 3: Structural characteristics of the charted artists

Note: On this figure, the values for path length have been normalized to range from 0 to 1.

Success is most likely dependent on the work of many different artists, who contribute to reinforce specific conventions, therefore promoting the styles they are associated to. In other words, we consider success to be the result of a collective process, based on the integration of overlapping groups who benefit from each other in such a way that creative material can progressively become widely accepted and prevail on the market. Catchy melodies, as well as captivating tunes may allow some artists to perform better than others. These individuals will generally increase their reputation through time, therefore increasing the number of sessions they participate in, as well as the number of their connections. However, their success can only last as long as other artists support their musical expressions.

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By allowing the younger artists to reinforce their status through time, Blue Note has been able to guarantee the continuous renewal of its catalog, constantly adapting to the changes in jazz. The evolution of the Jazz Messengers illustrates this well. Throughout its history, the Blue Note label has launched many new artists, frequently associating them to established individuals. These new talents have therefore benefited from the experience of those forming the core of the label, which has allowed them to gradually occupy a central position in the network. In this context, the different styles of jazz, and particularly hard bop, have been constantly nourished by the work of a variety of artists. This process is probably the major reason for the label’s long-lasting success. As a result, if high-status artists appear to be an essential source of growing power and prestige on a rather short-term basis, they do not promise long-term viability. They must therefore be progressively replaced in order for new creative talents to acquire a central position and eventually become tomorrow’s hit-makers. In this perspective, success may be the key mechanism leading to economic viability, but it can also be the main reason explaining failure, in cases where strong dependence on several major stars inhibits the enforcement of change.

CONCLUDING REMARKS

Since its establishment in 1939, “the finest in jazz” has been Blue Note’s slogan and motto. Many are those who would agree with this assertion. Indeed, the label has always taken great care in recording some of the most important artists of each era, all of which have contributed, by their multiple interactions, to the creation of a variety of styles describing jazz. In that respect, the different musical expressions should be considered as having emerged from a cohesive core, in which integrated groups of rival and non-rival artists overlap, forming one big entity. This idea supports the organic evolution of jazz described by DeVeaux (1991).11

Throughout this analysis, we have attempted to characterize the extent to which this musical creativity can be related to the dynamic network formed by the collaborations among the many different artists. Although we do not have the sufficient data to be able to fully address the many questions that are raised in this work, our findings do suggest that the structure can be directly related to the recording strategy implemented by Blue Note in time. As a matter of fact, by intensively relying on the numerous artists in the core who helped create hard bop, the label was able to benefit from an important success. This gave Blue Note the opportunity to also experiment with new talent and record more novel artistic expressions, like avant- garde or free jazz. In other words, at any point of its evolution, the label has been able to find the right equilibrium between specialization and variety, by recording well-established musicians, as well as creative newcomers.

Following this perspective, we have shown that some artists benefit from a much more important rank than others, and can reasonably be viewed as the actual stars in the collaboration structure. These stars however do not appear to be responsible for connecting the network. Hence, if artists with many collaborators may contribute to influence the creation

11 This process of ongoing evolution in which category boundaries are blurred is similar to what is observed in the world of science (Lamont and Molnar, 2002; Frickel and Gross, 2005).

17 of new musical expressions in some way or another, they must rely on the cohesive and interconnected regions of the network to diffuse their ideas, and to allow for commonly accepted conventions to develop. A closer look at the extent to which these stars bridge different styles and benefit from their creativity to reach success would be however necessary in order to fully conclude on that topic.

In short, this study supports the fact that successful evolution within a creative organization is mainly driven by greater cohesiveness and integration of stylistic expressions (which is suggested by the emerging small world phenomenon), so as to certify the institutionalization of creative content while offering the possibility for novel streams to rise. In this setting, special attention should be given to several leaders or stars (as suggested by the unequal degree distribution), to the extent that their popularity ensures sufficient returns. In other words, part of the success of the Blue Note label should be viewed as inherent to its ability to have relied on a growing group of core artists while giving the opportunity to a wide and dispersed periphery to develop its own standards and progressively reach a central position. As such, the conclusions we draw from our analysis may serve as an example so as to how organizations in the cultural industries may implement diversity.

As in most scientific domains, success in art worlds is not always guaranteed. In fact, in order to be economically efficient, the creative process must be constantly nourished by the ongoing renewal of trends and styles. This can only be accomplished throughout the coordination of new talents closely linked to the existing paradigms. As a result, economic incentives might be an important motor of local and global action. However, these procedures can only be viable as long as evolution is deeply rooted in the incremental implementation of artistic values. In other words, as suggested by most historical examples, it seems that the revolution must nurture in the system in order for the outcome to be satisfying and for diversity to be fully expressed.

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