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C H A P T E R

Handbook of Organizational Creativity.DOI: © 2012 Elsevier Inc. All rights reserved.201210.1016/B978-0-12-374714-3.00004-5

Fields, Domains, and Individuals

Dean Keith SimontonUniversity of California, Davis, CA

According to the poet William Wordsworth, the physicist and mathematician Isaac Newton was:

“A mind forever / Voyaging through strange seas of thought, alone” (quoted in Jeans, 1942, p. 711).

Newton’s supposed solitary genius allowed him to make discoveries that amazed the world. As Alexander Pope put it:

“Nature and Nature’s laws lay hid in night: / God said, Let Newton be! and all was light” (quoted in Cohen & Cohen, 1960, p. 285).

Now, no doubt Newton was very much a loner. Indeed, he may have had a disposition that might be diagnosed as Asperger’s today (Fitzgerald, 2002). He never formed a truly intimate relationship with another human being, and certainly not with a woman. Even his friendships were few and often fleeting. Nevertheless, it is not quite correct to say that he was alone. In the first place, he himself admitted that his work built about that of his predecessors:

“If I have seen further, it is by standing on the shoulders of giants” (quoted in Who Said What When, 1991, p. 129).

Among these predecessor giants were Nicolaus Copernicus, Johannes Kepler, Galileo Galilei, and René Descartes.

But even more than this, Newton was deeply embedded in a network of contemporary mathematicians and scientists in England and on the European continent. Among the most eminent of these were Jean Bernoulli, James Bradley, Abraham DeMoive, John Flamstead, Edmund Halley, Robert Hooke, Gottfried Wilhelm Leibniz, John Locke, Colin McLauren, Ole Christensen Römer, John Wallis, and Sir Christopher Wren. These associates had more

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than a peripheral connection with Newton’s life. For example, Halley facilitated the pub-lication of Newton’s masterpiece, the Principia Mathematica. Newton had a bitter prior-ity dispute with Leibniz over who first invented the calculus, a dispute that was settled in Newton’s favor through the aid of his friend DeMoive.

Hence, although Newton might be taken as the prototypical example of the “lone gen-ius,” he was definitely not an isolated individual. If a loner like him cannot be considered alone, then it is hard to conceive how creators in general can be viewed as persons divorced from the social context. Although it is not natural for psychologists to focus beyond the indi-vidual, more creativity researchers have increasingly come to emphasize the importance of the larger interpersonal and sociocultural milieu (e.g., Amabile, 1996; Harrington, 1990; Sawyer, 2007). However, for the purposes of this chapter, I wish to concentrate on one par-ticular take on this issue, namely, Csikszentmihályi’s (1990, 1999) systems perspective. I will first provide a brief overview of this perspective and then offer two illustrations of its utility.

SYSTEMS PERSPECTIVE

Csikszentmihályi (1999) argues that creativity does not take place in a singular creative person. Instead, it emerges in a system consisting of three components: the domain, the field, and the individual. The interaction of the three systemic components decides that a given contribution is in fact creative. Because Csikszentmihályi’s distinction between domain and field is more precise than the terms are often used in everyday language, we will define those first. We can then discuss how the individual interacts with those two com-ponents to yield creativity.

Domain

According to Csikszentmihályi (1990), the domain represents “the parameters of the cul-tural symbol system” (p. 190) within a given area of creativity. More specifically, the domain constitutes “a set of rules, a vocabulary with a grammar and a syntax” (p. 200). Of course, the particulars of this definition vary from domain to domain. In quantum mechanics, for instance, we might say that the domain is characterized by such concepts as the “adiabatic hypothesis, anharmonic oscillator, Bell’s inequality, blackbody radiation, collapse of the wave function, Copenhagen interpretation, correspondence principle, eigenvalue problem, electron spin, exclusion principle, Heisenberg uncertainty principle, hidden variables, indeterminacy, Josephson effect, line spectrum, magnetic dipole moment, many-worlds interpretation, pho-toelectric effect, Planck’s constant, Planck’s radiation law, positron, quanta, quantum electro-dynamics, quantum oscillation frequency, renormalization, state functions, the Stern-Gerlach experiment, tunneling, virtual oscillators, wavelength, wave equation, wave-particle duality, wave-particle hypothesis, and X-ray scattering” (Simonton, 2004a, p. 44).

Speaking more generally, we could argue that the domain for a given area of creativity would be encompassed by the entries in a comprehensive encyclopedia devoted to that sub-ject. Examples would include encyclopedias of physics, chemistry, biology, psychology, or sociology. Admittedly, it is more realistic to fragment these inclusive disciplines into sub-disciplines. Most creators are specialists rather than generalists. Thus, a creative individual

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sysTEms PERsPECTIvE 69

might work in solid-state physics or evolutionary biology or social psychology. Whatever the details, because each domain evolves over time, the specific character of any domain represents the accumulated knowledge and technique up to a given point in time. If domains cease to change, then they are stagnant, and thus no longer provide the foundation for creativity. In the terms of Kroeber (1944), the cultural pattern becomes exhausted.

Field

In contrast to the domain, “the field is composed of individuals who know the domain’s grammar of rules and are more or less loosely organized to act as gatekeepers to it” (Csikszentmihályi, 1990, p. 201). To illustrate, at various times in the history of quan-tum mechanics the field was defined as variable subsets of the following scientists: “John Stewart Bell, Hans Bethe, Niels Bohr, Max Born, Louis-Victor de Broglie, Paul Dirac, Paul Ehrenfest, Albert Einstein, Richard Feynman, James Franck, George Gamow, Werner Heisenberg, Pascual Jordan, Brian Josephson, Hendrik A. Kramers, Rudolf W. Ladenburg, John Von Neumann, Max Planck, Erwin Schrödinger, Julian Schwinger, Tomonaga Shin’ichiro, John C. Slater, Arnold Sommerfeld, and John H. Van Vleck” (Simonton, 2004a, p. 44). If the domain can be characterized by the entries in a domain-specific encyclopedia, the field can be characterized by the entries in a field-specific biographical dictionary or who’s who, with the proviso that all deceased or inactive creators are excluded from the list. Notice, too, that these reference works should correspond. For every encyclopedia of economics, architecture, or wine, there should be a corresponding biographical dictionary of economists, architects, or winemakers.

Finally, it should be obvious that the field, like the domain, changes over time. Not only do particular creators come and go, but the role of any given creator within the field may dra-matically alter. An especially notorious example is how Einstein went from being an early advocate of quantum theory (via his work on the photoelectric effect) to becoming a staunch opponent of quantum theory (via his critique of the Copenhagen interpretation). Indeed, sometimes the older members of a field, in their role as gatekeepers, exert a conservative force over more innovative developments (Diamond, 1980; Hull, Tessner, & Diamond, 1978; cf. Levin, Stephan, & Walker, 1995; Sulloway, 1996). This phenomenon has been styled Planck’s principle after Planck’s (1949) claim that “a new scientific truth does not triumph by convinc-ing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it” (pp. 33–34).

Individual

Last but certainly not least (from the psychological perspective) we have the individual creator making up the third component of this tripartite system. In combination with the domain and field, the individual enters into a special kind of creativity cycle: “The domain transmits information to the person, the person produces a variation, which may or may not be selected by the field, and the field in turn will pass the selected variation to the domain” (Csikszentmihályi, 1990, p. 200). Naturally, the newly added information then is transmitted to persons operating within the domain, and the cycle goes on.

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As a case in point, consider Einstein’s classic 1905 paper on the photoelectric effect. In conceiving this contribution, Einstein drew upon such domain-specific ideas as Maxwell’s electromagnetic theory, Wien’s black-body formula, Boltzmann’s probabilistic formula for entropy, Planck’s quantum theory, and Lenard’s experiments on the photoelectric effect (Hoffmann, 1972). His results supported the idea that light consisted of discrete quanta that much later became known as photons. He wrote up the findings, and had the paper accepted for publication in Annalen der Physik, the leading journal in his field, where it appeared in 1905. Although experimental verification of Einstein theory took some time— Robert Millikan managed to do so by 1916—by 1921 the theory had sufficient support to earn him a Nobel Prize for Physics. Thus recognized by his field, and his ideas having entered his domain, Einstein’s paper on the photoelectric effect then became a basis for fun-damental developments in quantum theory by both himself and in the field. And so the sys-temic cycle continued.

I should note a complication to this picture: The actual act of creative synthesis, of putting all of the domain-specific ideas into a coherent package, does not always take place within a solitary individual. Einstein was not much of a collaborator, especially in his early years, so his photoelectric effect paper was single-authored. This systemic pattern is now much less common, particularly in the sciences (Sawyer, 2007). If anything, collabora-tion has become a norm. This means that two or more members of the same or affiliated fields and domains will iterate ideas back and forth before the final product is presented to the rest of the field for evaluation and possible incorporation into the domain. Even if creators do not directly collaborate with others in the field, they might engage in other interactions—such as correspondence with colleagues—that might contribute to ongo-ing projects. Accordingly, although the systems perspective is more sophisticated than the standard individualistic analysis of creativity, it still represents a highly simplified, even schematic treatment. Nonetheless, the perspective still proves useful, as will be seen next.

TWO ILLUSTRATIONS

Below I wish to outline two illustrations of how the domain–individual–field perspective can be applied to creativity. In the first example, the application was explicit (i.e., directly based on Csikszentmihályi, 1990, albeit with modifications). For the second example, the application was only implicit because domain and field components were not explicitly sep-arated out in line with Csikszentmihályi’s original conceptions. In any case, the first con-cerns combinatorial models and the second disciplinary hierarchies. These two illustrations do not exhaust the possible useful applications, but because the examples are so radically different, they suffice to indicate something of the range of applicability.

Combinatorial Models

Many creative individuals have compared creativity to a combinatorial procedure (e.g., Hadamard, 1945; Poincaré, 1921). Moreover, empirical and theoretical research suggests that creativity may, in effect, operate according to a stochastic combinatorial process (Simonton, 2003, 2010). That is, creators take a set of domain-specific ideas or “mental elements” and

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Two IllusTRATIons 71

then subject them to something akin to chance permutations (Simonton, 1988). Once a stable “configuration” is found, it is elaborated into a completed product (Simonton, 1997a). This product then is submitted for evaluation for potential publication in the vehicles appropri-ate for a given domain. Once published, the ideas contained in this publication can provide input into the revised domain.

This is not to say that combinatorial processes constitute the sole basis of creativity. For example, various algorithmic and heuristic methods are involved as well (see, e.g., Klahr & Simon, 1999). Moreover, the precise mix of processes and methods may vary from discipline to discipline (see, e.g., Mumford, Antes, Caughron, Connelly, & Beeler, 2010). However, because combinatorial models make the fewest assumptions and thus lend themselves to mathematical treatment, it may be useful to model creativity as a combinatorial process to provide a “chance baseline” against which we can assess the need to introduce additional processes (Simonton, 2009b). For this reason, Simonton (2004a) translated this combinato-rial process into a theoretical model of creativity in science (which was later generalized to handle creativity in the arts: see also Simonton, 2009a, 2010). Like Csikszentmihályi (1990), Simonton began the translation with the scientific domain, which was defined as the set of “phenomena, facts, concepts, variables, constants, techniques, theories, laws, questions, goals, and criteria” (p. 44). During the course of education and training, individuals develop creative potential by drawing their respective samples from this domain. At the beginning of a scientist’s career, the ideas making up these personalized subsets of the domain are then subjected to the combinatorial process. Those combinations that are preserved and prepared for publication are subsequently communicated to the field—the discipline’s gatekeepers— who then decide which of the new ideational combinations will become incorporated into the pool of domain ideas. This decision includes both what will get published but also what will get cited by other members of the field after publication. The result of this three-component process is depicted in Figure 4.1.

As it stands, this graphic depiction of the systemic cycle is uninteresting. It does not say much more than we already know. Fortunately, the application can undergo some modi-fications that render the application far more useful (Simonton, 2004a, 2010). These modi-fications allow us to deal with variations in (a) the size of domains, field, and individual

DOMAIN

FIELD INDIVIDUAL

Sampling

Communication

Incorporation

FIGURE 4.1 The creativity cycle linking domain, individual, and field. (cf. Csikszentmihályi, 1999, Figure 16.1.)

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domain-specific samples and (b) the amount of overlap in those individual samples for those making up the same field. These complications are indicated in Figure 4.2.

Here we see two domains, A and B, demarcated by the square boundary. The two boxes contain all of the ideas that define the respective domains. Hence, domain A con-tains more ideas than does domain B. In comparison, the circles depict the individual samples from the domain. The larger the circle, the greater the sample for that given indi-vidual. In simple terms, some creators know more about their chosen domain than do others. The total number of circles contained totally within a domain defines the field of that domain. Thus, in the figure, field A is larger than field B, probably a representa-tive situation if we can assume that the size of the field tends to be roughly proportional to the size of the domain. In any event, the overlap between the circles for a given field indicates the extent that the individuals share domain-specific samples (i.e., the degree that they had the same curriculum, read the same textbooks, studied under the same teachers and mentors, etc.).

Although it would certainly be the norm in the sciences for these overlapping regions to maximize, for sake of completeness Figure 4.2 shows two provocative exceptions. First, in domain A is found individual 1, a scientist who managed to obtain a sample of domain-specific ideas that do not overlap with any of the ideational samples of his or her col-leagues in the same field. This person might be called the “lone wolf” in the field. Second, in domain B can be found individual 2, a scientist who has attained a sample of ideas from domain A even though most of his or her ideas come from domain B. This scien-tist may be considered an interdisciplinary or even multidisciplinary interloper—someone

FIGURE 4.2 Domains A and B, fields A and B, and indi-vidual samples from domain-specific ideational pools. (from Simonton, 2004a.)

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Two IllusTRATIons 73

who may be able to synthesize the ideas of two previously unrelated disciplines to create a new discipline.

I realize that this conceptual scheme may seem quite abstract, but it turns out that it pro-duces a large number of unique predictions that have undergone tests in empirical research (Simonton, 2004a, 2010). Some of these concern just the individual. For instance, the larger the domain-specific sample acquired by a particular scientist, the larger the number of potential ideational combinations that can be generated. Furthermore, the number of com-binations increases as a roughly exponential function of the number of sampled ideas. That means that if the size of the domain samples is normally distributed, then the distribution of combinations will be described approximately by a highly skewed log-normal distribu-tion. In more concrete terms, the distribution will exhibit a long upper tail so that most of the contributions will be made by a very small percentage of the individuals working in the field (Simonton, 2004a). There is abundant evidence that this distribution is actually char-acteristic of individual differences for creative individuals contributing to the same domain (Simonton, 1997a).

Yet from the standpoint of the current chapter, a more interesting implication concerns the consequences that operate at the level of the field (Simonton, 2004a, 2010). Clearly, fields may vary greatly in the extent to which their individual members share the same domain-specific ideas. On the one hand, in those fields where the overlap is extremely high, indi-viduals will be subjecting the same ideas to the same stochastic combinatorial process. As a result, the probability is increased that two or more individuals will come up with the same viable combination. On the other hand, those fields in which the individual samples exhibit little overlap are less likely to see two or more individuals duplicate their efforts in this fashion.

The occasion I am describing is known as multiple discovery (Merton, 1961). Memorable instances include the calculus (Newton 1671, Leibniz 1676), the prediction of the new planet Neptune (J. C. Adams 1845, Leverrier 1846), the law of conservation of energy (J. R. von Mayer 1843, Helmholtz 1847, Joule 1847), the periodic law of the elements (DeChancourtis, Newlands, L. Meyer, and Mendeleev), the theory of evolution by natural selection (C. Darwin 1844, Wallace 1858), the ophthalmoscope (C. Babbage 1847, Helmholtz 1851, Anagnostakis 1854), and the incandescent carbon filament (Swan 1879, Edison 1878). Such cases run into the hundreds, so this is certainly not a rare event.

The multiples phenomenon is often attributed to sociocultural determinism, that is, to the notion that particular ideas become absolutely inevitable at a given moment in the his-tory of science (e.g., Lamb & Easton, 1984). Even so, it should be evident that these events can be explicated in terms of a stochastic combinatorial process (Simonton, 2004a, 2010). Furthermore, this probabilistic rather than deterministic explanation can handle other dis-tinctive attributes of multiples that cannot be explained by deterministic models, such as the signature distribution of the total number of scientists in a given field who are involved in a particular multiple (Simonton, 2009a, 2010). However, discussion of these niceties will take us too far from the main purpose of this essay. The main point is that the multiples phenom-enon cannot be explicated without first adopting a systems perspective. Any account must begin with a domain of ideas and a field of individuals who have obtained variably overlap-ping samples from that domain. By definition, multiples cannot even occur at the individual level of analysis.

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Disciplinary Hierarchies

In the previous application of the systems perspective, it was assumed that scientific fields could differ regarding the degree to which their individual members had similar samples of domain-specific ideas. Certainly, this specific contrast does not constitute the only criterion by which fields and domains can differ from each other. At this point, it is instructive to ponder a conjecture first introduced by the philosopher August Comte (1839–1842/1855) in the mid-19th century. Comte hypothesized that scientific disciplines could be arrayed into a hierarchy. In his case, the sequence was astronomy, physics, chemistry, biology, and sociology. Although this sequence had a basis according to criteria unique to Comte’s philosophy, his arrangement closely parallels more contemporary contrasts among the sciences in which they are distinguished as exact versus non-exact, hard versus soft, paradigmatic versus pre-paradigmatic, and natural versus human (e.g., Kuhn, 1970; Smith et al., 2000).

Although these disciplinary orderings are highly speculative, they have gained some empirical endorsement in recent research (Simonton, 2004b; see also Fanelli, 2010). Using objective criteria, five major scientific disciplines could be reliably ordered as follows: phys-ics, chemistry, biology, psychology, and sociology. This ordering is depicted in Figure 4.3. Interestingly, physics and chemistry were grouped close together at the top, with biology and psychology forming a second cluster, and with sociology more distant from psychology than biology was from chemistry. More importantly, the criteria concerned the nature of the domain or the field corresponding to each discipline. In particular, these (and additional) disciplines were assessed on the following three sets of criteria:

1.51.41.31.21.11.00.90.80.70.60.50.40.30.20.1

–0.1–0.2–0.3–0.4–0.5–0.6–0.7–0.8–0.9–1.0–1.1

1 2 3 4 5

0.0

Com

posi

te s

core

Physics

Chemistry

Biology

Psychology

Sociology

Rank in Hierarchy

FIGURE 4.3 Hierarchy of the sciences based on objective characteristics of both field and domain. (from Simonton, D. K. (2004b.) Psychology’s status as a scien-tific discipline: Its empirical placement within an implicit hierarchy of the sciences. Review of General Psychology, 8, 59–67.)

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Two IllusTRATIons 75

First, fields at the top of the hierarchy exhibit a tighter consensus regarding which field members are making the high-impact contributions to the domain. This consensus is revealed by:

1. the earlier impact rate for scientists under 35 (i.e., the “up and coming” are recognized sooner; Cole, 1983),

2. the lower average age at receiving the Nobel Prize for those disciplines that have the honor (Stephan & Leven, 1993; see also Manniche & Falk, 1957), and

3. the stronger agreement in peer evaluations of the relative impact of various members of the field (Cole, 1983).

Not only do the top-of-the-hierarchy fields concur on who is doing the best work, but they also can identify those contributors earlier in their careers.

Second, the foregoing consensus applies, not just to individual contributors, but also to single contributions, as indicated by the higher concentration of citations to specific research articles (Cole, 1983). Moreover, this consensus appears to delineate a well defined “research front” of “hot topics” that the field deems most important for domain advancement. This disciplinary “leading edge” is characterized by:

1. greater citation immediacy (a gauge of whether citations concentrate on the most recent publications, with rapid decay rates as a function of time; Cole, 1983),

2. faster knowledge obsolescence rates (i.e., how fast domain-specific expertise becomes out of date; McDowell, 1982), and

3. higher probabilities of research anticipation (i.e., the degree to which scientists had their research anticipated by other scientists working in the same field; Hagstrom, 1974).

Third, the field’s consensus on contributors and contributions is associated with consen-sual understanding of the ideas that make up the discipline’s domain. In disciplines lower in the hierarchy, the concepts tend to be more imprecise, ambiguous, and uncertain, with considerably more latitude for subjective interpretation. This domain-specific ideational imprecision, ambiguity, and uncertainty is reflected in:

1. higher peer consultation rates (i.e., the degree to which researchers consult with colleagues before submitting their work for publication; Suls & Fletcher, 1983),

2. higher theories-to-laws ratios, that is, greater theoretical speculation than empirically confirmed laws in the discipline’s mainstream introductory textbooks (Roeckelein, 1997), and

3. higher lecture disfluency, that is, higher rates of filled pauses (“uh,” “er,” and “um”) during classroom lectures for undergraduate courses (Schachter, Christianfeld, Ravina, & Bilous, 1991).

Incidentally, a certain conceptual concordance appears between these results and the combinatorial models discussed earlier. In disciplines with a higher magnitude of con-sensus, individual samples from the domain should exhibit a more conspicuous overlap. Higher sampling overlap indicates that each member of the field will be subjecting many of the same ideas to the combinatorial process. Consequently, scientists in high-consensus disciplines should have higher likelihoods of participating in multiple discoveries. There is some evidence that this is the case (Simonton, 1978, 2010). Multiples appear much more

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often in the physical sciences than in the biological sciences, and are rather rare in the social sciences.

Having just established the empirical existence of a Comtean hierarchy of the sciences, I would now like to use this demonstration as the basis for three consecutive extensions (cf. Simonton, 2009b, 2009c). First, I will show that the hierarchy can be interpolated within any given science as well as extrapolated beyond the sciences to encompass the arts and human-ities. Second, I will indicate how this more finely differentiated and extended hierarchy cor-relates with the dispositional traits and developmental experiences of the creators active in a given field and domain. Third, I will examine whether the creator’s magnitude of achieve-ment within that domain depends on the degree to which his or her disposition and devel-opment match what is typical of those in the same field.

Extrapolation and InterpolationThe foregoing disciplinary hierarchy can be both extrapolated beyond the sciences to

encompass the arts and humanities, and interpolated to accommodate within-discipline contrasts.

Extrapolation. Some of the criteria used to differentiate the various sciences also apply to the humanities (Simonton, 2004b, 2009c). Let me give just two examples.

1. The knowledge obsolescence rate is slower for the humanistic domains of history and English than in the scientific domains of physics, chemistry, biology, psychology, and sociol-ogy (McDowell, 1982). History and English scholars can take a break from research—such as going into administration—with much less damage to their later output than is the case for scientists, particularly a natural scientist. In fact, physics is as far above the domain aver-age in the obsolescence rate as English is below average. In concrete terms, a high-energy physicist must work much harder to avoid falling behind his or her field than does a Chaucer scholar. In other words, the domain–individual–field creativity cycle in Figure 4.1 churns much faster in the former discipline than in the latter.

2. The lecture disfluency displayed in political science, art history, and English exceeds that exhibited in sociology and psychology (Schachter, Christenfeld, Ravina, & Bilous, 1991). Hence, the concepts that define domains in the humanities tend to be more imprecise, ambiguous, and uncertain relative to those in the social sciences. There is one fascinating exception to this generalization, however. The philosophers apparently put a premium on logical and conceptual precision because they score somewhere between psychologists and chemists on this indicator. In that limited sense, philosophy belongs in the social sciences rather than in the humanities!

Although the extrapolation is more tenuous, the disciplinary hierarchy may be extended into the arts (Bliss, 1935). The extension is more tenuous because many of the criteria would have to be defined in a broader fashion. Yet if we grant this extension, then we would expect that the psychological factors that distinguish the natural from the social sciences would also differentiate the sciences from the arts. As will be shown shortly, this turns out to be the case.

Interpolation. To be more precise, the scientific hierarchy depicted in Figure 4.3 can only be considered an approximation. The specific placement should more precisely add error bars. That is, each domain is placed according to its empirical center of gravity or central tendency, about which individual scientists will vary in significant ways. The degree of variation is even great enough to show overlap between the separate domain distributions.

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Although a portion of this variation may be attributed to individual differences, a more interesting source of the variation is intra-disciplinary in nature. Again, allow me to give two illustrations.

1. Natural-science versus human-science psychology. According to the hierarchy presented in Figure 4.3, psychology stands somewhere between biology and sociology. Although it leans toward biology, clearly some psychologists are more favorably disposed toward the social sciences, even humanities. Empirical evidence supports this view (Coan, 1968, 1973; Simonton, 2000; see also Kimble, 1984). In particular, a study of eminent psychologists found that they formed two separable psychological orientations. On the one hand are the natural-science oriented psychologists who are objectivistic, quantitative, elementaris-tic, impersonal, static, and exogenist in their theory and methodology. On the other hand are the human-science oriented psychologists, who are theoretically and methodologi-cally subjectivistic, qualitative, holistic, personal, dynamic, and endogenist. Furthermore, psychologists who represent the extremes on these dimensions tend to receive more cita-tions than those who occupy more compromising or conciliatory positions between the extremes (Simonton, 2000). As a consequence, psychology’s placement in Figure 4.3 actually represents a mean of two psychologies. It is worth pointing out the magnitude of domain consensus inspired by Skinner’s radical behaviorism (as indicated by the Journal for the Experimental Analysis of Behavior) compares quite favorably with research published in the hard sciences (Cole, 1983).

2. Normal versus revolutionary science. Kuhn (1970) distinguished between sciences that were paradigmatic, such as physics and chemistry, and those that were pre- or non- paradigmatic, such as psychology and sociology. Scientists in the former domains operate with a higher level of theoretical and methodological consensus. In Kuhnian terminology, such scientists practice “normal” or “puzzle-solving” science. At the same time, Kuhn rec-ognized that paradigmatic sciences often go through “crises” owing to the appearance of “anomalies”—findings that do not fit the accepted paradigm. During these periods, the con-sensus breaks down, and the science becomes, in a sense, less paradigmatic. Happily, revo-lutionary scientists eventually appear who introduce a new paradigm to replace the old one. The discipline then can move up to its original place in the hierarchy. Practitioners will prac-tice normal science once again.

Note that individual practitioners of paradigmatic sciences have a strong expectation that the crisis will be temporary. Practitioners in non-paradigmatic sciences do not share that belief. Thus, natural- and human-science oriented psychologists seldom endeavor to reach some unified paradigm for the discipline.

Disposition and DevelopmentSo far, we have looked at the disciplinary hierarchy just in terms of field and domain

attributes. Does the field exhibit a consensus? Does the domain consist of precise and unam-biguous ideas? Yet according to the systems perspective, we have to add the individual to complete the analysis. Do the individuals who enter a given discipline display disposi-tional traits and developmental experiences that line up with field and domain characteris-tics? The relevant empirical literature appears to give an affirmative answer. To show this, I will provide a brief review of the results, starting first with disposition and then turning to development.

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Dispositional traits. The creative individual can be characterized by a distinctive set of motives, values, interests, and attributes (Martindale, 1989). However, these dispositional traits vary both across- and within-disciplines (Feist, 1998).

1. Across-disciplines. Although creativity is often associated with psychopathology, the empirical research demonstrates that the incidence and intensity of psychopathological symptoms vary according to discipline (Jamison, 1989; Ludwig, 1992, 1995; Raskin, 1936; Post, 1994; Simonton & Song, 2009). Nevertheless, Ludwig (1998) indicated a method to the madness, namely that “persons in professions that require more logical, objective, and formal forms of expression tend be more emotionally stable than those in professions that require more intuitive, subjective, and emotive forms” (p. 93). It should be immediately apparent that this distinction corresponds almost perfectly with a discipline’s placement in the extended hierarchy. Ludwig went on to show that the contrasts across disciplines dis-play the fractal pattern of “self-similarity”. This pattern is found at four consecutive levels of magnification; first, scientists as a group have lower lifetime rates of mental illness than do artists as a group. Second, in the sciences, natural scientists tend to average lower rates than do social scientists, whereas in the arts, creators in the formal arts (e.g., architecture) tend to average lower rates than those in the performing arts (e.g., music and dance), who in their turn average lower rates than those in the expressive arts (e.g., literature and the visual arts). Third, within a specific expressive art such as literature, nonfiction writers are prone to display lower rates than do fiction writers, who in their turn average lower rates than poets do. Fourth and last, within any given artistic specialty (e.g., painting, sculpture, and photography), those who create in a formal style are prone to exhibit lower rates than those creating in a symbolic style, and the latter are disposed to exhibit yet lower rates than those creating in an emotive style. It must be emphasized that these interdisciplinary differ-ences represent averages only, so that substantial individual differences exist within each discipline, a cross-sectional variation that has critical repercussions.

Individuals creating in different disciplines will tend to differ in other dispositional traits besides psychopathology. For instance, in comparison to chemists, psychologists are prone to be more introverted, unconventional, bohemian, imaginative, and creative (Chambers, 1964). Similarly, eminent social scientists tend to be less factual, more emotional, and more rebellious than do eminent physical scientists (Roe, 1953). Collating all of the findings indi-cates that creators in the natural sciences differ from those in the social sciences in much the same way as scientists in general differ from artistic creators (Simonton, 2009c).

2. Within-discipline. Returning to psychopathology, the fractal pattern observed across dis-ciplines should also be found within disciplines, and there is evidence for this expectation within the sciences (Ko & Kim, 2008). Revolutionary scientists who overthrow the domi-nant paradigm tend to exhibit higher rates of mental illness than do normal scientists who conserve and extend that paradigm. Just as interesting is the evidence that psychologists who favor a natural-science orientation are prone to display a different set of personality traits relative to those who favor a human-science orientation (Johnson, Germer, Efran, & Overton, 1988). The former have a tendency to be more orderly, stable, conventional, con-forming, objective, realistic, interpersonally passive, dependent, and reactive, whereas the latter are inclined to be more fluid, changing, creative, nonconforming, participative, imagi-native, active, purposive, autonomous, individualistic, and environmentally integrated. Finally, another investigation has shown that eminent human-science psychologists, relative

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to their natural-science colleagues, have a greater propensity for complex but integrated thinking about the discipline (Suedfeld, 1985).

Developmental experiences. I have just shown how the dispositional traits of individual creators correspond to their discipline’s placement in the extended and differentiated hier-archy. The experiences that those individuals have encountered during their development exhibit a similar regularity. This again holds both across- and within-disciplines.

1. Across-disciplines. In terms of developmental experiences, Nobel laureates are not all cut from the same cloth (Berry, 1981). At one extreme, laureates in physics are most likely to come from highly stable, professional homes, whereas at the other extreme laureates in literature are far less so. Indeed, almost a third “lost at least one parent through death or desertion, or experienced the father’s bankruptcy or impoverishment” (p. 387; see also Raskin, 1936; Simonton, 1986). Laureates in chemistry fall between these extremes, but tend to be closer to the physicists. A parallel contrast is seen the home environments of creative adolescents (Schaefer & Anastasi, 1968). Scientific talents were more likely grow up in sta-ble homes in which their parents pursued conventional interests and hobbies, while artistic talents were more likely to come from unconventional homes that displayed conspicuous diversity with respect to geographic origins (e.g., foreign born), economic mobility, and extensive travels both in the United States and abroad. In a way, the family background of potential scientists was closer to “normal” while that of potential artists was unequivocally more deviant from the normal—more varied, unusual, and unstable.

This divergence between scientists and artists persists in educational and training expe-riences (Simonton, 2009c). Eminent scientists tend to have had the most formal education, eminent artists the least (Raskin, 1936; Simonton, 1986). Scientific creativity, relative to artis-tic creativity, appears to be associated with fewer and more homogeneous mentors and role models (Simonton, 1984, 1992b). On this score, eminent psychologists are more similar to scientists than to artists (Simonton, 1992a). Lastly, artistic creators have a higher likelihood of developing their creative potential in unstable and heterogeneous sociocultural milieus (Simonton, 1975, 1997b), whereas stable and culturally homogeneous systems are more sup-portive of scientific development (see also Candolle, 1873).

The foregoing concern contrasts between scientific and artistic disciplines. Still, some empirical evidence suggests that a similar pattern is found when different scientific disci-plines are compared (Simonton, 2009c). For instance, relative to creative chemists, crea-tive psychologists are disposed to have more rebellious relationships with their parents (Chambers, 1964; see also Roe, 1953). All in all, there is some reason to believe that a disci-pline’s placement in the hierarchy corresponds to the developmental experiences of its prac-titioners. The higher the placement, the more stable, conventional, and homogeneous the experiences.

2. Within-discipline. Although very little research addresses the question of within-disci-pline contrasts in developmental experiences, one notable exception is Sulloway’s (1996) work on the birth order of revolutionary scientists. Unlike practitioners of normal science, the scientists most favorable to revolutionary scientists tend to be laterborns. According to Sulloway’s theory, firstborns tend to gravitate to conventional high-prestige and high-power professions, whereas laterborns tend to lean toward unconventional and high-risk careers. This theory falls in line with other findings regarding across-discipline birth-order effects (Simonton, 2009c). Thus, firstborns are more likely to become eminent scientists

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(Eiduson, 1962; Galton, 1874; Roe, 1953; Simonton, 2008; Terry, 1989), whereas literary crea-tors may have higher odds of being laterborns (Bliss, 1970). But composers in classical music are more prone to be firstborns (Schubert, Wagner, & Schubert, 1977). These results make sense if we assume that creators active in domains that are more logical, objective, conven-tional, and formal tend to be firstborns while those who create in domains that are more intuitive, subjective, individualistic, and emotional tend to be laterborns.

Sulloway (1996) maintained that birth order was by no means the only developmental factor that affects whether someone is likely to become a revolutionary scientist. Among the additional influences are some that bear a connection to placement in the disciplinary hier-archy. These include early parental loss, parent–offspring conflict, and minority status. So the fractal pattern appears applicable to developmental experiences.

Agreement and AchievementI have just shown that an individual’s dispositional traits and developmental experiences

correspond with the position which his or her discipline occupies in the hierarchy. Not only may these psychological attributes distinguish the natural sciences from the social sciences, but also they differentiate the sciences from the arts and even various intra-disciplinary con-trasts (e.g., natural-science versus human-science psychology). I would now like to raise an independent question: What determines the magnitude of the impact of an individual on the creator’s chosen discipline? As indicated earlier when I discussed the combinatorial model, one explanation is that some individuals obtain a larger sample of domain-specific ideas. But this explanation is too simplistic. Two individuals can draw the same size sam-ples and still differ dramatically in creative output. Where one colleague becomes a genuine creator, the other becomes a mere expert who has mastery without originality. This differ-ence suggests that some psychological factors are involved in allowing the individual to convert his or her ideational sample into a new set of products.

Researchers have not found it difficult to identify variables that predict exceptional achievement in any given field. For instance, every high-achieving individual must boast a superlative degree of drive, motivation, determination, or persistence (Cox, 1926; Duckworth et al., 2007; Helmreich et al., 1980; Matthews et al., 1980). In this regard, a Nobel laureate in literature will be similar to a laureate in physics or chemistry. Yet a far more pro-vocative question is whether any of the variables that influence an individual’s disciplinary affiliation also affect the same person’s likelihood of making high-impact contributions. To appreciate why this issue is so intriguing, consider the following three alternative possibili-ties (Simonton, 2009c):

1. The creators who have the highest impact on their discipline may be precisely those whose dispositional traits and developmental experiences closely approximate those that characterize most of their colleagues in the same field. The most influential psychologist, for example, would be typical of psychologists in general. By comparison, psychologists whose dispositional and developmental characteristics put them at the periphery with respect to most members of their field will be less likely to prove highly influential. Individuals in the former group may be styled domain-typical creators. The more the creator is like everybody else in the same field, the greater is the magnitude of that creator’s production of high-impact work.

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2. The creators with the highest impact on the field may be those whose disposition and development are most similar to individuals who occupy domains higher in the disciplinary hierarchy. Hence, high-impact psychologists may feature dispositional traits and develop-mental experiences that render them most similar to biologists or even chemists. As a result, natural-science orientated psychologists may actually be more influential than human- science psychologists. Such individuals may be called domain-progressive creators. They seem-ingly aspire to move their discipline up the disciplinary hierarchy. These aspirations might even adopt the form of reductionism; that is, reducing the phenomena at one level to the explanatory principles that dominate at a higher level in the hierarchy.

3. The most influential individuals just might be those whose disposition and develop-ment place them nearer to creators active in a discipline lower in the hierarchy. In a sense, such creators represent a regression from the objective, logical, conventional, and formal to the subjective, intuitive, individualistic, and emotional. Accordingly, we may identify these persons as domain-regressive creators.

The latter of the three possibilities might seem the least plausible, especially in scientific disciplines. After all, if most “soft” sciences aspire to become more “hard,” and thereby move up the hierarchy, we would expect scientists to aspire to the rigor and precision of the more exact sciences. Nonetheless, a counterargument would suggest that high-impact crea-tivity requires a relaxation of logical constraints rather than their imposition. Albert Einstein once admitted that:

“to these elementary laws there leads no logical path, but only intuition, supported by being sympatheti-cally in touch with experience” (as cited in Holton, 1971–1972, p. 97).

If so, the highest-level scientific creativity might actually have more kinship with the artistic creativity more normally exhibited at lower levels in the hierarchy. In line with this conjecture, Max Planck (1949) once observed that creative scientists:

“must have a vivid intuitive imagination, for new ideas are not generated by deduction, but by an artisti-cally creative imagination” (p. 109).

The extant research relevant to this question predominantly favors the third alternative (Simonton, 2009b, 2009c). Within any given discipline, the domain-regressive creators are the most likely to have the biggest impact on the field. This tendency is especially strong for dispositional traits. One particular manifestation of this finding concerns the artistic interests and hobbies of high-impact scientists (Root-Bernstein et al., 2008; Root-Bernstein, Bernstein, & Garnier, 1995). Not only are artistic avocations associated with scientific crea-tivity, but the higher the level of that creativity the higher the likelihood that the scientist engages in such avocations. These interests and hobbies are also positively associated with openness to experience, a Big-Five personality factor also positively correlated with creativ-ity (Carson, Peterson, & Higgins, 2003; Harris, 2004; McCrae, 1987).

To provide a second example, consider the relation between psychopathology and crea-tivity. We have already seen that the incidence and intensity of mental illness relates to a discipline’s placement in the extended hierarchy. Yet within a given discipline, a greater propensity toward psychopathology is positively associated with creative achievement

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(Eysenck, 1995; Feist, 1998; Ludwig, 1995; Rushton, 1990). This positive relation becomes especially strong in the arts (Götz & Götz, 1979; Barron, 1963). This is not to say that mad-ness is required for creative genius, but only that the two syndromes share some dispo-sitional traits, such as a reduced capacity for cognitive filtering, a reduction that is also associated with higher openness to experience (Carson, Peterson, & Higgins, 2003; Peterson & Carson, 2000). Besides openness, creative individuals possess certain compensatory char-acteristics, such as high intelligence and ego-strength, which turn this supposed attentional deficiency into an asset (Barron, 1963; Carson, Peterson, & Higgins, 2003). Such defocused attention allows creators to “think outside the box”, an ability that becomes increasingly essential toward the artistic end of the spectrum.

CONCLUSIONS

In this chapter, I have argued that we cannot fully understand individual creativity with-out placing the person in the context of the field and the domain—the two key aspects of the discipline to which creators make their contributions. This argument was based on Csikszentmihályi’s (1990, 1999) systems perspective which situates creativity in a dynamic interaction among the domain, the field, and the individual. This perspective was then illus-trated in two distinct ways, one theoretical and the other empirical.

The first illustration involved combinatorial models. In these models, the members of a particular field begin with a sample of ideas from that domain. Each individual then sub-jects his or her personal ideational sample to a combinatorial process. Viable combinations are then submitted to the field, which then determines which combinatorial products will enter the domain set of ideations. These models can generate a large number of verifiable predictions, but the most interesting and valuable are those entailing phenomena that can-not be explicated without adopting a systems perspective. Most notable is the multiples phenomenon where two or more scientists independently make the same contribution—a phenomenon that has no meaning at the individual level of analysis. Furthermore, certain specific attributes of both field and domain determine the odds that a creator will even par-ticipate in a multiple.

The second illustration was much less abstract and formal: disciplinary hierarchies. I began by showing how the main sciences can be ordered according to the consensus exhib-ited by the field and the precision of the ideas making up the domain. This ordering was then extrapolated to encompass disciplines in the humanities and interpolated to handle within-discipline contrasts. I then showed that the resulting hierarchy had a psychological basis in the dispositional traits and developmental experiences of discipline-specific prac-titioners. The scientists differ from artists in a manner that parallels the difference between natural scientists and social scientists. Last, but not least, I observed that individual differ-ences in disciplinary impact were a partial consequence of the fit between individual and the discipline. The most high-impact members of a field tend to be domain-regressive in the sense that their dispositional and developmental attributes are closer to what prevails in domains lower in the hierarchy.

Taken altogether, it should be manifest that individual creators cannot be completely understood without placing their creativity in the proper disciplinary context. This context

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