DRAFT - Colleges & Universities 2000

Market Model and Academic Fields

The Market Model and the Growth and Decline of Academic Fields In U.S. Colleges and Universities, 1975-2000

Steven Brint University of California, Riverside Lori Turk-Bicakci American Institutes of Research Kristopher Proctor University of California, Riverside Scott Patrick Murphy University of California, Riverside Robert A. Hanneman University of California, Riverside

April 2009

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Market Model and Academic Fields The Market Model and the Growth and Decline of Academic Fields in U.S. Colleges and Universities, 1975-2000 1 ABSTRACT Recent interpretations of change in colleges and universities focus on their responsiveness to market conditions and the preferences of donors. A study of the growth and decline of academic fields over a 25-year period shows, at best, mixed support for such interpretations. In addition to responding to donors’ preferences, the growth and decline of fields is related to isomorphic pressures preserving the academic core; processes of closure in relation to occupational fields linked to the higher education credential system; in selected cases, scientific-intellectual revolutions in the disciplines; and the rise of fields connected to historically marginalized populations.

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"Even the rise and disappearance of whole systems of knowledge may ultimately be reduced to certain factors and thus become explicable... The sociology of knowledge should seek to investigate the conditions under which problems and disciplines come into being and pass away." – Karl Mannheim

Over the last two decades, the most popular interpretations of organizational and curricular change in U.S. higher education have derived from the premise that colleges and universities are increasingly responsive to economic incentives in their environments. For example, Gumport (2002) speaks of the rise of an “industry logic” in which “students tend to be seen as consumers rather than members of a campus community (and) the major responsibility for managers is to read the market…and attempt to reposition accordingly” (p. 55). Geiger (2004) observes, in the areas of revenue sources, university functions, and student outlooks, “coordination of behavior has migrated from within universities to the markets governing these activities” (p. 261). Kirp (2003) writes that “what is new…is the raw power that money directly exerts over so many aspects of higher education” (p. 3). Contained within many of these accounts is a contrasting ideal type drawn from an earlier era in which higher education institutions were “social institutions,” collegially rather than commercially organized, and concerned with advancing basic fields of knowledge, serving public rather than private purposes, and socializing students into the cultural norms of the academic community (see, e.g. Gumport 2002: 53-6). In works on the market model in higher education, the term “market” is perhaps best understood as a symbol subsuming a variety of business-related conceptual logics and institutional practices. At least five distinct practices have been connected to the

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Market Model and Academic Fields market as an influence on U.S. higher education: (1) the adoption of corporate practices in college and university management; (2) the adoption of corporate marketing practices for purposes of attracting students and external support; (3) commercialization of university products; (4) responsiveness to student market and labor market signals in the development of educational programs; and (5) responsiveness to the preferences of external resource providers, such as federal agencies and individual donors, in the development of educational programs. It is, consequently, not surprising that a great many activities of colleges and universities have been interpreted as reflecting the influence of “the market.” These include the influence of corporate models on internal business practices and enrollment management (Birnbaum 2000; Coopers & Lybrand 1995; Kirp 2003: chap. 6; Kraatz, Ventresca and Deng 2008); the commercialization of scientific research (Aronowitz 2000; Kirp 2003: chap. 11; Slaughter and Leslie 1997; Slaughter and Rhodes 2004; Washburn 2005), educational technologies (Slaughter and Rhodes 2004) and inter-collegiate athletics (Bok 2003: chap. 3; Schulman and Bowen 2001; Duderstadt 2000); and the adoption of corporate branding and marketing strategies for communication with the outside world (Kirp 2003: chaps 2-4). This paper concerns only one facet of the market-model interpretation of recent developments in U.S. higher education, namely, the idea that the growth and decline of academic fields is closely connected to market influences. We will focus on two market forces: changes in the market conditions for educated labor in professional and managerial occupations and the market signals associated with the preferences of external resource providers.

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Market Model and Academic Fields The trajectories of academic fields are frequent topics discussed by those who advocate thinking about universities as market institutions. In a well-known formulation, Engell and Dangerfield (1998) stated the precepts of the “market-model university” as it applies to academic fields: those academic fields most likely to be supported, they wrote, have clear links to money, either “the promise of money” (for example, high-income fields bearing on graduates’ earnings), “the knowledge of money” (for example, economics and finance fields), or “as a source of money” (for example, from new technology fields bringing donor support). (For further elaboration of this position, see Engell and Dangerfield 2005). Researchers have identified the rise of marketable and donor-supported fields in biomedical sciences, new engineering technologies, and business specializations as central to the development of higher education in recent decades (Brint, Riddle, Turk-Bicakci, and Levy 2005; Clark 1998; Gumport 2002; Kraatz and Zajac 1996; Maginson and Considine 2000). In this paper, we will subject the precepts of the market model to more rigorous empirical evaluation than has been possible thus far by examining the academic fields that grew and declined over the 25-year period, 1975-2000, in 294 U.S. colleges and universities. Specifically, we will examine the extent to which growth fields during the period of the study can be explained by either market conditions or the preferences of external resource providers. The results of this analysis raise significant questions about the capacity of the market model to explain the growth and decline of academic fields during the period. In light of the limited support in our data for the market model, we provide an empirically grounded alternative interpretation. Our interpretation acknowledges that the

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Market Model and Academic Fields preferences of large donors are a likely influence on the growth of academic fields, but it emphasizes that four other influences are important as well: (1) the conservatism of higher educational institutions, which leads to the preservation of core fields, even those that lack marketability or appeal to donors, (2) institutional and professional association interests in the preservation and expansion of labor market shelters in professional and managerial occupations for holders of educational credentials; (3) intellectual revolutions that transform the primary structures for organizing knowledge in disciplines; (4) movements to incorporate historically-marginalized populations into the structure of legitimized knowledge. We argue further that this interpretative framework sheds light on fields in decline as well as growth fields by highlighting (5) the withdrawal of colleges and universities from fields associated with industrial era economic sectors and cultural formations. Our alternative interpretation is influenced by several theoretical traditions: notably, neo-institutional theory, labor market closure theory, and scientific-intellectual movements theory.

OVERVIEW OF ACADEMIC GROWTH FIELDS, 1975-2000 We begin by providing a descriptive portrait of changes in academic fields during the period of our study. These data will serve as the foundation for our evaluation of the market model and for our alternative interpretation. We will present data both on aggregated field categories and on specific fields within categories.

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Market Model and Academic Fields The College Catalog Study Database This overview of academic field change is based on the College Catalog Study (CCS) Database. CCS includes information on changes in academic fields during the period 1975-2000 in 294 U.S. four-year colleges and universities. 2 The research team coded catalogs at five-year intervals for each of six target years 3 : 1975-76, 1980-81, 1985-86, 1990-91, 1995-96, and 2000-01. 4 CCS is designed as stratified random samples of institutions from four tiers of American four-year colleges and universities: (1) highly selective liberal arts colleges and leading research universities, (2) other selective liberal arts colleges and doctoralgranting universities, (3) masters’-granting universities, and (4) other baccalaureate granting institutions. 5 CCS does not include specialized institutions (such as art colleges, business colleges, and seminaries). Research universities were over-sampled in CCS. Over-sampling was necessary to capture a sufficient number of these influential, but less numerous institutions. Most four-year colleges and universities in the United States are small (under 2500 students). However, these small institutions enroll a low proportion of the total student population in the United States. Table 1 compares the distribution of institutions in CCS to the distribution of institutions in all U.S. four-year colleges and universities in 2000. [Insert Table 1 Here] We report results based on unweighted data. Although they represent a relatively small minority of all U.S. four-year colleges and universities, research universities and larger campuses are the primary locations of new developments in the knowledge structure of academe. To understand the type, volume, and locations of growth fields, it

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Market Model and Academic Fields is therefore important to oversample research universities and larger campuses, as we have done.

Classification of Academic Fields If a field is sufficiently institutionalized to appear in the name of an academic department, we consider this an indicator that the field has become part of the legitimized structure of knowledge in U.S. higher education. We examine fields rather than departments because departments are sometimes composed of more than one field. For example, departments of religion and philosophy are not uncommon in U.S. colleges and universities. The CCS database allows us to isolate all fields, including those joined together under one departmental roof, and to chart the trajectory of each field. The inclusion of fields located in both the arts and sciences and professional schools represents an important methodological advance in this study. We incorporate both to present a more complete picture of academic change than would be possible if we had focused solely on fields in the arts and sciences. Professional school faculty is a growing and central component of academe (Schuster and Finkelstein 2007). Moreover, many fields, such as economics and music, are located in arts and sciences in some colleges and universities, but in professional schools in many others. 6 We engaged in a process of data reduction in order to create meaningful categories from the large number of named fields represented in the raw data. During this process, fields with similar names were grouped together. Thus, the field name “neuroscience” was grouped with the field name “cognitive and neuroscience.” In some cases fields were combined under broader rubrics so as to improve statistical power.

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Market Model and Academic Fields Thus, we grouped French, Italian, Spanish, and Portuguese together as European Romance languages, and we grouped German, Dutch, and Scandinavian together as European Germanic languages. We developed a common set of categories to encompass both fields located predominantly in arts and sciences and fields located predominantly in professional schools. Our most disaggregated categorization includes 200 separate academic fields represented in CCS institutions. 7 Fields in medical schools were excluded from CCS, because resource constraints prevented the coding of the fastchanging fields represented in these very large schools. For this reason, fields such as pediatrics and oncology, which appear solely in medical schools, are not counted in our data, and fields such as bioengineering and bioinformatics, which often appear in medical schools, are undercounted in our data. 8

Growth Patterns of Aggregate Fields We begin by providing a picture of broad patterns of change among academic fields. For this purpose, we have grouped the 199 CCS academic fields into one of 10 categories: (1) advanced technology, (2) other technology, (3) advanced management and business services, (4) other business, (5) state regulatory and social control, (6) visual and performing arts, (7) communications, (8) human services, (9) education, and (10) “new cultural/identity” fields. By grouping fields in this way, we are able to provide a clear picture of the types of fields that experienced strong growth during the period, and those that did not. By advanced technology and advanced management and business services, we mean fields that have been most closely associated with dynamic sectors of the economy

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Market Model and Academic Fields characterized by relatively rapid change in intellectual technology. Some scholars have referred to these fields as “new-economy” fields (Slaughter and Rhodes 2004). 9 By “new cultural/identity” fields, we mean fields associated with historically marginalized populations: women, U.S. racial and ethnic minorities, and non-western peoples (Allardyce 1982; Boxer 1997; Frank, Schofer and Torres 1994; Olzak and Kangas 2007; Turk-Bicakci 2007; Rojas 2007).

These fields are “new” in so far as their

institutionalization in U.S. higher education is relatively recent when compared to cultural/identity fields that were institutionalized earlier in the history of U.S. higher education, such as European Studies and European Romance languages and literatures. We used more than 50 expert raters to classify fields into the advanced technology and advanced management and business services categories, as well as the two largely state-based categories (regulatory/social control and human services), because no authoritative classifications of these categories exist. (For the case of advanced technology, compare Devol and Charuwarn 2008; Ewing Marion Kauffman Foundation and Information Technology and Innovation Foundation 2008; Jorgenson and Wessner 2002; Slaughter and Rhodes 2004). 10 We used a simple majority rule for classifying fields: if more than 50 percent of experts identified a field as belonging in a particular category, we assigned the field to that category. In most cases, three-fifths or more of the experts classified fields in the same way. 11 The expert surveys produced the following results: Advanced technology fields included aerospace engineering; biomedical engineering; biophysics; biotechnology; chemical engineering; cognitive/neuroscience; computer engineering; computer/information science; electrical engineering; environmental engineering;

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Market Model and Academic Fields materials sciences; materials engineering; nanotechnology; and systems engineering. Advanced management and business services fields included advertising/marketing; business analysis; decision science; finance; international business; management science; organizational behavior; and strategy. Regulatory and social control fields included criminology; environmental design; health administration; human services administration; international relations; legal studies; military studies; public administration; and public policy. Human services fields included gerontology; child studies; community development; community services; health policy; housing studies; human services; and public health. Figures 1 and 2 provide a macro-level picture of change based on the 10 aggregate categories. Figure 1 shows trends in the five fastest-growing categories, while Figure 2 shows trends in five slower-growing categories. 12 These figures show that fields connected to advanced sectors of the economy; those connected to social control and social service functions of the state; and the new cultural/identity fields all showed robust growth. Advanced technology fields were already relatively numerous at the beginning of the time series, and experienced very rapid growth -- more than doubling -during the period. Social services fields were much less well represented at the beginning of the period, but experienced an equivalent rate of growth during the period. Fields connected to advanced sectors of corporate management, state-based regulation and social control, and historically marginalized cultural/identity groups all experienced growth rates well above 50 percent during the period as well. Arts and communications fields experienced solid growth, too, in the range of 20 to 30 percent during the period.

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Market Model and Academic Fields This rate of growth in the arts is particularly noteworthy, because arts fields were already numerous at the beginning of the time period. [Insert Figures 1 and 2 Here]

Growth and Decline of Disaggregated Fields We can gain additional perspective by examining specific fields. In the CCS database, growth fields were more than twice as common during the period than fields in decline. Of the 199 disaggregated fields in the study, 127 fields (64 percent) were represented in a larger number of institutions at the end of the period of study than at the beginning; 62 (31 percent) showed declining representation; and another 10 (5 percent) showed no change in representation. The average rate of growth of academic fields between 1975 and 2000 was 15 percent. Table 2 provides data on disaggregated fields whose growth was at least double that of the average rate of field growth. If we look only at fields that more than doubled during the period and were represented at more than 10 percent of CCS institutions by the end of the period, we see the significance of leading technology-based industries (computer science, biomedical sciences, and environmental technologies). In the business category, finance and management science grew rapidly. Some social control specialties (criminology) more than doubled during the period, as did the fields of public policy, public administration, and social services. Law and legal studies also nearly doubled. Drama, dance and art history grew rapidly in the arts, and the field of communications more than doubled. Six of the cultural/identity fields representing historically marginalized populations (women’s and gender studies, Native American

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Market Model and Academic Fields studies, multicultural studies, Near Eastern/Middle Eastern Studies, Jewish Studies, and Asian/Asian American Studies) more than doubled in size during the period, although none of the six was represented at even 10 percent of CCS institutions. [Insert Table 2 Here]

EVALUATION OF THE MARKET MODEL The data we will use to evaluate the market model describes occupational labor market conditions and the preferences of external resource providers during the period. By occupational labor market conditions, we mean changes in the average income of workers in professional and managerial fields. We draw data on market conditions from the one percent public use micro-samples (PUMS) for the 1980 and 2000 censuses. These data show median income changes (in constant 2000 dollars) by occupational fields during the period. Changes in the market conditions of PUMS fields can be compared to growth in closely related academic fields in the CCS database. By external resource providers, we mean research grants from federal agencies and philanthropic foundations, and gifts from individual donors. Our first source on external resource providers is National Science Foundation research expenditures during the period 1980-2000. Here we compare the growth in support of scientific fields through NSF funding with the growth of linked scientific fields in our college catalog database. The second and third sources are the overall levels of support for humanities and arts through the National Endowment for the Humanities and the National Endowment for the Arts, respectively, during the period 1980-2000. Our fourth source of data consists of foundation grants over $100,000 to U.S. higher education institutions.

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Market Model and Academic Fields This data comes from the Foundation Center and is analyzed for the year 2000. 13 Our fifth source of data is from the “Million Dollar List” of individual donations to higher education. The Million Dollar List is compiled by the Center on Philanthropy at Indiana University-Purdue University in Indianapolis, and includes all gifts of $1 million dollars or more to higher education from individual or family donors. Here, too, our data comes 2000, the first year data from the Million Dollar List was available by fields supported. We compare foundation grants and individual gifts in 2000 with patterns of academic field change in the most recent panel period, 1995-2000. 14 From the disaggregated set of 199 academic fields, we were able to combine fields to correspond to categories used by our sources on market conditions and external resource support. Appendix A provides the table of correspondence we used for relating PUMS occupational categories to CCS field categories. Appendix B provides the table of correspondence we used for relating NSF fields to CCS fields. Categories of correspondence used in analyses of foundation grants and individual gifts to higher education institutions can be found in the notes to Tables 5 and 6. Ours is a socio-tropic analysis (Kinder and Kieweit 1981). Our assumption is that, if the market model is correct, the broader climate of labor market incentives and donor support should register in the aggregate levels of growth of academic fields. If institutions of higher education are seeking to maximize their access to resources in the larger environment, we should observe that they are more likely to create and institutionalize organizational units in areas that are closely associated with market trends.

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Labor Market Conditions as an Influence on Academic Field Growth Table 3 compares changes in average incomes of occupations during the period 1980-2000 (in constant 2000 dollars) to growth rates of corresponding academic fields. As shown in Table 3, changes in the median income of occupations between 1980 and 2000 fail to account for the growth and decline of academic fields during the period. Some relationships in the data stand out, for example, as anomalous. Computer and information science was the fastest growing field in U.S. academe during the period, but only the 44th fastest growing field in median income (of 54 ranked fields). Conversely, clergymen and religious workers constituted only the 42nd fastest growing field in the CCS data, but were the second fastest-growing fields in median income during the period. Spearman’s Rho for the correlation of change in median income and growth rate of CCS academic fields during the period 1980-2000 was just .12 and statistically insignificant. [Insert Table 3 Here]

External Resource Providers as Influences on Academic Field Growth With the exception of large gifts from individual donors, the preferences of external resource providers also appear to have had little impact on the growth of academic fields during the period.

National Science Foundation. Table 4 compares growth of NSF expenditures by field in the period 1980-2000 (in constant 2000 dollars) to growth rates of corresponding

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Market Model and Academic Fields academic fields over the same period. Computer science was the fastest-growing category in both NSF expenditures and CCS. Moreover, agricultural biology was at the bottom of both data arrays. However, outside of these extreme cases ranks showed little correspondence (Spearman’s Rho = -.06). Metallurgy and materials engineering showed the second fastest growth among NSF fields, but the growth rates of these fields fell near the bottom in the CCS data. Several fields that suffered constant dollar losses in NSF funding – such as Political Science, Mechanical Engineering, and Psychology -- showed strong growth in the CCS data. 15

National Endowments for the Humanities and the Arts. Two agencies, the National Endowment for the Humanities (NEH) and the National Endowment for the Arts (NEA), provide funding for non-scientific fields. NEH and NEA do not break out expenditures by fields, but we can gain a perspective on the influence of external support on the humanities and arts by comparing overall levels of funding to overall levels of growth in humanities and arts fields. Figure 3 provides data on NEH and NEA funding during the period 1975-2000 (in constant 2000 millions of dollars). Funding for both agencies declined dramatically during the period, from highs of nearly $350 million in 1979 to just over $100 million in 2000, a 72 percent decline. Rather than declining, the number of arts fields in CCS grew by 21 percent during the period 1975-2000, while the number of humanities fields also grew, albeit more slowly, by 3.5 percent. [Insert Figure 3 Here]

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Market Model and Academic Fields Philanthropic Foundations. Table 5 provides evidence on foundation support for higher education institutions in 2000. In this table, we report on two 10 percent samples from the list of more than 6500 foundation grants over $100,000 to U.S. higher education. Each 10 percent sample was drawn without replacements and had more than 600 observations, suggesting that sampling errors are likely to be very small in estimating the population proportion of giving that is directed at major fields. The two separate 10 percent samples produced similar results, further suggesting that the estimate of population proportions of grants going to major fields are quite accurate. Again, a number of anomalies stand out in Table 5. Education received one of the highest shares of foundation support, though the number of education fields remained flat in CCS institutions during the period 1995-2000. By contrast, both communications and new cultural/identity fields grew significantly during the period, but were near the bottom of the list of recipients of foundation grants. 16 Spearman’s Rho confirms the weak relationship between the distribution of foundation grants and academic field growth. Spearman’s Rho for number of grants and CCS field growth was .11, while Spearman’s Rho for dollars in grants and CCS field growth was .26. In both cases, the rank-order correlation was insignificant. [Insert Table 5 Here]

Individual Donors. As compared to the other sources of external support we consider, the preferences of large donors correspond relatively well to the growth of academic fields, as shown in Table 6. Spearman’s Rho for number of gifts and CCS growth rates was .50, while Spearman’s Rho for dollar amount of gifts and CCS growth

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Market Model and Academic Fields rates was .51. These associations are high, but they do not reach statistical significance because of the small number of categories in the analysis. 17 Again, some anomalies stand out. Business and management fields, mid-ranked among CCS growth fields, received the second largest number and the second highest dollar amount of funding. Conversely, new cultural/identity fields were not funded at all by individual donors in this data, but were the fastest growing of the CCS academic categories corresponding to donor data during the most recent five-year panel period. 18 Nevertheless, this data suggests that the priorities of large donors and those of colleges and universities were relatively closely aligned. The relationship between large gifts and academic growth fields consequently bears further investigation. Fund-raising is commonly defined as an exchange of values between institutions and donors (Council for Advancement and Support of Education 2009), and development officers are expected to solicit funding first for activities that are explicitly defined as institutional priorities. At the same time, college and university priorities may be at least partially determined by assessments of the types of projects donors are interested in supporting. [Insert Table 6 Here]

Summary. The available data show, at best, mixed support for the market model as it applies to the growth and decline of academic fields in U.S. colleges and universities during the last quarter of the 20th century. Growth in academic fields was not clearly related to changes in the median income of corresponding occupations, the best indicator available of market conditions for educated labor during the period. Growth in scientific fields was not related to growth in National Science Foundation support for these fields,

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Market Model and Academic Fields and rapidly declining government support for the arts and humanities during the period did not prevent solid growth in the arts within higher education or slow growth in representation of humanities fields. Nor was growth in academic fields clearly related to the preferences of philanthropic foundations, at least not during the last years of our data series. The relationship between growth in academic fields and the preferences of individual donors was stronger, but still far from a one-to-one correspondence. Moreover, the fastest growing of all categories corresponding to the donors’ data (i.e. the new cultural/identity fields) received no gifts of $1 million from individual donors.

AN ALTERNATIVE INTERPRETATION Because colleges and universities are relatively open systems (Hackman 1985; Miller 1978), many forces can come into play when universities develop new fields. The data discussed above suggest that the preferences of large donors are one of these forces. However, a more complete understanding requires conceptualizing U.S. higher education as composed of conservative institutions which tend to preserve well-established fields of knowledge in the arts and sciences. These institutions are simultaneously interested in monopolizing access to the higher levels of professional and managerial occupations for holders of higher education credentials. Further, colleges and universities are also sociocultural institutions. This means that they are open as well to intellectual revolutions in the disciplines and well-supported movements of cultural and social change. Finally, under relatively mild levels of resource pressure, they are inclined to withdraw from industrial sectors, as well as from communications media and cultural/identity fields, that

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Market Model and Academic Fields were the centers of earlier social formations but are no longer as central under current historical conditions. Our alternative approach thus combines elements of neo-institutionalism (DiMaggio and Powell 1991; Meyer and Rowan 1977), labor market closure theory (Freidson 1985; Parkin 1983), and scientific-intellectual movements theory (Frickel and Gross 2005). Neo-institutional theory helps us to explain the tendency of higher education institutions to preserve core academic fields, even if they are not highly marketable or attractive to external resource providers. Core fields provide legitimacy and autonomy for educational institutions precisely in so far as they are defined as oriented primarily to intellectual rather than economic considerations. Labor market closure theory is particularly relevant to the applied fields that have become incorporated into higher education. It helps to explain the relatively strong relationship between academic growth fields and changes in the professional and managerial occupations, those parts of the occupational structure historically most closely connected to higher education. Closure theory argues that higher education institutions are oriented less to responding to market conditions than to the growth of occupations already incorporated into the credential system and to occupations closely related to those already incorporated. Further, it sees higher education institutions, abetted by professional associations and the state, as attempting also to make inroads into professional and managerial occupations historically open to non-credentialed workers by making the case that formal training is required to guarantee acceptable standards of practitioner performance. Scientific-intellectual movements theory helps explain selected

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Market Model and Academic Fields reorganizations of academic fields, as well as the rise of new cultural/identity fields, by drawing attention to analogies between intellectual movements and social movements. 19

Core Academic Fields Fifteen academic fields were represented in at least two-thirds of the CCS institutions in 1975-6. Fourteen of these fields continued to be represented at two-thirds or more of the CCS institutions in 2000-1. 20 These 14 can be considered the core academic fields in American higher education during the last quarter of the 20th century. This core included the natural science fields of mathematics, biology/life sciences, chemistry, and physics. It included the social science fields of psychology, economics, political science, and sociology. It also included the humanities fields of English, history, foreign languages and literatures, and philosophy; and the fine arts fields of studio art and music. Nearly all of these core fields were institutionalized during the late 19th and early 20th centuries, the period in which the German research university model, with its emphasis on categorical organization of research specialists, was imported to the United States (Bledstein 1976: chap. 8; Haskell 1977; Rudolph 1976; Veysey 1965: chap. 3). Computer science joined the core during the period, and the theatrical arts, represented in nearly two-thirds of institutions in 2000, arguably also joined the core. [Insert Table 7 Here] Not all of these core fields are highly marketable or well supported by external resource providers. Indeed, the qualitative social sciences and the humanities lack market power and receive relatively little support from external resource providers. In addition, both physics and mathematics experienced both declining enrollments and declining

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Market Model and Academic Fields support from external resource providers during the period (Brint et al. 2005). Nevertheless, colleges and universities showed impressive levels of inertia in relation to core fields. In the CCS sample, none of the 14 core fields in 1975-6 grew by ten percent during the period and none declined by more than five percent.

The Credential System and Labor Market Closure Within this context of continuing commitment to core arts and sciences fields, our interpretation emphasizes the interests of colleges and universities in monopolizing access to professional and managerial occupations for holders of higher education credentials. This interpretation focuses attention on the interests of colleges and universities in coverage of expanding fields connected to the credential system, rather than their responsiveness to the market conditions affecting fields. Brint (1994: chap. 3) identified five “spheres of social purpose” closely linked to the higher education credentialing: (1) advanced technology, (2) business services, (3) culture and communications (including scholarship, arts, and media), (4) civic regulation, and (5) human services. In each of these spheres, higher degrees became common -- and in some occupations normative -- during the 20th century, due to the perceived cognitive demands required for effective practice. In many cases, professional associations effectively lobbied the states for stricter credential requirements as ways to limit competition and raise salaries, as well as to improve practice standards (see Abbott 1988; Freidson 1985; Larson 1977; Wilensky 1964). If colleges and universities are fundamentally concerned with the maintenance of labor market shelters in occupational specializations, we should expect that the growth of

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Market Model and Academic Fields occupations connected to the credential system will be more important to academic field growth than changes in the salary incentives of occupations. Our data shows support for this proposition. Table 8 shows a strong and significant relationship existed during the period 1980-2000 between occupational growth in the professional and managerial categories and the growth of corresponding academic fields. Spearman’s Rho for this association is .34 and statistically significant. The correlation is substantially higher than that between changes in median incomes and growth in corresponding academic fields (Spearman’s Rho =.12). Colleges and universities moved, in particular, to develop programs for occupations that began the period tilting only moderately in the direction of credentialbased access. The rank order correlation for academic field growth and occupational growth was higher (Spearman’s Rho = .54, p < .01) in the 26 professional and managerial occupations that began the period with at least half but less than 80 percent of workers holding baccalaureate or higher level degrees. This group included many engineering, management, and health professions, as well as social work and social science professions. Much less decisive movement was evident in the 16 census professional and managerial occupations with fewer than half of workers holding baccalaureate or higher level degrees (Spearman’s Rho = .07). [Insert Table 8 Here] Although the relationship between growth in occupations and academic fields is strong, some anomalies exist here as well. For example, dance was the second fastest growing academic field, but one of the slowest growing occupational fields. Similarly, foresters and conservation scientists were one of the faster growing academic fields, but

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Market Model and Academic Fields they placed at the bottom of occupational growth during the period. Conversely, specialists in recreation and leisure were one of the fastest growing occupational groups, but one of the slowest growing academic fields. These anomalies suggest that a fully adequate interpretation will need to take into account non-occupational influences on field growth, including the expressive interests of students and the status positioning of colleges and universities in relation to occupations (see Brint et al. 2005).

Scientific-Intellectual Revolutions In mature academic systems, far-reaching reorganizations of existing fields are rare. For the most part, scientific-intellectual movements occur within the disciplines rather than across them (see, e.g. Abbott 2001; Collins 2003; Frickel and Gross 2005; Oakley 1997). However, in these rare cases, whole disciplines may be reconstituted along substantively different lines in order better to accord with strategic sites of knowledge advancement. Such far-reaching reorganizations can be termed “scientificintellectual revolutions.” Such a revolution occurred in the life sciences in the 1980s, as taxonomic forms of classifying knowledge gave way to reorganization based on strategic sites for understanding processes of organic development and evolution -- and the application of engineering technology to biological and biomedical processes (Abir-Am 2002; Jong 2008; Judson 1979). CCS data showed declines, for example, in anatomy (11%), botany (-54%), and zoology (-65%), together with growth in genetics (50%), biochemistry (65%), molecular biology (144%), and ecology (156%), the latter as part of environmental science. Still higher levels of growth were found in biomedical engineering (375%) and bioengineering (633%).

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Market Model and Academic Fields Intellectual revolutions are rarely, if ever, driven solely by the logic of the internal development of scientific understanding. In the case of the biological sciences, the Rockefeller Foundation played an important role in the institutionalization of molecular biology, in part due to its long-term strategic planning with scientists (Abir-Am 2002). New forms of organization were also well supported by businesses, such as biotechnology and bioengineering firms, which expected to profit from new breakthroughs (see, e.g., Kay 1993; Powell, White, Koput, and Owen-Smith 2005; Washburn 2005). CCS data also showed two borderline cases of scientific-intellectual revolution. During the period, educational studies departed from organization around age-graded organizational segments (primary and secondary education declined by nearly 30%) and in the direction of “pedagogical science” (curriculum and instruction grew by 124% and educational measurement and research by 800%) (see Lagemann 2002). Business studies shifted from organization along the lines of administrative and functional categories (business administration declined by 41%) in the direction of a more “scientific” orientation (decision science and strategy grew by 433% and management science by 91%). Some of this change reflects symbolic status mobility through adoption of labels associated with the prestige of science, but some undoubtedly also reflects real changes over time in the conceptualization and teaching of management subjects (Rawlings 2005).

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Market Model and Academic Fields The Incorporation of New Cultural/Identity Fields We have separated the new cultural/identity fields from other instances of scientific-intellectual revolution in U.S. academic life. The separation is warranted by the very different circumstances that gave rise to these socially incorporative fields. Here intellectual revolution was due, not only to fundamental rethinking of the organization of existing disciplines, but also to the creation of fields based on demands for greater cultural representation of historically marginalized populations. The growth of these fields represents a particular difficulty for the market model; in the aggregate, they were among the fastest growing of all categories (+89%), in spite of having little direct connection to the labor market and little support among external resource providers. Previous scholarship has shown that many women’s studies and ethnic studies programs originated in the responsiveness of colleges and universities to social movement activism (see, e.g., Boxer 1997; Olzak and Kangas 2007; Rojas 2007; TurkBicakci 2007; Slaughter 2002). Demographic changes – notably, the growing representation of women, minorities, international students, and immigrants on college and university campuses -- lent background support to these gender and racial-ethnic movements of social incorporation (Smelser 1994). The new cultural/identity fields also quickly gained outside support from a number of key liberal philanthropies, including the Ford Foundation and the Carnegie Corporation (Shiao 2005), because of their promise to increase social inclusiveness. National higher education advocacy organizations, such as the Carnegie Foundation for the Advancement of Teaching and the American Association of Colleges and Universities, funded by liberal philanthropies, also fostered the growth of these fields (Brint, Turk-Bicakci, Proctor, and Murphy 2009).

25

Market Model and Academic Fields Intellectual influences were clearly also involved in the rise of the new cultural/identity fields. In particular, the work of French literary and social theorists, such as Derrida, Foucault, and Lacan, on the interplay of culture and power led to a theoretical approach that called into question taken-for-granted claims to objectivity in textual interpretation and created intellectual space for analyses of the subtle ways that power operated in both literature and social life (see Cusset 2003; Frickel and Gross 2005). These writers, and those who followed them, analyzed “texts,” both literary and social, as reflecting at once living historical cultures and social constructions based on their own peculiar classifications and codes.

Declining Fields: The Mirror of Growth Fields A good interpretation of the growth of academic fields should also be capable of interpreting the decline of academic fields. Our analysis of declining fields mirrors in many ways our findings for growing fields. During the period, CCS growth fields were linked to new-economy sectors (advanced technology and advanced business services), new media (broadcast, film, and internet), and new cultural/identity categories. By contrast, as Table 9 indicates, fields linked to the older economic sectors of agriculture and manufacturing (home economics, agricultural specialties, and industrial engineering), oral and print media (speech, library science, and journalism) and historically dominant cultural/identity categories (European languages and literatures) all experienced declines during the period. Insert Table 9 Here]

26

Market Model and Academic Fields DISCUSSION This paper makes three contributions to the sociology of U.S. higher education. First, it debunks the conventional wisdom that U.S. colleges and universities are responsive above all to market signals. Second, it makes a rigorous evaluation of the market model possible for the first time by collecting extensive data both on the growth and decline of academic fields and on a wide variety of market signals. Finally, it offers an empirically supported alternative interpretation of the growth and decline of academic fields during the period of the study. This alternative interpretation accepts that large donors help to shape the climate of priorities of academic institutions. However, it emphasizes influences that do not fit the market model. In addition to noting the preservation of legitimacy conferring core fields, many of which lack market power, we have counter-posed an occupational closure model to the market model. The most important source of change in this model is the interest of occupational practitioners and higher education institutions in creating labor market shelters for the holders of academic credentials. Income growth in occupations is clearly less important to colleges and universities than occupational growth. This is understandable, given the interest of colleges and universities in controlling access to a wide range of occupational fields, rather than only to fields in which salaries are increasing. As mass institutions enrolling students with a wide variety of interests and abilities, colleges and universities act more like occupational alliance partners than investors in an occupational stock market. Along with the traditional arts and sciences fields, our data show that advanced technology and advanced management and business service fields are at the heart of the

27

Market Model and Academic Fields contemporary growth of knowledge fields in U.S. colleges and universities, just as the related occupations are at the heart of the U.S. economy. But they are not the only sphere of social purpose served by higher education. State-based regulatory and human services fields and the consumption-driven fields of the arts and communication are also fast growing. Colleges and universities seek to monopolize at least the upper levels of these occupations for their graduates through the institutionalization of educational requirements, sometimes backed by the force of law. Education itself provides the personnel for training and much of the research that allows for reflexivity in each of these professionalized spheres of social purpose (Freidson 1985: chap. 4). The primary reason why patterns of growth and decline of academic fields do not fit the market model is that the higher education credentialing system has broader ambitions than responding to market signals. For this reason, an imperial metaphor makes better sense of the results of our analysis than a market model. U.S. colleges and universities can be conceived, collectively, as institutional units of an expansionary system, which at once maintains autonomy from the occupational structure through the preservation of its arts and sciences core and is, at the same time, closely connected to developments in the occupational structure. This system tends to protect core intellectual “territories” (i.e. the traditional arts and sciences) that were institutionalized long ago and continue to be valuable for maintaining autonomy and legitimacy. Its expansion is otherwise closely tied to changes in the upper reaches of the occupational structure. Fields tend to expand as occupations tied to credential system expand. Colleges and universities also move selectively into professional and managerial fields still open to non-credentialed workers. Intellectual territories occasionally reorganize in response to

28

Market Model and Academic Fields the interests of leading faculty in greater cognitive effectiveness and better funding opportunities, and in response to pressures for change from social movement organizations. Finally, colleges and universities withdraw, very gradually, from intellectual territories that show persistent signs of long-term decline in economic significance and cultural immediacy. Our interpretation differs not only from the market model, but from other interpretations of academic change as well. It stands in particularly marked contrast to views of academic change that focus primarily on internally generated scientific and cultural revolutions (see, e.g., Kuhn 1962; Metzger 1987). Of course, such internally generated reorganizations do occur, but their effects are more often found within disciplines (see, e.g., Abbott 2001; Collins 2003; Frickel and Gross 2005; Oakley 1997) and only rarely lead to fundamental changes in the broader organization of academic fields. Only a very few disciplines were reorganized during the period due to new thinking about sources of intellectual advance. Our interpretation also stands in contrast to the idea that colleges and universities are the inclusive “service stations” of society. Beginning with Kerr (1963), some have argued that the modern university is not only attuned to economic growth, but also to social incorporation. Whereas Kerr emphasized the university’s interest in reaching out to every important constituency in its region or state, Ramirez (2005) emphasized the university’s roots in values of progress and justice as a source of its socially incorporative outlook. In our view, such analyses fail to account for the selective character of academic movements of social inclusion. CCS data, for example, shows that such marginalized groups as labor and community organizations have experienced little

29

Market Model and Academic Fields incorporation into the knowledge structure of colleges and universities. In the CCS data for 2000, we find just four cases of labor studies and ten cases of urban or community studies. It is consequently more accurate to say that colleges and universities are selectively inclusive and those selective processes are greatly influenced by social movement activism, as well as by the advocacy of liberal philanthropies. Finally, we see little basis in these data for the idea that vulnerable fields are those most closely connected to subordinate populations, as argued by Gumport (1993) and Slaughter (1993) and suggested by many other critics of U.S. higher education. Indeed, many fields in which women play a prominent role (such as women’s studies and gender studies) grew during the period of our study, as did several fields serving the needs of subordinate populations (such as social services and public administration). Instead, colleges and universities during the period of our study demonstrated a progressive orientation by very gradually eliminating fields associated with older economic eras, older communications media, and previously-integrated European cultural groups. Many fields connected to subordinate populations grew robustly during the period, reflecting the expansion of human services occupations, as well as the incorporation of new cultural/identity fields connected to historically marginalized groups.

Notes 1

We would like to thank the National Science Foundation, the Spencer Foundation, and

Atlantic Philanthropies for grants that supported the creation of the databases used in this paper. We also thank Jerry A. Jacobs, David F. Labaree, Kerry Mulligan, Craig Rawlings, and Matthew Rotondi for comments that improved the quality of this paper.

30


2

To collect the catalogs, the research team contracted with CollegeSource, Inc., a San

Diego-based company specializing in the reproduction of college catalogs on microfiche and, since the mid-1990s, online.

3

In some cases, catalogs were not available in the target year. In these cases, we used

catalogs from the next available adjacent year. If a catalog for 1985-6 was not available, for example, we used the catalog for 1986-87.

4

The research team made every effort to ensure high quality coding of college catalogs.

Coders were given detailed instructions about coding data. Experienced coders were assigned to inexperienced coders for purposes of answering difficult questions. Weekly meetings were held to discuss coding issues. Catalogs of the largest institutions and those with the most complex catalogs were coded twice. The two results were compared and discussed until coders resolved differences in coding. Altogether, second codes were conducted on 15 percent of sample institutions.

5

CCS is linked to a larger data archive, the Institutional Data Archive (IDA) on American

Higher Education. IDA includes more than 2000 variables measuring institutional characteristics; student characteristics; research, academic, and extracurricular programs; and the backgrounds and attitudes of institutional leaders over the same 25-year period for 385 U.S. four-year colleges and universities (reference masked). CCS includes all

31


IDA institutions for which a full set of catalogs were available in each of the six target years. 6

In a few universities, the same fields were located in more than one unit. In these cases,

we counted each appearance of the field. 7

The research team took a number of precautions to improve the accuracy of its coding

of college catalogs. Student coders were given detailed instructions on coding, with particular attention to the coding of potentially ambiguous data. Experienced coders were designated to provide advice on difficult decisions. In addition, the research team held regular meetings to discuss coding issues. Independent checks, based on complete recoding of institutions, were conducted on approximately 20 percent (56) of the sampled institutions. These independent checks were conducted on the larger and more complex institutions, and on those institutions whose catalogs were most difficult to interpret. Because of the checks and protections built into the process, we are confident that we obtained a high level of accuracy in the coding of the college catalogs.

8

Although we collected data on fields in dental schools, we excluded this data because

the closing of one CCS dental school led to declines in every dental field. Because of the small number of dental schools in the sample, we concluded that generalizations about fields in dental schools were not warranted from this data.

9

In most accounts, the new economy is composed of industries in which the decision

environment of practice is unstable, technological change is rapid, and in which new 32


mechanisms for generating profits are quickly adopted by firms. Interpretations of the growth of academic fields based on “new-economy” industries represent a contemporary updating of the concept of “post-industrial society” (Bell 1973). Where the idea of postindustrial society included non-profit and government services in education, health, and quality of life occupations, as well as high tech industries, the idea of new-economy industries shifts the focus more completely to advanced sectors of the for-profit economy, building on the reconsideration of the concept of post-industrial society by Stanback et al. (1981), Sassen (1991) and others.

10

We contacted 42 experts on post-industrial economic change and 42 experts on the

state. We received 25 and 27 completed responses, respectively. The names of these experts are available on request. We excluded the responses of five state experts who said they did not feel comfortable making the distinction that we requested between state regulatory and state social welfare fields.

11

Of 28 technology fields, only two – aerospace engineering and chemical engineering –

produced near 50-50 splits among the expert raters. Based on the simple majority rule, we classified both as advanced technology fields. Of 19 business fields, two fields – advertising/marketing and organizational behavior – produced near 50-50 splits. Again, based on the simple majority rule we classified both as advanced management/business services fields. Of 32 state-based fields, two non-education fields – health administration and urban studies -- produced near 50-50 splits. We counted both as social control/ regulatory fields. However, we bent our rule for health administration. A slight majority

33


of respondents who said they could classify the field (13 of 25) classified it as a social welfare field. For purposes of consistency, we assigned it to the social control/ regulatory category, because all other fields with the term “administration” in their titles were assigned by experts to this category.

12

In these figures, we exclude core fields in the arts and sciences, such as physics,

psychology, and English. These fields show impressive stability, and we discuss them as part of our alternative interpretation.

13

Data from the Foundation Center are available for three preceding years, but the cost of

obtaining this data was prohibitive.

14

Because data on foundation grants and individual donations were not available for

1995, the first year in the most recent college catalog panel series, we were unable to compute statistics on the growth and decline of giving in particular academic field categories during this most recent panel period, and relied instead on the weaker assumption that the giving climate in 2000 was similar to that of the giving climate in the preceding four years. Accordingly, we consider our analyses comparing field change to the limited available data on the preferences of foundations and individual donors as suggestive, rather than definitive. Although we do not know which fields were supported in 1995, we do know that overall rates of giving to higher education were quite consistent during the period. A positive rank-order correlation between level of support in 2000

34


with rates of field growth between 1995 and 2000 is consistent with the hypothesis that external resource environments determine the direction of curricular change within higher education institutions.

15

Other federal agencies also provide support for scientific fields. The largest funding

agency is the National Institutes of Health (NIH), with annual expenditures more than five times that of NSF. We do not analyze NIH funding, because, as noted, medical fields are outside the scope of this study.

16

Not all foundation grants to higher education institutions went to academic fields. In

our sample, more than two-fifths of foundation grants to higher education institutions (44 percent) were for non-academic field based purposes, such as scholarships, libraries, student services, and building renovations. More than one-third of foundation grants, as measured by dollars (35percent), were for these latter purposes.

17

When new cultural/identity fields are left out of the calculations, the rank-order

correlation between dollar amount of gifts and CCS growth rates is stronger, at .58 and statistically significant.

18

As in the case of foundation grants, not all individual gifts to higher education

institutions went to support academic fields. Individual donors were, indeed, far less likely to support academic fields than other university activities. More than two-thirds of the gifts, both in numbers and dollar amounts, were for non-academic field based

35


purposes, such as scholarships, libraries, student services, and building renovations. Undefined, restricted-use contributions were particularly prevalent, representing nearly half of total gifts.

19

Several considerations led us to conclude that statistical modeling would not produce

substantively meaningful or sufficiently precise results. The most important is that the available data do not allow us to measure a single dependent variable, such as percentage growth in the 200 disaggregated fields over time. Instead, the data related to market forces are available only in broad, incommensurable categories. The imputation of values for broad fields generates a variance restriction and biases against resource dependency arguments which would be more properly measured in relation to highly disaggregated fields. Even if a single, useful dependent variable could be constructed, measurement issues related to independent variables in the model would present formidable obstacles to modeling. The level of concordance between census occupational fields and CCS academic fields is acceptable for rank-order correlations, but in a multivariate context the validity of effects size estimates would be questionable.

20

Physical education, a core field in 1975-6, declined during the period. The declining

representation of physical education is likely related to its absorption by newer fields – such as recreation and leisure, on one side, and kinesthesiology, on the other -- and by the surge of fitness activities among young people, reducing the need for colleges and universities to require physical fitness activities in the curriculum.

36


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Table 1 College Catalog Study Sample Characteristics, 2000

Type of Institution Public Religious Doctoral-Granting Universities Masters-Granting Universities Baccalaureate-Granting Colleges Specialized Institutions* SAT/ACT Top Quintile SAT/ACT Bottom Quintile Coastal Regions (West,New England, Mid-Atlantic)

College Catalog Study Institutions (%)

All Four-Year Colleges and Universities (%)

45.5 28.0 28.3 31.5 40.2 NA 30.4 14.5 39.2

27.9 33.2 11.7 25.9 30.4 32.0 19.1 21.5 39.6

Sources. – Higher Education Directory (2000); College Catalog Study Database. Notes. – The number of institutions are as follows: CCS Institutions (N=294); All FourYear Colleges (N = 1958). * Carnegie “specialized institutions” include such four-year institutions as: art institutes, business colleges, military institutes, and seminaries.

Table 2 Growth in Disaggregated Academic Fields, 1975-2000

Field

Change N 2000 (%)

Advanced Technology Cognitive Science* Computer Engineering Biological Engineering Biomedical Engineering/Science Environmental Engineering Computer Science Molecular Biology Biochemistry/Bioengineering Electrical Engineering

17 47 22 19

--2250.0 633.3 375.0

48 254 22 56 85

300.0 225.6 144.4 64.7 32.8

State Regulatory/Social Control Criminology International Relations Public Administration/Policy Law, Legal Studies Environmental Design Health Administration/Policy

53 23 33 40 7 19

194.4 187.5 135.7 90.5 75.0 58.3

Field

Change N 2000 (%)

Advanced Management/Business Services Decision Science/Strategy International Business Organizational Behavior Business Law Finance Management Science Marketing/Advertising

16 8 14 13 89 150 94

433.3 166.7 133.3 116.7 97.8 89.8 88.0

Visual and Performing Arts Dance Art History Creative Writing Music Composition History of Music Musical Instruments Architecture Drama

68 51 5 9 16 22 45 191

257.9 183.3 150.0 80.0 77.8 57.1 32.4 29.1

Table 2 (Continued)

Field Communications Rhetoric Communications Broadcast Communications Film and TV New Cultural/Identity Gender Studies/Women's Studies American Indian Studies African Languages/Literatures Cultural Studies Near Eastern Languages/ Literatures Near Eastern Studies/Middle Eastern Studies Asian, Asian-American Studies Asian Languages/Literatures Hispanic, Latin American Studies

N 2000

Change (%)

8 152 39 30

166.7 149.2 129.4 50.0

20

1900.0

4 3 17 14

300.0 200.0 142.9 133.3

8

100.0

16

77.8

48 15

71.4 66.7

Field Human Services Human Development Gerontology Social Services Community Development Other High Growth Fields School Leadership* Arts & Sciences/Liberal Arts* Educational Research Manufacturing Consumer Science Communications Disorders Construction Human Resources Landscape Architecture Rehabilitation

Source. – College Catalog Study Database. * No counts in 1975.

N 2000

Change (%)

19 6 107 5

533.3 200.0 154.8 150.0

28 11 18 14 26 31 19 8 14 6

----800.0 600.0 420.0 210.0 171.4 166.7 133.3 100.0

Table 3 Changes in Median Income of Occupations and Academic Field Growth, 1980-2000 Occupation Lawyers and Judges Clergy and Religious Workers Art/Entertainment Performers Art Makers Pharmacists Musician or Composer Dancers Registered Nurses Speech Therapists Physical Therapists Occupational Therapists Managers and Public Administrators Management Analysts Mathematical Sciences Dietitians and Nutritionists Librarians Electrical Engineer Editors and Reporters Managers of Medicine and Health Occupations Designers Teachers Accountants and Auditors Architects Managers of Properties and Real Estate Chemical Engineers Engineers, n.e.c. Industrial Engineers Foresters and Conservation Scientists Financial Managers Mechanical Engineers Urban and Regional Planners Petroleum/Mining/Geological Engineers Chemists Social Workers Archivists and Curators Aerospace Engineer Biological Scientists Operations and Systems Researchers and Analysts

1

2

3

4

5

104 59 56 55 55 53 48 47 46 46 44 39 37 30 26 26 24 23 21 20 19 18 18 18 18 17 16 15 15 15 15 14 11 11 11 11 10 9

55000 28000 33000 12100 62000 11050 14650 40000 36000 42000 38000 69000 48000 57000 32000 35000 65000 33700 53000 30000 32300 40000 42000 37000 66000 60000 54000 41000 60000 60000 44400 70000 47000 30000 30200 65000 36650 51000

8 42 23 39 48 28 2 18 17 5 7 46 3 28 32 51 21 43 12 4 44 15 25 20 27 16 47 13 6 19 41 49 28 14 50 24 32 11

67 - 6 17 - 2 -29 6 106 30 31 78 70 -26 100 6 2 -56 21 - 9 46 86 -12 35 14 22 9 34 -27 42 75 26 - 5 -48 6 37 -50 16 2 52

40 174 191 248 32 248 68 121 59 16 17 104 18 337 43 18 85 41 19 26 477 109 66 11 59 157 54 125 89 86 36 12 248 107 1 58 428 179

Table 3 (Continued) Occupation

1

2

3

4

5

Physicists and Astronomers Managers in Education and Related Fields Economists and Market Researcher Human Resources Computer Systems Analysts and Computer Scientists Atmospheric and Space Scientists Managers and Specialists in Marketing/Advertising/Public Relations Civil Engineers Psychologists Geologists Agricultural and Food Scientists Recreation Workers Metallurgical and Materials Engineers Physical scientists, n.e.c. Sociologists; Social scientists, n.e.c.

9 9 8 8 7

64000 50000 50000 44000 50000

32 9 31 37 1

2 59 5 0 131

296 70 254 8 302

6 5

50000 55000

6 10

75 57

14 94

5 5 3 2 0 - 1 - 2 - 5

55000 30000 44000 36000 20000 56000 40000 31000

26 32 40 45 44 22 37 32

12 2 - 3 -18 -12 19 0 2

74 263 140 145 64 32 19 825

Sources. – College Catalog Study Database; U.S. Bureau of the Census (2003). Notes. – Column labels are as follows: 1 = Percent change in median income 1980 to 2000; 2 = Median Income in 2000 constant dollars, 2000; 3 = CCS field growth ranking; 4 = Percent growth in CCS fields, 1980 to 2000; 5 = Number of CCS fields, 2000. All occupational data is based upon occupation holders with a bachelors degree or higher. Detailed information about census occupational categories and department field categories can be found in Appendix A.

Table 4 National Science Foundation Expenditures and CCS Growth Fields, 1980-2000 National Science Foundation Field

1

2

3

4

5

Computer Sciences Metallurgy & Materials Engineering Mathematics Biology and Environmental Biology Chemical Engineering Astronomy Electrical Engineering Chemistry Environmental Sciences, Atmospheric Sciences and Oceanography Civil Engineering Physics Geological Sciences Political Science Economics Sociology Mechanical Engineering Psychology Astronautical and Aeronautical Engineering Agricultural Biology

755 193 85 54 49 40 21 5 2

348705 117777 96598 389839 44040 47098 50162 145675 235315

107 - 12 6 - 4 9 25 61 0 93

1 18 10 16 9 6 3 13 2

255 44 337 508 59 79 137 226 83

1 - 13 - 14 - 17 - 22 - 44 - 73 - 81 - 100

40458 166619 95472 5756 15356 4306 6532 4393 0

39 - 4 - 3 21 1 0 26 5 16

4 17 15 7 12 13 5 11 8

167 217 140 326 268 226 86 320 58

- 100

0

- 12

19

161

Sources. – College Catalog Study Database; National Science Foundation (2004). Notes. – Column labels are as follows: 1 = Percent growth in NSF funding, 1980-2000; 2 = Average NSF funding 1999-2001; 3 = Percent growth in CCS fields, 1980- 2000; 4 = CCS field growth ranking; 5 = Number of CCS fields, 2000. College Catalog Study academic field categories corresponding to National Science Foundation Science and Engineering field categories can be found in Appendix B.

Table 5 Foundation Grants to Colleges and Universities, 2000 and Academic Field Growth, 1995-2000 Field

1

2

3

4

5

6

Medicine/Biomedical1 Engineering/Computer Science/ “New Sciences”2 Education3 State Regulatory4 Business/Management Arts Traditional Sciences5 Religion Social Welfare6 Traditional Humanities Traditional Social Sciences7 Communications Agriculture/Veterinary New Culture/Identity

144.7 89.7 50.9 39.9 35.7 17.1 17.0 15.9 14.2 5.2 5.0 3.0 1.0 0.0

33.1 20.5 11.6 9.1 8.2 3.9 3.9 3.6 3.2 1.2 1.1 0.7 0.2 --

144 108 69 95 25 32 60 23 49 9 20 8 7 0

22.4 16.8 10.7 14.8 3.9 5.0 9.3 3.6 7.6 1.4 3.1 1.2 1.1 --

NA 15.8 - .8 7.6 2.1 3.5 - .1 - .8 -1.4 - .3 -2.0 4.2 -6.5 16.1

NA 2 9 3 6 5 7 9 11 8 12 4 13 1

Total Academic Fields

437.6

642

Source. – College Catalog Study Database; The Foundation Center (2001). Notes. – Column labels are as follows: 1 = Total dollars (in millions); 2 = Total dollars as percent of Total fields; 3 = Number of grants; 4 = Number of grants as percent of total fields; 5 = Percent growth in CCS fields 1980 to 2000; 6 = CCS field growth ranking. 1 Includes grants for medicine, biomedical/medical research, public health, and nursing/nursing research. Includes one grant for $82.7 m. (18.9% of total academic field-based grants). Excluding this outlier changes the medical total to $62 m. 2 Includes grants for new engineering specialties, computer science, environmental science, cognitive/neuroscience, genomics/biotechnology. 3 Includes grants for K-12 education and higher education research/advocacy. 4 Includes grants for public affairs/public policy, international relations, law/legal studies, criminology, and national security. 5 Includes grants for physics, chemistry, biology, biochemistry, and mathematics/statistics. 6 Includes grants for social welfare and urban/community studies. 7 Includes grants for demography, economics, labor studies, political science, and social sciences, not specified.

Table 6 Millar Dollar Gifts to Colleges and Universities 2000 and Academic Fields Growth, 1995-2000 Field Medicine/Biomedical1 Business/Management Engineering/Computer Science/New Sciences2 Traditional Sciences3 Arts State Regulatory4 Communications5 Misc. Applied Fields6 Traditional Humanities7 Religion New Cultural/Identity8 Traditional Social Sciences9 Education State Social Welfare Total Field-based Gifts

1

2

3

4

5

6

208.2 186.7 184.1 125.7 114.8 66.3 37.0 29.5 14.6 16.8 6.5 4.7 3.7 0.0

20.5 18.3 18.1 12.4 11.3 6.5 3.6 2.9 1.4 1.6 .6 .5 .4 --

35 26 19 17 22 20 7 11 6 4 4 3 3 0

19.8 14.7 10.6 9.6 12.4 11.3 4.0 6.2 3.4 2.3 2.3 1.7 1.7 --

NA 2.1 15.8 - .1 3.5 7.6 4.2 -6.5 - .3 - .8 16.1 -2.0 - .8 -1.4

NA 6 2 7 5 3 4 13 8 9 1 12 9 11

1020.0

177

Sources. – College Catalog Study Database; “Million Dollar List” (2001). Notes. – Column labels are as follows: 1 = $1 Million gifts in dollars; 2 = $1 million gifts as percent of total fields’ 3 = Number of $1 million gifts; 4 = Number of $1 million gifts as percent of total fields; 5 = Percent growth in CCS fields, 1980-2000; 6 = CCS field growth ranking. 1 Includes gifts for biomedical sciences, medicine, and nursing. 2 Includes gifts for all computer science, engineering, environmental science, and neuroscience. Fields data includes only “new-economy” engineering and science fields. 3 Includes gifts for chemistry, life sciences, mathematics, and unspecified sciences, including science centers. 4 Includes gifts for international relations, law, public policy, political economy, and public affairs/public service. 5 Includes gifts for communications, broadcast media, journalism, and speech. 6 Includes gifts for agriculture, architecture, landscape architecture, food science, furniture studies, and veterinary medicine. Fields include architecture, landscape architecture, agriculture, library science, and miscellaneous vocational fields. 7 Includes gifts for English, history, humanities, ethics, religion, archeology, and American studies. 8 Includes gifts for lesbian, gay, bisexual and transgender studies and for women’s studies. 9 Includes gifts for economics, psychology, and urban studies.

Table 7 Core Academic Fields, 1975-2000 N 2000

CCS Institutions 2000 (%)

Growth, 1975-2000 (%)

Natural Sciences Mathematics Computer Science Biology, Life Sciences Chemistry Physics

269 254 231 227 218

92 87 79 78 75

.8 226.0 8.5 - .9 - 3.1

Social Sciences Psychology Political Science Economics Sociology

237 229 227 213

81 78 78 73

2.2 9.6 - 4.6 2.9

Humanities English History Foreign Languages & Literatures Philosophy

237 233 225 224

81 80 77 77

4.9 3.6 - 1.7 - 1.8

Arts Art Music Drama

230 209 191

79 72 65

- 3.0 .5 29.1

Field

Source. – College Catalog Study Database.

Table 8 Occupational and Academic Growth, 1980-2000 Occupation Physical Scientists, n.e.c. Recreation Workers Computer Systems Analysts and Computer Scientists Management Analysts Occupational Therapists Managers of Medicine and Health Occupations Archivists and Curators Physical Therapists Art/Entertainment Performers Designers Managers of Properties and Real Estate Financial Managers Registered Nurses Speech Therapists Managers and Specialists in Marketing/ Advertising/Public Relations Human Resources Sociologists; Social Scientists, n.e.c. Accountants and Auditors Biological Scientists Operations and Systems Researchers and Analysts Psychologists Architects Urban and Regional Planners Geologists Lawyers and Judges Metallurgical and Materials Engineers Art Makers Atmospheric and Space Scientists Managers in Education Editors and Reporters Civil Engineers Mechanical Engineers Social Workers Pharmacists Engineers, n.e.c. Managers and Public Administrators

1

2

3

4

5

6

7

1681 876 620

1443 859 8567

38 45 1

0 - 12 131

19 64 302

83 23 59

97 33 51

411 332 290

3978 588 2221

3 8 13

100 70 46

18 17 19

65 79 50

73 78 54

277 276 220 212 205

275 1241 1473 3179 1426

51 5 24 4 21

- 50 78 17 86 22

1 16 191 26 11

51 74 39 31 24

71 68 53 42 33

173 172 165 145

5287 11795 1034 8459

6 19 18 11

75 30 31 57

89 121 59 94

47 34 94 42

55 53 97 62

145 143 120 120 107

6240 321 12612 806 815

38 33 16 33 12

0 2 35 2 52

8 825 109 428 179

39 72 57 88 51

47 84 70 94 57

104 99 97 95 85 80 80 68 65 63 62 61 60 59 58 52

1654 1628 199 789 9136 249 1568 67 5169 2139 2193 1879 4782 1970 2910 27148

33 26 42 41 9 23 40 6 10 44 27 20 15 49 17 47

2 14 - 5 - 3 67 19 - 2 75 59 - 9 12 26 37 - 29 34 - 26

263 66 36 140 40 32 248 14 70 41 74 86 107 32 157 104

88 73 86 87 94 63 35 49 80 64 67 57 64 86 64 32

99 85 90 91 98 65 44 82 75 73 81 68 74 95 77 48

Table 8 (Continued) Occupation

1

2

3

4

5

6

7

Dancers Clergy and Religious Workers Teachers Musician or Composer Electrical Engineer Economists and Market Researchers Industrial Engineers Aerospace Engineer Librarians Dietitians and Nutritionists Agricultural and Food Scientists Petroleum/Mining/Geological Engineers Chemical Engineers Chemists Physicists and Astronomers Foresters and Conservation Scientists Mathematical Sciences

48 47 44 43 39 34 32 28 28 26 25 22

40 3579 43472 692 2736 917 1156 811 1520 442 194 201

2 43 45 29 22 32 48 25 52 33 46 50

106 - 6 - 12 6 21 5 - 27 16 - 56 2 - 18 - 48

68 174 477 248 85 254 54 58 18 43 145 12

20 71 81 34 60 71 44 72 66 50 60 73

16 68 73 44 72 76 62 79 78 59 72 84

577 903 209 217 233

28 29 33 14 29

9 6 2 42 6

59 248 296 125 337

85 80 81 58 64

88 89 92 82 84

19 18 8 - 3 - 6

Sources. – College Catalog Study Database; U.S. Bureau of the Census (2003). Notes. – Column labels are as follows: 1 = Percent growth in occupation, 1980-2000; 2 = Number in occupation, 2000 (in 100’s); 3 = CCS field growth ranking; 4 = Percent growth in CCS field, 1980-2000; 5 = Number of CCS fields, 2000; 6 = Percent with 4 or more years of college, 1980; 7 = Percent with 4 or more years of college, 2000. All occupational data is based upon occupation holders with a bachelors degree or higher. Detailed information about census occupational categories and department field categories can be found in Appendix A.

Table 9 Academic Fields in Decline, 1975-2000 Field "Old Economy" Botany Home Economics Industrial Engineering Horticulture Veterinary Medicine Agricultural Engineering Animal Science Agricultural Economics

N 1975

28 82 75 20 37 29 27 22

Decline (%)

-

53.6 42.7 28.0 25.0 16.2 13.8 11.1 9.1

"Old Media" Library Science Speech Journalism

36 107 44

- 50.0 - 47.7 - 6.8

"Old Cultural/Indentity" Germanic Languages/Literature Romance Languages/Literature Slavic Languages/Literature Religious Studies

83 137 61 178

- 21.7 - 17.5 - 9.8 - 2.3

Source. – College Catalog Study Database.

Appendix A Correspondence of Census Occupational Titles and College Catalog Study Academic Fields Census 1990 Occupational Category

College Catalog Study Departmental Fields

Lawyers; Judges

Law/Legal Studies

Clergy and Religious Workers

Religion

Art/Entertainment Performers *: Actors/Directors/Producers; Art/Entertainment Performers and Related

Drama

Art makers*: Art Makers: Painters/Sculptors/Craft-Artists/PrintMakers; Photographers

Art/Studio Arts/Fine Arts/Visual Arts; Arts/Creative Arts

Pharmacists

Pharmacology

Musician or Composer

General Music; Music Composition; Singing; Instruments

Dancers

Dance

Registered Nurses

Nursing

Speech Therapists

Communication Disorders; Audiology/Speech Pathology/Speech Science

Physical Therapists

Physical Therapy

Occupational Therapists

Occupational Therapy

Managers and Public Administrators*: Chief Executives and Public Administrators; Managers and Administrators, n.e.c.

Business Administration/Office Administration/Commerce; Other Management; Public Administration and Policy

Management Analysts

Decision Science/Strategy; Business Policy

Mathematical Sciences*: Statisticians; Mathematicians and Mathematical Scientists

Mathematics; Statistics

Dietitians and Nutritionists

Nutrition/Food Science

Librarians

Library Science/Library and Information Science

Electrical Engineer

Electrical Engineering

Editors and Reporters

Journalism

Managers of Medicine and Health Occupations

Health Administration/Health Policy

Designers

Graphic Arts/Design

Teachers*: Kindergarten and Earlier School Teachers; Primary School Teachers; Secondary School Teachers; Special Education Teachers; Teachers, n.e.c.

Teaching Specialties; Primary/Secondary Teaching; Physical Education/ Athletics/Kinesiology; Education; Early Childhood Education; Special Education

Accountants and Auditors

Accounting

Architects

Architecture; Landscape Architecture; Environmental Design

Managers of Properties and Real Estate

Real Estate

Chemical Engineers

Chemical Engineering

Engineers, n.e.c.

Nuclear Engineering; Other Engineering Specialty; General Engineering; Environmental Engineering; Biological Engineering; Engineering Technology; Systems Engineering

Industrial Engineers

Industrial Engineering/Industrial Arts

Foresters and Conservation Scientists

Forestry; Fisheries/Aquatic Science; Natural resources/Park Management/Resource Economics; Environmental Studies/Environmental Science/Ecology; Range/Wildlife

Financial Managers

Finance

Mechanical Engineers

Mechanical Engineering

Urban and Regional Planners

Urban Studies/Community Studies; Planning

Petroleum/Mining/Geological Engineers

Metallurgy/Mining Engineering

Chemists

Molecular Biology; Chemistry

Social Workers

Community Services; Social Services/Human Services

Archivists and Curators

Museum Science

Aerospace Engineer

Aerospace Engineering/Aeronautics

Biological Scientists

Horticulture; Micro/Cell Biology; Developmental Biology; Entomology/Nematology; Zoology; Biological Science/Life Science; Cognitive Science/Neuroscience/Neurobiology; Botany; Biochemistry/Biotechnology; Other Biological Specialties; Biophysics; Genetics

Operations and Systems Researchers and Analysts

Business Analysis/Research/Quantitative Analysis/Operations Research; Management/Management Science/Management Information Systems; Organizational Behavior

Physicists and Astronomers

Physics; Astronomy

Managers in Education and Related Fields

School administration/Supervision; School Leadership; Education Measurement/Research/Policy

Economists and Market Researchers*: Economists/Market Researchers/ Survey Researchers

Consumer Science/Consumer Economics; Economics

Human Resources*: Human Resources and Labor Relations Managers; Personnel/Human Resources/ Training/Labor Relations Specialists

Human Resources/Industrial Relations/ Personnel

Computer Systems Analysts and Computer Scientists

Computer Engineering; Computer Science/Information Science

Atmospheric and Space Scientists

Meteorology/Atmospheric Science

Managers in Marketing and Public Relations*: Managers and Specialists in Marketing/Advertising/Public Relations

Advertising/Marketing

Civil Engineers

Civil Engineering

Psychologists

Psychology; Educational Psychology/School Psychology

Geologists

Geology/Earth Sciences/Geological Engineering

Agricultural and Food Scientists

Dairy/Poultry/Avian Science; Agricultural Engineering; Animal Science; Agriculture; Agronomy; Crop/Soil Science/Plant Science/Plant pathology

Recreation Workers

Recreation/Leisure Studies

Metallurgical and Materials Engineers

Material Science/Material Engineering

Physical Scientists, n.e.c.

Physical Science

Sociologists; Social Scientists, n.e.c.

Behavioral Science; Geography; Criminology; Anthropology; Political Science/Government; Archeology; Sociology; Social Science

Sources. – College Catalog Study Database; U.S. Bureau of the Census (2003) Notes. – Semi-colons demarcate unique fields as they appear in either census or CCS data. Forward-slashes indicate fields that were already grouped together in either census or CCS data. * Name of census occupation truncated in tables 3 and 8.

Appendix B Correspondence of National Science Foundation Funding Categories and College Catalog Study Academic Fields National Science Foundation Fields

College Catalog Study Departmental Fields

Biology and Environmental Biology

Molecular Biology; Biochemistry/Biotechnology; Genetics; Biological Science/Life Science; Nutrition/Food Science; Developmental Biology; Microbiology/Cell Biology; Entomology/ Nematology; Anatomy; Pharmacology; Pathology; Physiology; Biophysics; Botany; Zoology

Agricultural Biology

Range/Wildlife; Fisheries/Aquatic Science; Crop/Soil Science/Plant Science/Plant Pathology; Agriculture; Animal Science; Forestry; Horticulture; Agronomy

Psychology

Human development; Educational Psychology/School Psychology; Behavioral Science; Child Studies/Child Development; Psychology

Astronomy

Astronomy

Chemistry

Chemistry

Physics

Physics

Environmental Sciences/Atmospheric Sciences/Oceanography

Environmental Studies/Environmental Science/Ecology; Meteorology/Atmospheric Science; Marine Science

Geological Sciences

Geological Sciences

Mathematics

Mathematics

Computer Science

Computer Science/Information Science

Aeronautical and Astronautical Engineering

Aerospace Engineering/Aeronautics



Civil Engineering

Environmental Engineering; Architecture; Civil Engineering

Electrical Engineering

Computer Engineering; Electrical Engineering; Electronics



Metallurgy & Materials Engineering

Material Science/Material Engineering; Metallurgy/Mining Engineering

Economics

Decision Science/Strategy; Labor Studies; Economics; Agribusiness/Agricultural Economics

Political Science

International relations; Public Administration and Policy; Law/Legal Studies; Political Science/Government

Sociology

Organizational Behavior; Sociology

Sources. – National Science Foundation (2009); College Catalog Study Database Notes. – NSF funding for Medical sciences was omitted because CCS does not include data on medical schools. The following CCS fields fell into NSF, n.e.c., categories and were omitted because NSF (2009) defines this category as being used “when the multidisciplinary and interdisciplinary aspects make the classification under one primary field impossible”: Other Biology Specialties; Physical Science; Biological Engineering; Manufacturing; Biomedical Engineering/Biomedical Science; Engineering Technology; General Engineering; Systems Engineering; Agricultural Engineering; Other Engineering Specialty; Nuclear Engineering; Asian and Asian American Studies; Criminology; Ethnic Studies; History of Science/Philosophy of Science or Technology/Science and Society; Hispanic and Latin American Studies; American Indian Studies; Jewish/Near Eastern Studies; American Studies; European Studies; Archeology; African and African American Studies; Linguistics/Language; Geography; Social Science; Urban Studies/Community Studies; Housing Studies; Community Services; Technology; Audiology/Speech Pathology/Speech Science; Natural Sciences; General Science; Museum Science; Library Science/Library and Information Science; Safety Science.

Supplementary Table 1 Disaggregated College Catalog Study Academic Field Categories Accounting Advertising, Marketing Aerospace Engineering, Aeronautics African and African American Studies African Language and Literature Agricultural Engineering Agribusiness, Agricultural Economics Agriculture Agronomy American Indian Studies American Studies Anatomy Ancient, Classical Language and Literature Animal Science Anthropology Apparel, Textiles Archeology Architecture Art History Art, Studio Arts, Fine Arts, Visual Arts Arts and Sciences Arts, Creative Arts Asian and Asian American Studies Asian Language and Literature Astronomy Audiology, Speech Pathology, Speech Science Behavioral Science Biochemistry, Biotechnology Biological Engineering Biological Science, Life Science Biomedical Engineering, Biomedical Science Biophysics Botany Broadcast Communications, Media, Radio, Telecommunication Business Policy Business Administration, Office Administration, Commerce Business Analysis/Research, Business Operations Research

Business Law Chemical Engineering Chemistry Child Studies, Child Development Civil Engineering Classics Clinical Lab, Medical Technology Cognitive Science, Neuroscience, Neurobiology Communication Disorders Communication, Mass Communication Community Development Community Services Computer Engineering Computer Science, Information Science Construction Consumer Science, Consumer Economics Counseling, School Counseling Creative Writing, Writing Criminology Crop, Soil Science, Plant Science, Plant Pathology Cultural Studies, Multicultural Studies Curriculum, Instruction Dairy, Poultry, Avian Science Dance Decision Science, Strategy Developmental Biology Drama Early Childhood Education Economics Education Foundations Education Measurement, Research, Policy Education Psychology, School Psychology Education Technology, Educational Media Education Electrical Engineering Electronics Engineering Technology English Entomology, Nematology Environmental Design

Environmental Studies, Environmental Science, Ecology Environmental Engineering Ethnic Studies European Germanic Language and Literature European Romance Language and Literature European Studies Family Life, Home Economics Fashion Merchandising Film and TV Finance Fisheries, Aquatic Science Foreign language Forestry General Business General Engineering General Music General Professional Studies, Vocational Studies General Science General Studies Genetics Geography Geology, Earth Sciences, Geological Engineering Gerontology Graphic Arts, Design Health Administration, Health Policy Health Science Hispanic and Latin American Studies History of Science, Philosophy of Science or Technology, Science and Society History History, Study of Music, Music Industry Horticulture Hotel, Restaurant Management, Hospitality, Tourism Housing Studies Human Development Human Resources, Industrial Relations, Personnel Humanities, Letters Industrial Engineering, Industrial Arts Instruments Insurance Interdisciplinary Studies

Interior Design International Relations International Business Jewish Studies Journalism Labor Studies Landscape Architecture Law, Legal Studies Liberal Arts Library Science, Library and Information Science Linguistics, Language Literature Management, Management Science, Management Information Systems Manufacturing Marine Science Material Science, Material Engineering Math Mechanical Engineering Mechanics Metallurgy, Mining Engineering Meteorology, Atmospheric Science Micro Biology, Cell Biology Military Miscellaneous Molecular Biology Museum Science Music Composition Natural Resources, Park Management, Resource Economics Natural Sciences Near Eastern, Middle Eastern Language and Literature Nuclear Engineering Nursing Nutrition, Food Science Occupational Therapy Organizational Behavior Other Biological Specialties Other Engineering Specialty Other Health Specialties Other Management Specialties Other Professional, Vocational

Pathology Pharmacology Philosophy Physical Education, Athletics, Kinesiology Physical Science Physical Therapy Physics Physiology Planning Political Science, Government Post-Secondary Education Primary, Secondary Teaching Psychology Public Administration and Policy Public Health Radiology Range, Wildlife Real Estate Recreation, Leisure Studies Rehabilitation Religion Rhetoric Russian, Slavic Language and Literature Safety Science School Administration, Supervision School Leadership School Services, Student Personnel, Instructional Services Singing Social Science Social Services, Human Services Sociology Special Education Speech, Speech Communication Statistics Systems Engineering Teaching Specialties Technology Transportation Urban Studies, Community studies Veterinary Medicine

Women’s Studies, Gender Studies Zoology

Figure 1 Change in Field Categories from 1975 to 2000: Categories that had at least five times the growth rate of all fields combined Figure 2 Change in Field Categories 1975 to 2000: Categories that had less than double the growth rate of all fields combined

Figure 3 National Endowments Expenditures and Arts and Humanities Field Trends, 1975-2000

900 800 105%

Number of Fields

700

Advanced Technology

600

Advanced Management/Business Services

500

Social Control/Regulatory

400

New Cultural/Identity

300

94% 75%

200

89% 113%

100

Human Services

Growth rate of all fields is 15%

0 1975

1980

1985

1990

1995

2000

Year

Figure 1

900 21%

800

Number of Fields

700 600

Arts

500

6% 23%

400

1% 30%

300

Education Other Business Other Technology Communication

200 Growth rate of all fields is 15%

100 0 1975

1980

1985

1990

1995

2000

Year

Figure 2

1400

300

1200

250

1000

200

800

150

600

100

400

50

200

0

Number of Fields

Funding (in millions)

350

NEH Funding NEA Funding Arts Fields Humanities Fields

0 1975

1980

1985

1990

1995

2000

Year

Figure 3