Research Productivity in Academia: A Comparative Study of the Sciences, Social Sciences and Humanities

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<ul><li><p>Research Productivity in Academia: A Comparative Study of the Sciences, Social Sciences andHumanitiesAuthor(s): Richard A. Wanner, Lionel S. Lewis and David I. GregorioSource: Sociology of Education, Vol. 54, No. 4 (Oct., 1981), pp. 238-253Published by: American Sociological AssociationStable URL: .Accessed: 02/08/2013 17:09</p><p>Your use of the JSTOR archive indicates your acceptance of the Terms &amp; Conditions of Use, available at .</p><p> .</p><p>JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact</p><p> .</p><p>American Sociological Association is collaborating with JSTOR to digitize, preserve and extend access toSociology of Education.</p><p> </p><p>This content downloaded from on Fri, 2 Aug 2013 17:09:39 PMAll use subject to JSTOR Terms and Conditions</p></li><li><p>RESEARCH PRODUCTIVITY IN ACADEMIA: A COMPARATIVE STUDY OF THE SCIENCES, SOCIAL SCIENCES AND HUMANITIES* </p><p>RICHARD A. WANNER LIONEL S. LEWIS The University of Calgary DAVID I. GREGORIO </p><p>State University of New York at Buffalo </p><p>Sociology of Education 1981, Vol. 54 (October):238-253 </p><p>Though a significant number of studies of scholarly productivity have accumulated in the past decade, the majority have focused on limited samples of specialists in one or only a few scientific disciplines, making it difficult to generalize findings across dissimilar academic disciplines. This paper tests a model incorporating both academic and nonacademic factors as determinants of productivity with samples of physical and biological scientists, social scientists, and humanists taken from the 1972-73 American Council on Education survey of J'aculty at U.S. institutions of higher learning. We find considerable variation in the process determining productivity both across the broad disciplinary categories as well as within categories when article and book productivity are compared. We also examine the relative influence of the disciplinary context and attributes of scholars on productivity. Our evidence suggests that the decisive edge that physical and biological scientists enjoy over social scientists and humanists in article productivity is largely the result of the nature of work or a favorable disciplinary milieu, while the lower rate of productivity among humanists is more heavily determined by their attributes. </p><p>INTRODUCTION </p><p>Over the last decade a significant number of studies of scholarly productivity-the publication of articles and books-have accumulated. Most of this work is ably built upon a research tradition begun in the 1940s. The extent of its development-from Meltzer's (1949) and Manis' (1951) findings of relationships among measures of professional perfor- mance and publication to Long's (1978) use of a longitudinal design and regression analysis for examining the reciprocal ef- fects of departmental location and scien- tific productivity-is most evident. </p><p>As analysts have become increasingly specialized in the sociology of science, however, research on productivity has been gradually restricted to samples of scientists. Such studies typically focus on limited numbers of specialists in one or a few scientific disciplines. The research productivity of social scientists, for example, has been less frequently consid- </p><p>ered, while that of humanists is seldom examined,- and then, only as part of a larger sample of university faculty. </p><p>Over 30 years ago, Meltzer observed that for research on scholarly productivity there is "wisdom in treating each disci- pline . . . separately" (1949:29). While detailed comparisons such as Meltzer might envision may be unnecessary, it would certainly be useful to know if mod- els applicable to one context could be ex- tended to other areas of academia. The body of empirical work from the sociology of science, however, offers few clues as to how closely its models predicting research productivity of scientists would approx- imate those for social scientists and humanists. This paper was prompted by our wish to determine the extent to which notions of scientific productivity are rele- vant to the understanding of scholarly productivity in general. </p><p>A GENERAL MODEL OF PRODUCTIVITY: A SUMMARY OF PREVIOUS RESEARCH </p><p>The great diversity that exists among scholars with respect to research produc- tivity has been frequently documented (Allison and Stewart, 1974; Faia, 1975; Lewis, 1975; Reskin, 1977), and explana- </p><p>* Revised version of a paper presented at the an- nual meeting of the American Sociological Associa- tion, New York, NY, August, 1980. Address corre- spondence to Dr. Richard A. Wanner, Department of Sociology, The University of Calgary, Calgary, Al- berta, T2N 1N4, Canada. </p><p>238 </p><p>This content downloaded from on Fri, 2 Aug 2013 17:09:39 PMAll use subject to JSTOR Terms and Conditions</p></li><li><p>RESEARCH PRODUCTIVITY IN ACADEMIA 239 </p><p>tions for such differences continue to interest sociologists. Suggested answers to the question emphasize both personal attributes of the scholar (e.g., natural ability, commitment to research) and the dynamics of professional life (e.g., the superiority of some graduate training pro- grams, the influence of sponsorship, the stratification of the academic profession). Despite the acquisition of abundant data and sophisticated research designs, there is really little consensus regarding the de- terminants of scholarly productivity. As one instance, writers disagree about the impact of graduate training on the later production of scientific work. The direct relationship which Crane posits between the quality of graduate training and later productivity (1965:703-4) is supported elsewhere in the literature (Lightfield, 1971), while on the other hand, Clemente and Sturgis observed only a weak re- lationship between these measures (1974:295), and Gaston found almost none (1970:721). Similar incongruities pertain- ing to the effects of gender, time to ac- quire a Ph.D., experience and the quality of institutional affiliation are evident in the literature. For example, Cole and Cole used cross-sectional data on 120 American physicists to demonstrate a statistically significant correlation (r=.24) between the quality of academic positions and produc- tivity (1967:385). Gaston derived an iden- tical correlation between these measures for his sample of British physicists, but concluded that "the prestige of a scien- tist's current affiliation has only a negligible-if any-effect on his produc- tivity" (1970:721). In short, the utilization of diverse theoretical and empirical mod- els has precluded the development of a single perspective from which academic productivity can be understood. We now review a number of studies falling into two research traditions which offer quite dif- ferent explanations of scholarly produc- tivity. </p><p>Using a sample of 266 social scientists, Meltzer (1949) observed that signs of early productivity (age at Ph.D. and first publi- cation), as well as rapid completion of graduate training, were directly associated with career productivity. The proposition that early performance is a strong predic- </p><p>tor of productivity in later years is gener- ally supported by Cole and Cole (1967:338), Clemente (1973:415), Clemente and Sturgis (1974:292), Long (1978:898) and Long, Scott, Allison and McGinnis (1979:826).' </p><p>These studies (with the exception of Long et al., 1979) implicitly support the "sacred spark" thesis of productivity (Cole and Cole, 1973:114) which holds that dif- ferences in ability, motivation, stamina and attitude predispose certain individuals toward research endeavors which, in turn, contribute to their productivity. Accord- ingly, general commitment to research in the form of psychological dispositions and/or exaggerated work routines is a key explanatory variable in many such ac- counts (Aran and Ben-David, 1968; Simon, 1974; Simon, 1974; Gaston, 1970: 721; Hargens, 1978:103).2 </p><p>Extending the sacred spark perspective further, Crane presents data which sug- gest that the relationship between institu- tional affiliation and productivity is medi- ated by the quality of graduate training (1965: 704). Crane reasons that the most capable individuals come to attend the best graduate programs and through a process of increasing selectivity, gain sponsorship from top scientists, ap- pointments to major universities, and eventually "become the next generation's most productive scientists" (1965:705). </p><p>While theories of natural ability such as Crane's presume a clear and direct re- </p><p>I On the other hand, Reskin studied 238 chemists and observed that "early productivity did not signifi- cantly affect decade output," nor did the time it took to complete a Ph.D. (1977:500). </p><p>2 Since most studies of productivity have focused on the scientific community, its overall homogeneity with respect to ascriptive characteristics that are often sociologically relevant (e.g., gender and race) has unfortunately limited inquiry into the impact of these variables on productivity, though some studies have examined the question. Babchuk and Bates concluded that "women were far less prolific than men," a condition attributed to the formers' "appar- ent lesser orientation to the discipline" (1962:347). Among studies not excluding women from the analysis, however, the majority found gender to be unrelated to productivity (Simon, Clark and Galway, 1967; Clemente, 1973; Clemente and Sturgis, 1974; Reskin, 1978), although Hargens et al. found that "male research chemists published more than fe- males" (1978:158). </p><p>This content downloaded from on Fri, 2 Aug 2013 17:09:39 PMAll use subject to JSTOR Terms and Conditions</p></li><li><p>240 WANNER, LEWIS AND GREGORIO </p><p>lationship between individual charac- teristics and performance differences, ad- vocates of what has come to be known as the "accumulative advantage" framework recognize the reciprocal effects of mate- rial and symbolic factors upon produc- tivity. Here it is argued that because scholarly productivity results in dif- ferential recognition, it, in turn, functions to motivate as well as to furnish various resources that will facilitate later re- search. Manis ,first observed that the quality of an individual's institutional af- filiation was directly related to the quality of scholarly productivity (1951:270), a finding indicative of the contextual effect of institutional setting upon performance. Babchuk and Bates likewise conclude that "generally, the more prolific sociologists were affiliated with major universities" (1962:347). </p><p>Reskin's use of a longitudinal design, which represents a substantial advance- ment over previous methods, suggests that "beginning one's career in a university was a far more important determinant of decade productivity than one's graduate school credentials" (1977:499), particu- larly for women (1978:1239). Substan- tially identical conclusions were drawn by Long (1978), who emphasized that dis- parities in productivity among biochemists are in fact accentuated when such effects as the quality of an individu- al's Ph.D., sponsorship and individual prestige are controlled. </p><p>The body of research, then, may not provide a consistent picture, but it does offer some theoretical notions as well as an empirical tradition which suggests the contours of a general model of produc- tivity that can be utilized to make the comparisons across disciplinary categories that are central to our research. We have neither the intent nor capacity to assess the relative strengths of the pre- vailing analytic schemes or previous studies. Our data, cross-sectional in na- ture and further constrained by their use in secondary analysis, are unsuited for such questions. We do propose, how- ever, to offer a composite model of pro- ductivity that incorporates several promi- nent themes and important variables con- </p><p>tained in the major studies of academic productivity, regardless of what perspec- tive they appear to support. </p><p>The studies that we have reviewed and from which our model is developed point to several questions that must be ad- dressed if we are to further our under- standing of scholarly productivity. First of all, they make it clear that we must ex- plicitly separate explanatory factors into two major domains: background charac- teristics, such as sex or socioeconomic origins, and features of the academic career, such as rank or quality of institu- tion. Much research by sociologists has either ignored background factors or con- centrated on just one or two of them. If in fact these characteristics have a major im- pact on scholarly productivity, a serious specification error affecting the relation- ship between academic factors and pro- ductivity is committed by ignoring them. For purposes of this analysis we presume that the background characteristics are antecedent to the academic factors, mak- ing it possible to determine the extent to which they have both direct and indirect effects on scholarly productivity. Beyond this, our data do not permit further order- ing of causal factors and we limit our analysis and interpretations accordingly. Second, it is important to separate the ef- fects of disciplinary context from those of the attributes of scholars within disci- plines. This we attempt to achieve by means of a standardization procedure elaborated later. We note prior to the analysis that the assumption of homogeneity of process implicit in much of the literature requires further inquiry. At the heart of our study is the assumption that the process whereby backgrounds, motivations, and resources are transformed into scholarly productivity is likely to vary systematically across the natural sciences, social sciences, and humanities. Our understanding of the re- search productivity process, upon which the following analysis is based, may raise questions for some. Other models for studying this problem might be useful, but given our interests and the data available, we have decided that this approach is most appropriate. </p><p>This content downloaded from on Fri, 2 Aug 2013 17:09:39 PMAll use subject to JSTOR Terms and Conditions</p></li><li><p>RESEARCH PRODUCTIVITY IN ACADEMIA 241 </p><p>DATA AND MEASURES </p><p>The data to be analyzed were gathered during the 1972-73 academic year by the American Council on Education (ACE). A four-page questionnaire was mailed to a stratified sample of 108,722 faculty teaching in 301 American institutions of higher learning, yielding 53,034 usable re- sponses.3 The sample included faculty from 78 universities, 181 four-year col- leges, and 42 junior or community col- leges. Our analysis is restricted to 17,399 individuals (33 percent of total sample) holding conventional appoin...</p></li></ul>


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