Kanter’s Theory of Proportions: Organizational Demography and PhD Completion in Science and Engineering Departments
Increasing the size and diversity of the scientific and technological workforce is a national priority. Investments in policy and programmatic efforts toward increasing the representation of women in science and engineering fields have resulted in significant advances; however, a gender gap remains among PhDs and faculty in these fields. This study tests whether Kanter’s (Men and women of the corporation, Basic Books, New York, 1977) theory of proportions, which suggests that numerical representation of groups influence group dynamics and cultural context, applies to the proportion of female faculty and the probability that female doctoral students will complete their degrees in science and engineering. Using data from two research-intensive academic institutions, results show that female doctoral students are more likely to complete the degree in departments with higher proportions of female faculty. Further, female PhD students working with female faculty dissertation advisors are also more likely to complete the degree than female PhD students working with male faculty dissertation advisors. Departmental faculty sex ratios and whether their faculty advisor is male or female, however, have no effect on the completion probabilities of male PhD students. Consistent with Kanter’s theory, research findings illustrate the importance of organizational demography on the academic outcomes of PhD students, and provide support for initiatives and programs aimed at increasing the representation of female faculty in science and engineering.
KeywordsPhD completion Organizational demography Doctoral students Faculty Gender Science and engineering
This material is based upon work supported by the Cornell University Center for the Study of Inequality (CSI). Initial support of this research also came from the Andrew W. Mellon Foundation through a grant to the Cornell Higher Education Research Institute. Any opinions, findings, and conclusions or recommendations are those of the author and do not necessarily reflect the views of the Andrew W. Mellon Foundation or the Cornell University Center for the Study of Inequality. The author deeply appreciate the funding support from Cornell CSI and the Andrew W. Mellon Foundation. The author thanks Ronald G. Ehrenberg, Pamela S. Tolbert, Stephen L. Morgan, Russell P. Main, and the anonymous reviewers for their valuable feedback.
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