THE UNDERREPRESENTATION OF WOMEN IN SCIENCE: INTERNATIONAL AND CROSS-DISCIPLINARY EVIDENCE AND DEBATE

EDITED BY: Stephen J. Ceci, Wendy M. Williams and Shulamit Kahn PUBLISHED IN: Frontiers in Psychology

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ISSN 1664-8714 ISBN 978-2-88945-434-1 DOI 10.3389/978-2-88945-434-1

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# **THE UNDERREPRESENTATION OF WOMEN IN SCIENCE: INTERNATIONAL AND CROSS-DISCIPLINARY EVIDENCE AND DEBATE**

Topic Editors:

**Stephen J. Ceci,** Cornell Univesity, United States **Wendy M. Williams,** Cornell University, United States **Shulamit Kahn,** Boston University, United States

"Woman teaching geometry" attributed to Meliacin Master (fl. 13th century–1312). This file has been provided by the British Library from its digital collections.

There is no shortage of articles and books exploring women's underrepresentation in science. Everyone is interested--academics, politicians, parents, high school girls (and boys), women in search of college majors, administrators working to accommodate women's educational interests; the list goes on. But one thing often missing is an evidence-based examination of the problem, uninfluenced by personal opinions, accounts of "lived experiences," anecdotes, and the always-encroaching inputs of popular culture. This is why this special issue of Frontiers in Psychology can make a difference. In it, a diverse group of authors and researchers with even more diverse viewpoints find themselves united by their empirical, objective approaches to understanding women's underrepresentation in science today.

The questions considered within this special issue span academic disciplines, methods, levels of analysis, and nature of analysis; what these article share is their scholarly, evidence-based approach to understanding a key issue of our time.

**Citation:** Ceci, S. J., Williams, W. M., Kahn, S., eds. (2018). The Underrepresentation of Women in Science: International and Cross-Disciplinary Evidence and Debate. Lausanne: Frontiers Media. doi: 10.3389/978-2-88945-434-1

# Table of Contents

*06 Editorial: Underrepresentation of Women in Science: International and Cross-Disciplinary Evidence and Debate* Wendy M. Williams

# **Sexism in Professorial Hiring**

# **Exploring the Gender Gap Via National Datasets**

*29 Are Recent Cohorts of Women With Engineering Bachelors Less Likely to Stay in Engineering?*

Shulamit Kahn and Donna K. Ginther

*44 All STEM Fields are Not Created Equal: People and Things Interests Explain Gender Disparities Across STEM Fields*

Rong Su and James Rounds

*64 Math Achievement is Important, But Task Values are Critical, Too: Examining the Intellectual and Motivational Factors Leading to Gender Disparities in STEM Careers*

Ming-Te Wang, Jessica Degol and Feifei Ye

# **Stereotypes About Brilliance and Male-Oriented Fields**

*73 Women are Underrepresented in Fields Where Success is Believed to Require Brilliance*

Meredith Meyer, Andrei Cimpian and Sarah-Jane Leslie

David I. Miller and Jonathan Wai

# **Importance of Competitive Schools and Perceived Math Ability**

*122 The Role of School Performance in Narrowing Gender Gaps in the Formation of STEM Aspirations: a Cross-National Study*

Allison Mann, Joscha Legewie and Thomas A. DiPrete

*133 Perceived Mathematical Ability Under Challenge: A Longitudinal Perspective on Sex Segregation Among STEM Degree Fields* Samantha Nix, Lara Perez-Felkner and Kirby Thomas

# **Wisdom from the Trenches of Academia**

*152 Does Gender of Administrator Matter? National Study Explores U.S. University Administrators' Attitudes About Retaining Women Professors in STEM*

Wendy M. Williams, Agrima Mahajan, Felix Thoemmes, Susan M. Barnett, Francoise Vermeylen, Brian M. Cash and Stephen J. Ceci

# Editorial: Underrepresentation of Women in Science: International and Cross-Disciplinary Evidence and Debate

Wendy M. Williams\*

*Department of Human Development, Cornell University, Ithaca, NY, United States*

Keywords: women in science, underrepresentation of women, women in STEM, STEM careers, work-life balance

**Editorial on the Research Topic**

### **Underrepresentation of Women in Science: International and Cross-Disciplinary Evidence and Debate**

There is no shortage of articles and books exploring women's underrepresentation in science. Everyone is interested—academics, politicians, parents, high school girls (and boys), women in search of college majors, administrators working to accommodate women's educational interests; the list goes on. But one thing often missing is an evidence-based examination of the problem, uninfluenced by personal opinions, accounts of "lived experiences," anecdotes, and the alwaysencroaching inputs of popular culture. This is why this special issue of Frontiers in Psychology can make a difference. In it, a diverse group of authors and researchers with even more diverse viewpoints find themselves united by their empirical, objective approaches to understanding women's underrepresentation in science today.

Edited and reviewed by: *Jessica S. Horst, University of Sussex, United Kingdom*

> \*Correspondence: *Wendy M. Williams<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology*

Received: *17 October 2017* Accepted: *22 December 2017* Published: *22 January 2018*

#### Citation:

*Williams WM (2018) Editorial: Underrepresentation of Women in Science: International and Cross-Disciplinary Evidence and Debate. Front. Psychol. 8:2352. doi: 10.3389/fpsyg.2017.02352* OVERVIEW OF ARTICLES IN SPECIAL ISSUE

The questions considered within this special issue span academic disciplines, methods, levels of analysis, and nature of analysis; what these article share is their scholarly, evidence-based approach to understanding a key issue of our time.

# Sexism in Professorial Hiring

Ceci and Williams re-visited the experimental paradigm from their 2015 Proceedings of the National Academy of Sciences article in which (in four of their five experiments) faculty were asked to rate three short-listed finalists for a tenure-track position. The 2015 study revealed a 2:1 preference for women when finalists were equivalently excellent. The new study contrasted a male finalist who was slightly superior to the female finalist. Women's advantage vanished when the male applicant was depicted as slightly stronger, suggesting that fears that affirmative action goals will undermine hiring of most-qualified applicants are unfounded.

Allen-Hermanson examined an overlooked aspect of the women's underrepresentation debate: Are philosophers prejudiced against hiring women applicants despite professing conscious, explicit egalitarian beliefs? Unlike other humanities departments, philosophy departments have far fewer women professors than might be expected. He reviewed several recent data sets demonstrating that female applicants are favored when it comes to tenure-track hiring in philosophy departments.

# Exploring the Gender Gap via National Datasets

Using 1993–2010 nationally representative data, Kahn and Ginther examined whether the gender gap in engineering has narrowed recently. They discovered that the majority of the gender retention gap was due to women leaving the labor force coincident with child-bearing. There was no gender retention difference by 7–8 years post-bachelors for those fulltime employed; single childless women were more likely than men to remain in engineering than were single childless men, and women who left engineering entirely were just as likely as men who left to remain in math-intensive fields. Their findings caution against past assertions that women do not persist in STEM fields as long as men.

In their latest meta-analysis, Su and Rounds examined data from 52 samples entailing over 430,000 respondents between 1964 and 2007. Gender differences in interests favoring males were largest in engineering-related fields, and favored women in allied health fields and social sciences. This adds to the large body of empirical findings that have revealed similar sex differences along the people-thing dimension.

Miller and Wai reported the results of their analysis of longitudinal data to examine the baccalaureate-to-PhD transition. In contrast to the traditional leaky pipeline metaphor, they found that over time, women have segued from the baccalaureate to PhD programs in increasing numbers. Their work suggests that researchers and policy makers need to look elsewhere for causes of women's underrepresentation.

Wang et al. studied factors predicting gender differences in selection of STEM occupations, and whether math task values and altruism mediate the pathway through which gender affects STEM career choice through math achievement. Based on longitudinal analyses, they found that the association between gender and working in a STEM career by one's early- to midthirties was mediated by math achievement scores in twelfth grade; females did more poorly on standardized math tests than did males.

# Stereotypes about "Brilliance" and "Male-Oriented" Fields

Meyer et al. examined field-specific beliefs regarding the importance of brilliance. They provide support for the hypothesis that women are most likely to be underrepresented in fields that members believe require raw intellectual talent, which women are stereotyped to possess less of than do men. The beliefs of participants with exposure to a field predicted the magnitude of the field's gender gap, independent of their beliefs about the level of mathematical ability required. Their findings are consistent with female high school students taking fewer AP courses in all areas of science except biology (Ceci et al., 2014).

Cheryan et al. presented data and argument showing that modern American culture stereotypes as male-oriented those fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. Their work continues their recent insights and is consistent with the findings of some of the other contributors, particularly Meyer et al.

Smyth and Nosek explored whether variation in female representation across scientific disciplines is associated with differences in the strength of gender-science stereotypes, explicit and implicit, held by men and women in these fields. For explicit stereotypes that associate science with "male," the strength of stereotyping varied across scientific disciplines as a function of gender ratios in the disciplines; however, implicit stereotypes did not vary as a function of such ratios. Giving currency to their findings is recent evidence that children continue to associate science with being male (Miller et al., in press).

# Importance of Competitive Schools and Perceived Math Ability

Mann et al. analyzed findings from PISA data from 55 countries. They placed schools along a continuum from most to least competitive, based on average math and science performance. Schools that are most competitive are often associated with stronger math-science environments. The authors found that the aspirations gender gap narrowed for high-performing students in stronger performance environments.

Nix et al. reported an analysis of longitudinal, nationally representative high school data. They found that perceived mathematics ability when under challenge predicted important outcomes such as taking advanced science courses in high school, and that high school men scored higher than women did in their perceived ability under mathematics challenge. Their findings are consistent with female high school students taking fewer AP courses in all areas of science except biology (Ceci et al., 2014).

# Wisdom from the Trenches of Academia

Finally, Williams et al. collected and analyzed an original national empirical dataset in which provosts, deans, associate deans, and department chairs of STEM fields at 96 U.S. research-intensive universities rated the quality and feasibility of strategies for retaining women in STEM fields. For example, administrators agreed that gender quotas were a weak idea, and that campus childcare centers were an excellent idea. Women administrators were more supportive than were men of shared tenure lines, and saw it as more feasible for men to stop the tenure clock for 1 year for childrearing.

In sum, readers will find multiple perspectives in this special issue, and the editors hope it will stimulate new directions of thinking and scholarship on women and science.

# AUTHOR CONTRIBUTIONS

The author confirms being the sole contributor of this work and approved it for publication.

# REFERENCES

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Williams. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Women have substantial advantage in STEM faculty hiring, except when competing against more-accomplished men

#### Stephen J. Ceci\* and Wendy M. Williams

*Department of Human Development, Cornell University, Ithaca, NY, USA*

Audits of tenure-track hiring reveal faculty prefer to hire female applicants over males. However, audit data do not control for applicant quality, allowing some to argue women are hired at higher rates because they are more qualified. To test this, Williams and Ceci (2015) conducted an experiment demonstrating a preference for hiring women over identically-qualified men. While their findings are consistent with audits, they raise the specter that faculty may prefer women over even more-qualified men, a claim made recently. We evaluated this claim in the present study: 158 faculty ranked two men and one woman for a tenure-track-assistant professorship, and 94 faculty ranked two women and one man. In the former condition, the female applicant was slightly weaker than her two male competitors, although still strong; in the other condition the male applicant was slightly weaker than his two female competitors, although still strong. Faculty of both genders and in all fields preferred the more-qualified men over the slightly-less-qualified women, and they also preferred the stronger women over the slightly-less-qualified man. This suggests that preference for women among identically-qualified applicants found in experimental studies and in audits does not extend to women whose credentials are even slightly weaker than male counterparts. Thus these data give no support to the twin claims that weaker males are chosen over stronger females or weaker females are hired over stronger males.

#### Keywords: affirmative action, women in science, bias, sexism, academic hiring

# Introduction

Much has been written about the campaign to diversify faculty at American colleges and universities, an effort that started in earnest during the 1980s and continues unabated. To this end, hundreds of analyses of faculty hiring for tenure-track positions have been reported, and the temporal changes in the fraction of female and minority applicants in the American professoriate have been charted (e.g., Smith et al., 2004; Kang and Banaji, 2006; Turner et al., 2008; Niederle et al., 2013). Despite substantial gains in diversity of faculty, the dominant view appears to be that racial and gender preferences continue to be needed to counter not just historical prejudice but also current biases held by faculty—most of which may be implicit, and which result in barriers against hiring women and minorities. It is alleged that such biases create, in the words of Kang and Banaji, "threats to fair treatment—threats that lie in every mind" and that affirmative-action hiring

#### Edited by:

*Steven E. Mock, University of Waterloo, Canada*

# Reviewed by:

*David I. Miller, Northwestern University, USA Amy Yeung, University of Waterloo, Canada*

#### \*Correspondence:

*Stephen J. Ceci, Department of Human Development, Cornell University, G80 MVR Hall, Ithaca, NY 14853, USA<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology*

Received: *14 April 2015* Accepted: *22 September 2015* Published: *20 October 2015*

#### Citation:

*Ceci SJ and Williams WM (2015) Women have substantial advantage in STEM faculty hiring, except when competing against more-accomplished men. Front. Psychol. 6:1532. doi: 10.3389/fpsyg.2015.01532* programs should be continued until data are available to indicate such threats are over: "such data should be a crucial guide to ending affirmative action" (Kang and Banaji, 2006, p. 1063). With some notable exceptions demonstrating female-friendly hiring preferences by faculty (Williams and Ceci, 2015), there continues to be evidence of implicit and occasionally explicit biases directed at women and ethnic minorities. Although few of these demonstrations of bias concern hiring of academic science faculty, some of them are indirectly relevant. The present experiment was undertaken to determine whether gender differences trump applicant quality in tenure-track hiring decisions.

#### Stereotypes, Hiring Bias, and Gender Congruity

A growing literature reveals people are apt to explicitly associate science with men, including not only students but also scientists (Smyth and Nosek, 2015), and that such stereotypes are pervasive, as shown recently by Miller et al. (2015). In their transnational analysis, Miller et al. showed higher female enrollment in post-secondary course-taking in nations with weaker implicit and explicit gendered stereotypes regarding science. Such stereotypes can lead to biased evaluations against women in so-called gender-incongruous contexts, such as in STEM fields in which men have historically been dominant (engineering, physics, economics, computer science, geosciences, and mathematics). This form of bias is particularly likely to emerge when information about applicants' competence is unavailable or when the evaluators are not experienced professionals. For example, Ernesto Reuben and his colleagues (Reuben et al., 2014) asked nearly 150 men and women (mostly undergraduates) to add a string of four 2-digit numbers. They were given 4 min to do as many additions as possible. The authors then assigned the role of hiring manager to nearly 200 male and female students, who were asked to decide whom among these 150 students to hire. Afterward these managers were given an implicit bias test. The authors found that men were hired at twice the rate of women; most of the students playing the role of hiring manager believed men were better at math and science. Even when informed of superior arithmetic scores by women, some hypothetical managers continued to prefer to hire men. In their "cheap talk" condition (which had the largest gender bias), applicants selected the lower performing male over the higher performing female in 29% of the cases compared to selecting the lower performing female over the higher performing female in only 2% of the cases. Hence, in that study, the pro-male bias trumped even applicant quality. Taken together, these transnational and experimental studies indicate that implicit biases and sometimes explicit ones can lead to fewer women preparing for a career in STEM and ultimately being hired.

Studies of gender biases suggest that stereotypes are not always activated but rather are invoked when information about applicants is limited or ambiguous or when evaluators lack motivation to be careful. In such situations stereotypes can reduce cognitive load during decision-making. However, relying upon stereotypes may be unnecessary when information about applicants indicates unambiguously high competence, as in the case with tenure-track hiring. In their recent metaanalysis, Amanda Koch and her associates found that gender-role congruity bias was largest when so-called "individuating information" that was informative of applicants' competence was ambiguous or not clearly diagnostic of success. They reported that sex bias shrinks in male-dominated fields when diagnostic information about applicants' competence is available (see Koch et al., 2015, pp. 130–131). The authors reported near-zero bias when female applicants were evaluated by experienced professionals in male-dominated fields if information regarding their competence was available (d = 0.02). This finding is relevant to the Reuben et al. hiring manager study because the evaluation was not done by experienced professionals, and in one version student managers were significantly less biased when they were supplied with the women's actual arithmetic scores, albeit some smaller number of student managers still exhibited a male hiring bias even in this condition. Typically, however, the studies in the metaanalysis examined applicants with equally strong records, thus telling us little about whether bias occurs for female applicants possessing inferior credentials, as some have alleged (e.g., Niederle et al., 2013). We directly address this lacuna in the current experiment.

Relatedly, Moss-Racusin et al. (2012) found that both male and female faculty preferred to hire, remunerate, and mentor a male applicant for a lab manager post than an identicallyqualified female applicant. However, the lab manager post was baccalaureate-level and the lab manager applicant was depicted as ambiguously-competent rather than as unambiguously stellar. Thus, the Reuben et al. and Moss-Racusin et al. experiments leave unanswered the question of whether such bias would be found in hiring applicants for professorships under conditions in which experienced faculty have motivation to be careful and possess diagnostic information about applicants' competence—in other words, the real-world conditions under which faculty are usually hired.

### Background for the Present Study

In the present study we report findings from an ongoing program of experimental research aimed at examining biases in the hiring of women scientists in male-dominated fields in the academy. The major focal question in the current study is: How much do gender-related biases trump preferences for the candidate with the highest quantitative competence index, based on publications, letters, interview, and job talk? Recent experimental evidence indicates that when evaluators are themselves experienced professionals, women applicants for professorships are preferred over equally-competent men when both are depicted realistically, as identically and unambiguously stellar (Williams and Ceci, 2015). Here we ask whether this preference for female applicants will extend to situations in which women are quantitatively slightly weaker than men.

Many blue-ribbon panels and national organizations argue for the continued use of preferential hiring programs because biased hiring is viewed as a cause of women's underrepresentation in academic science, by "inadvertently foreclosing consideration of the best-qualified persons by untested presuppositions which operate to exclude women and minorities" (AAUP, 2014). Notwithstanding the recent pro-female hiring data of Williams and Ceci, there are recent empirical data implying that hiring is sexist and that it possibly forecloses the prospects of the best-qualified female applicants. However, none of these data concern the hiring of academic science faculty by professionals who possess diagnostic information, but they nevertheless are relevant. Below we describe a survey study and an experiment that are relevant to gender bias in academic hiring, even though neither actually involves hiring of professors in male-dominated fields.

Sheltzer and Smith (2014) surveyed biology department web pages and departmental directories to ascertain the numbers of graduate students and postdoctoral researchers employed by faculty members. They found that elite male faculty (winners of lifetime awards, members of the National Academy of Sciences, recipients of funding by the Howard Hughes Medical Institute) employed fewer female graduate students and postdoctoral researchers than did elite female faculty, who did not exhibit a gender asymmetry. New assistant professors in biology were disproportionately comprised of individuals who came from these elite laboratories, which had an overabundance of male grad students and postdocs, thus reflecting a seeming causal loop. However, two features of this study merit mention: first, biology is a field in which women are well represented among both PhD recipients and among the professoriate, so it is unlikely to be the ideal field in which to detect gender bias. Second, because this was not an experiment, it leaves open alternative explanations for the observed gender asymmetry, such as whether female postdocs self-selected (i.e., were more likely to apply to work with female faculty). Despite these concerns, the findings are suggestive of a male faculty bias in recruiting and appointing postdocs that can eventuate in more male professors being hired, despite the fact that biology is a field that appears to be female-friendly.

There is one experiment in the last 30 years that has addressed the question of sex bias in the hiring of professors; it was conducted by Steinpreiss and her associates 16 years ago (Steinpreis et al., 1999). They found faculty of both genders preferred to hire the male applicant over the identicallyqualified female applicant. However, there are two features of this experiment that limit its applicability: first, it examined bias in only one field, psychology, which is the field in which women are best represented—psychology has the largest fraction of women professors of all STEM fields, constituting the majority of faculty. Second, Steinpreiss et al. did not find a preference for hiring a man over a woman when the hypothetical applicants were depicted as unambiguously stellar senior faculty applicants (considered for early tenure). The reason these points are noteworthy is that Koch et al.'s metaanalysis found small-tomoderate sex bias in male-dominated jobs when applicants had average or ambiguous competence (d = 0.29) but, as noted above, no bias when applicants had high competence (d = 0.02) or when evaluators were motivated to be careful (d = 0.01), both conditions that characterize tenure-track hiring. For hiring tenure-track professors in male-dominated fields such as engineering, physics, and economics, experienced professionals might be expected to exhibit little or no sex bias when evaluating applicants who are unambiguously competent. Finally, some evidence suggests that an implicit stereotypic association of race with violence in a videogame simulation did not lead to racist behavior when participants held relatively high implicit negative attitudes toward prejudice (Glaser and Knowles, 2008). This suggests that motivation against possessing or demonstrating bias influences behavior and attitudes of even those possessing implicit biases.

In contrast to experiments showing hiring bias, Williams and Ceci (2015) reviewed 8 large-scale audits of actual hiring that indicate women are preferred for tenure-track hiring in the real world. For example in a large National Research Council (NRC) (2009) analysis, women were hired at rates higher than their application numbers in every field assessed at the 89 research universities the NRC panel studied: in mathematics, women constituted 20% of applicants but 32% of hires; in electrical engineering women were 11% of applicants but 32% of hires; in chemistry women were 18% of applicants but 29% of hires; and in physics they were 12% of applicants but 20% of hires. Similar pro-female hiring data were reported in the National Computer Research Association hiring report for professorships in computer science: "as new PhDs, women submitted far fewer applications than men but received many more offers per application. Female new hires applied for only 6 positions (compared with 25 for men), obtained 0.77 interviews per application (vs. 0.37 for men), and received 0.55 offers per application (vs. 0.19 for men). Obviously women were much more selective in where they applied, and also much more successful in the application process." Against this backdrop of actual hiring data showing a preference for female applicants, a goal of this program of research has been to determine whether this hiring advantage occurs because women applicants are more qualified than men. Williams and Ceci (2015) showed in their experiments this is not what is driving the female hiring preference because women applicants continue to be preferred over male applicants who are equally qualified. This is in contrast to frequent claims to the contrary.

# Present Study

In a recent series of experiments, Williams and Ceci (2015) asked a nationally stratified sample of 873 faculty from four academic fields (economics, psychology, biology, and engineering) to rank two otherwise identically-qualified hypothetical finalists for a tenure-track assistant professorship in their department. These identically-qualified finalists were referred to as Dr. X and Dr. Z and they were presented to faculty with identical quantitative ratings of their candidacy based on their research, job talk, letters, and interview; the sole difference between them was their gender. Faculty were informed that Dr. X and Dr. Z were both rated 9.5 by their departmental colleagues on the basis of their publications, interview, letters, and meetings, where 10.0 = outstanding/exceptional and 1 = cannot support for tenure-track hiring. Thus, Drs. X and Z were depicted as unambiguously strong applicants, which is realistic for tenure-track applicants who have made it to the short list of finalists in searches that often generate hundreds of PhD

applicants.<sup>1</sup> Faculty preferred to hire the female 2-to-1 over her identically-qualified male counterpart. This strong profemale bias was found in all four fields and by faculty of both genders with the exception of male economists who showed no preference between equivalently-qualified female and male applicants. Because of its stratified national sampling and use of sampling weights, the Williams and Ceci (2015) findings were representative of the size of the ratio at all types of institutions, from small teaching-intensive colleges to large, research-intensive ones.

There were two features in Williams and Ceci's experimental design that were implemented to obscure the true purpose of their experiment, one of which is relevant in the present context. To obscure the true nature of their hypothesis so that faculty would not realize they were being assessed to determine whether they harbored sexist biases in hiring, Williams and Ceci disguised the study to appear as a competition between different personalities. In actuality the personalities were counterbalanced with gender and varied in a between-subjects design. In addition to the use of this personality disguise, there was another ploy used to minimize faculty respondents' awareness; it was the addition of a third applicant, a foil. In addition to pitting an equally-qualified Dr. X against a Dr. Z, Williams and Ceci added a third short-listed competitor who was pretested to be slightly inferior to X and Z, labeled Dr. Y. Unlike Drs. X and Z who were both given quantitative scores of 9.5, Dr. Y was given 9.3, which although still very strong is slightly inferior. In the Methods section we describe this feature in more detail because it is a central aspect of the present study. Thus, the inclusion of these two features—a slightly lower-rated foil (Dr. Y) and the counterbalanced adjectives—served to disguise the true purpose of the experiment. And the misdirection appeared to work: A survey of 30 faculty in their study reported no suspicion that the experiment had to do with gender preference in hiring.

Summing across numerous analyses, Williams and Ceci reported the odds of preferring a woman over an identicallyqualified man was roughly 2-to-1. Importantly for the purpose of the present experiment, only 2.53% of faculty preferred to hire Dr. Y over his slightly stronger competitors, Drs. X and Z. In a subsequent experiment that excluded the Dr. Y foil, these researchers asked faculty to rate only one applicant (either a female or male finalist), to avoid implicit competition between a woman and man. Faculty assigned their own quantitative scores to the applicant they were sent to evaluate. Again, there was a preference for women, with faculty of both genders giving the female candidate a higher quantitative score than other faculty gave the identically-qualified male candidate. This latter finding suggests that faculty have internalized the norm of gender diversity and were not merely responding in a manner that is politically correct or to exhibit some other form of impressionmanagement, because faculty had no knowledge that other faculty were evaluating the identical accomplishments in the form of an opposite-sex applicant.

These results raise an intriguing question regarding the pervasiveness of the preference for women: Would it still be observed if the Dr. Y foil was a woman instead of a man? If Dr. Y was a slightly less accomplished female finalist as compared to the two male finalists, would faculty still reject her—that is, would they still choose her only 2.53% of the time as was found when Dr. Y was a male? Or would the desire for gender diversity among faculty be sufficiently strong that they would prefer to hire a slightly less accomplished female Dr. Y over more accomplished male applicants? This is the question we attempt to answer in the current experiment. It will shed light on the extent of faculty's desire to diversify the academy: It is one thing to find that faculty of both genders prefer to hire a female applicant over her identically-qualified male counterpart by a ratio of 2 to-1, but it is another matter to ask whether this preference for female applicants extends to a preference to hire a slightly weaker female applicant, one described as 9.3 on a 10-point scale who is competing against two males who are described as 9.5.

Thus, the current experiment consisted of a comparison of a woman assigned a slightly lower quantitative score competing against two men assigned a slightly higher quantitative score, all of whom were competing for the same assistant professorship. We used the same 9.3 vs. 9.5 quantitative scores used by Williams and Ceci (2015) because their survey provides a national baserate for faculty expectations for this contrast. If a preference is found for a female finalist depicted as 9.3 over men depicted 0.2 points higher, then subsequent contrasts between even lowerrated females would be in order. But first we sought evidence of preferential hiring of women who are only slightly weaker than their male competitors.

# Methods

# Participants

The pool of potential faculty participants was assembled by drawing a national stratified sample of 694 tenured/tenuretrack professors (half female, across all ranks). This was done by randomly sampling from online directories for Carnegie Foundation's 3 Basic Classifications of: (a) Doctoral (combining all three levels of doctoral intensity), (b) Master's institutions (combining all three levels—small, medium, and large), and (c) Baccalaureate institutions (combining all three levels of such institutions). This sample of 694 professors was drawn equally from four popular fields, two math-intensive ones in which women faculty are greatly underrepresented— < 15% (engineering, economics)—and two non-math-intensive fields (biology, psychology) in which women faculty are well represented and are considered to have achieved what gender

<sup>1</sup>For example, a faculty respondent in the field of biology in Williams and Ceci's experiment wrote: "In a typical search these days we will receive over 200 applications for one position. The search committee triages that down to a group of around 30 or 40, and then no more than around 6–8 are invited to come for a threeday visit and to give a seminar." Many similar comments were offered by others in their national survey, hence the finalists are usually unambiguously strong, as is true in our own department where a recent tenure-track search for an assistant professor generated 267 applicants in psychology. All applicants who survive to the short list are accomplished, having successfully completed doctorates, published papers, and garnered strong letters of recommendation. In a separate rating task we gave 35 faculty the CVs of actual short-listed candidates and asked them to rate these on a 10-point scale and, as expected, the mean rating was in the excellent range.

equity advocates regard as a critical mass, although even these fields still produce significantly more female PhDs than the female fraction of total professorships. There were two constraints in randomization. One was that for an institution to be included it had to have programs in at least three of the four fields. This was true of all doctoral institutions in the sampling frame, but it excluded many small colleges that lacked two or more of the four fields, and over half of the nation's combined master's programs. The second constraint was that only tenured or tenure-track faculty were included in the sample frame; offline faculty (emeriti, adjuncts, lecturers, instructors, courtesy faculty members, and visiting professors) were excluded, as only faculty who actually vote on tenure-track hiring were desired as subjects.

Overall, out of the 694 faculty who were assigned to one of two conditions, 252 responded with full data (36.3%): 158 rated a male Dr. X who was pitted against a female Dr. Y and a male Dr. Z; and 94 rated a female Dr. X who was pitted against a male Dr. Y and a female Dr. Z.

## Materials

Two sets of materials were used, the first containing profiles of two male applicants, Dr. X and Dr. Z, with identical scholarly qualitative scores but differing in gendered adjective descriptors ("kind, socially-skilled, creative" vs. "analytical, competitive, powerhouse"). As noted, these descriptors were used to disguise the actual hypothesis, leading raters to believe the research question was whether they preferred one type of individual over the other. These gendered descriptors were counterbalanced so that half the faculty received Dr. X portrayed as a male "analytical, competitive, powerhouse" competing against Dr. Z as a male "kind, socially-skilled, creative" colleague, and half received Dr. X and Z portrayed with the opposite terms. Dr. Y was described as "shy and reserved," which is more negative than "socially skilled" or a "real powerhouse," and in the chair's notes some concern was raised about Y's teaching performance, whereas no concern was raised for X or Z. Thus, the quantitative "pre-rankings" gave an explicit cue that Drs. X and Z were stronger than Dr. Y, albeit only slightly so (see Supplementary Material for one set of these materials). These different personae were the same as those used by Williams and Ceci (2015) and were based on gender congruity norms (Diekman and Eagley, 2000; Cuddy et al., 2004). Notwithstanding this systematic variation of these descriptors between faculty raters, Drs. X and Z were otherwise identical: both were rated 9.5 out of 10.0 in quality on the basis of their scholarly accomplishments, job talk, and faculty meetings. This corresponded to "impressive."

In every contest between the male Drs. X and Z, a third candidate was added, a female Dr. Y, who was depicted as slightly lower in scholarly quality (9.3) than the male Drs. X and Z, and who was pretested with an independent group of faculty who did not participate in this experiment to ensure that raters perceived her quality as slightly lower. Dr. Y was always depicted in the same terms used by Williams and Ceci for their Dr. Y foil when he was a male, since it was established that under these conditions their male Dr. Y was chosen by only 2.53% of faculty in their large stratified national sample.

The second set of materials simply reversed the genders so that Drs. X and Z were depicted as women and Dr. Y as a man; everything else was identical.

#### Procedure

Thus, the contest presented to every faculty member was to choose between three finalists for a tenure-track position, in one condition with Drs. X and Z both being male candidates of equivalent quality (9.5) and Dr. Y being a slightly lower quality female candidate (9.3), and in the other condition with these genders reversed (see Supplementary Material for materials). Faculty members were sent personal emails containing one of the counterbalanced depictions, and were asked to rank these three finalists in order of their hiring preference: first, second, and third for a tenure-track assistant professorship in their own department. The question of interest is whether faculty exhibit preferential hiring for female applicants possessing slightly lower quantitative scores than their male counterparts.

# Results

The main analysis examined which candidate was ranked first by faculty of each gender and at each type of college/university, and in each of four academic disciplines. In addition to the four disciplines (engineering, economics, psychology, biology) there were three types of colleges/universities based on the Carnegie classification (1 = doctoral, 2 = bachelors/masters, 3 = baccalaureate).

The response rates for every cell (university Carnegie type by discipline by gender, 3 × 4 × 2) were evaluated in a logistic regression. Response rates for the 252 faculty across these 24 cells were unrelated to the findings. These data were analyzed with both unweighted and weighted logistic regression models to provide a stronger test on their representativeness. Here we report only the traditional unweighted analyses but the weighted results (weighted to account for differences in the numbers of men and women in the population and in the sampling frame) were highly similar, with no result changing.

Across the 158 contests between the equivalently strong male Drs. X and Z, only 7 faculty respondents preferred the slightly weaker female Dr. Y, and one faculty rater gave tied ranks for X and Y for first place. This resulted in an overall female Dr. Y-preference of 4.8%. In the condition in which 92 faculty were asked to choose between two slightly more accomplished women—Drs. X and Z—and a slightly less accomplished male Dr. Y, only 1 out of 92 respondents chose the latter (1.2%). There was no statistical difference between Y foils when depicted as male vs. female, chi square 2.136, p = 0.144 (The 95% CIs for the ratio of choosing Dr. Y 7 times out of 158 contests is between 2 and 9 percent, and the ratio of choosing Dr. Y 1 time out of 92 contests is between 0 and 6 percent; the CI of the difference in proportions covers 0, ranging from −1.59 to 7.3 percent).<sup>2</sup> There were no differences between the four disciplines in this male vs. female Y-preference, nor were there

<sup>2</sup>With low counts some approximations used to compute CIs will not work well, so we used a number of methods to compute the CIs in R. The results were similar: The CIs for the ratio of choosing 7 Ys out of 158 pairings is between 2 and 9 percent,

any differences between the three types of Carnegie institutions or between male and female faculty members, all p > 0.20. Finally, faculty gender did not interact with the gender of the Y foil. Basically, everyone preferred the more accomplished X and Z candidates over the less accomplished Y candidate, regardless of Y's gender. And this extended even to fields in which women are very underrepresented (engineering and economics).

(PropCIs) library(binGroup) binCI(158,7,.95) 95 percent CP confidence interval [ 0.018, 0.08915 ] Point estimate 0.0443 binCI(92,1,.95) 95 percent CP confidence interval [ 0.0002752, 0.05908 ] Point estimate 0.01087 scoreci(7,158,.95) data: 95 percent confidence interval: 0.0216 0.0886 scoreci(1,92,.95) data: 95 percent confidence interval: 0.0019 0.0590 binom.test(7,158) Exact binomial test data: 7 and 158 number of successes = 7, number of trials = 158, p < 2.2e−<sup>16</sup> alternative hypothesis: true probability of success is not equal to 0.5 95 percent confidence interval: 0.01799534 0.08915030 sample estimates: probability of success 0.0443038 binom.test(1,92) Exact binomial test data: 1 and 92 number of successes = 1, number of trials = 92, p < 2.2e −16 alternative hypothesis: true probability of success is not equal to 0.5 95 percent confidence interval: 0.0002751557 0.0590778511 sample estimates: probability of success 0.01086957 add4ci(7,158,.95) data: 95 percent confidence interval: 0.02028254 0.09082857 sample estimates: [1] 0.05555556 add4ci(1,92,.95) data: 95 percent confidence interval: 0.06605514 sample estimates: [1] 0.03125 wald2ci(7,158,1,92,.95,adjust = T) data: 95 percent confidence interval: −0.01590209 0.07334890 sample estimates: [1] 0.0287234

In view of this finding, there was no justification for conducting a follow-up experiment in which the female Y foil was depicted as less qualified than the 9.3 value used in this experiment, given that she was not preferred even at this slightly lower level, meaning that she would not be ranked higher if she were depicted as lower in quality than 9.3 out of 10.

# Discussion

When, as in the present experiment, women candidates are depicted as slightly less accomplished than their male counterparts, they did not have a significant gender advantage in hiring, and were bypassed in favor of slightly superior male candidates 95.2% of the time, which is not significantly different from the 97.47% bypass rate of males depicted as slightly less accomplished (2.53% choosing male Y foil who had a 9.3 score) in Williams and Ceci's (2015) experiment. That is, this result is also similar to the situation in which Dr. Y is depicted as a less accomplished male competing against two stronger female Drs. X and Z. In this latter contest, the male Dr. Y is chosen only 1.2% of the time (all p > 0.10, n.s.). Even taking into account low power to detect differences between magnitudes this small, the hundreds of faculty in the Williams and Ceci (2015) study and the hundreds in the present study suggest that it is rare (<5%) to prefer any applicant who is depicted as even slightly weaker than her or his competitors. Apparently, academic faculty view quality as the most important determinant of hiring rankings, which suggests that when women scientists are hired in the academy it is because they are viewed as being equal or superior to male competitors.

Hence, the current findings should help dispel concerns that affirmative hiring practices result in inferior women being hired over superior men (e.g., Niederle et al., 2013). Even though the Dr. Y foil was described as only slightly less accomplished, faculty almost always preferred to hire a slightly more accomplished candidate, and this preference was independent of the gender of the candidates and the gender of faculty raters, and it was observed in both math-intensive and non-intensive fields.

The absence of preference for male Dr. Y does not necessarily imply that academic hiring is meritocratic under all conditions. It is possible that with different levels of candidate information (or if the candidates involved were at a somewhat lower level as opposed to being in the top tier), different results might have been found. For example, in the Steinpreis et al. (1999) study no gender preferences were found when the candidate's CV was highly competitive, but a male preference was found when the CV was less strong. The current study is consistent with these results at the highly competitive candidate level, and showed that slightly less exceptional female candidates were not preferred over exceptional male candidates. Relatedly, Dovidio and Gaertner (2004) findings on aversive racism and selection decisions found that white participants did not discriminate against an unambiguously strong black candidate (vs. a white candidate), but discrimination occurred when the candidates' qualifications were depicted as ambiguous. These findings suggest that discrimination may be a concern when candidate qualifications are ambiguous, but not when candidates

and the ratio of choosing 1 Y out of 92 pairings is between 0 and 6 percent. The CI of the difference in proportions covers 0 and ranges from −1.59 to 7.3 percent. Exact numbers below using the R code:

are exceptionally strong. Thus, the most prudent interpretation of the present results is that exceptionally strong candidates of both genders are unlikely to face gender discrimination. Given that the current study focused on top-tier candidates, any conclusions drawn should be confined to excellent tenure-track candidates.

The present findings may provoke concern of a different sort. If affirmative action is intended to not merely give a preference to hiring a woman over an identically-qualified man, but also to tilt the odds toward hiring a woman who may be slightly less accomplished but who is still rated very highly (recall that a 9.3 was in the "extremely impressive" range), gender diversity advocates may be disheartened by these findings. Those who have lobbied for more women to be hired in fields in which they are underrepresented, such as engineering and economics, may find the present findings dismaying and argue that, in the context of hiring in a field in which women are underrepresented, extremely well-qualified female candidates should be given preference over males rated a notch higher. Walton et al. (2013) argued on both empirical and theoretical grounds that hiring more members of devalued groups would actually promote meritocracy, diversity, and organizational performance, not undermine it. (Consideration of this argument entails complexities that are beyond the scope of this study.)

Notwithstanding differing views regarding affirmative hiring of impressive women in underrepresented fields, one claim finds no support in the present results. It is the allegation that the dearth of women in some fields is the result of superior women being bypassed in favor of less accomplished men—a claim made by numerous commentators.<sup>3</sup> If academic hiring is anti-meritocratic, then the weaker male Dr. Y should have been chosen over his stronger female competitors. But as seen, only 1.2% of males who were depicted as the slightly weaker candidate were preferred over slightly stronger female candidates. Thus, there is no support for the view that superior women are being bypassed in favor of inferior men when the contest is between highly accomplished candidates. Hence, these findings call into question claims of current biased tenure-track hiring that have been put forward and they suggest this is a propitious time for talented women to launch tenure-track careers in academic science, where their impressive credentials will be viewed favorably by hiring committees vis-à-vis identically-qualified men.

None of this means that women no longer face unique hurdles in navigating academic science careers. Evidence shows that female lecturers' teaching ability is down-rated due to their gender (Bug, 2010; MacNell et al., 2015), letter writers for applicants for faculty posts in chemistry and biochemistry use more standout (ability) words when referring to male applicants (Schmader et al., 2007), faculty harbor beliefs about the importance of innate brilliance in fields in which women's representation is lowest (Leslie et al., 2015), and newlyhired women in biomedical fields receive less than half the median start-up packages of their male colleagues, which could conceivably result in fewer publications down the line (Sege et al., 2015)—to mention a few areas where women continue to face hurdles. Nor do the present findings deny that historic sexist hiring prevented many deserving women from being hired. But these findings do call into question broad or unqualified claims of biased tenure-track hiring that have been put forward. The present findings are not incompatible with earlier studies that found anti-women bias at lower levels hiring a lab manager, (Moss-Racusin et al., 2012) or getting emails returned (Milkman et al., 2012), or hiring members of a math team (Reuben et al., 2014) if one assumes that bias may come into play when diagnostic information is missing (Koch et al., 2015) but not when such information is present as in the case of hiring a candidates who earned doctorates and garnered strong letters and ratings. This suggests that sex biases might reduce the number of women entering training for the STEM pipeline, but our results indicate that when a woman emerges as a strong candidate for a faculty position, she is no longer handicapped as far as being offered the job. Thus, these earlier findings of bias against less accomplished women (e.g., those applying to be lab managers) and the present findings are not mutually exclusive with the current results showing that top-tier female candidates are viewed favorably. This suggests that the gender gap in mathintensive fields might be best addressed by focusing on earlier experiences (encouraging more females to take high school AP physics, computer science, Calculus BC, recruiting more women into college STEM majors—areas identified by Ceci et al. (2014) as associated with the underrepresentation of women in these fields).

These new data will be of interest to academics struggling to increase the representation of women, because our data refute the claim that affirmative hiring policies are non-meritocratic

<sup>3</sup>Many commentators have opined that female scientists are superior to their male counterparts, and therefore the fact that they are hired at the same rate as men obscures the fact that they should be hired at even higher rates, if merit was the basis for hiring. Consider:

<sup>&</sup>quot;The studies [claiming gender neutrality] examined odds ratios rather than details of the proposals submitted. This does not rule out the possibility of gender bias. As Marie Vitulli and I said in 2011 [Kessel and Vitulli, 2011], "selection bias can also explain why, in the presence of gender discrimination, female scientists might still fare as well as their male colleagues in some respects if their work was better on average than that of their male peers." (Kessel, 2012) "Given qualified women drop out of math-intensive fields at higher rates than their male peers. the women who remain are probably, on average, better than their male colleagues and should be having better (hiring) outcomes on average. If their salaries, resources, publication rates, etc. are similar, it then indicates gender discrimination still exists, not that this problem has been solved." (http://blogs.sciencemag.org/sciencecareers/2011/02/ the-real-cause.html; retrieved on June 22, 2014)

<sup>&</sup>quot;Female scientists were either not retained or not hired so that only a couple of super-brilliant female scientists were working in staff-scientist positions. On the other hand, several mediocre male scientists were hired and retained, many rising to staff-scientist positions or higher.  (Kali, 2011)

and lead to less competent women being preferred for jobs. At the same time, these data debunk the claim that less-qualified men are favored over more-qualified women. We found no support for this, either. For those who believe affirmative action means giving a boost to an underrepresented group when all else is equal, our data will be welcome news, since we show that academic hiring preferences are quality-based. However, for those who argue that affirmative action means choosing slightly less accomplished individuals over more accomplished ones for reasons of diversity, our data suggest that at least when it comes to gender, faculty may be reluctant to embrace this pathway to diversity.

## Possible Reactions to These Findings

Our work on this topic has led to certain comments that we have heard repeatedly. We note some of these below along with a few reactions in response to them:

seems unpersuasive in view of the fact that in the real world of academic hiring women also are chosen over men in disproportionate numbers. As one commentator noted in arguing for the relevance of the current experimental design: "One would have to say both that women are, in fact, stronger candidates (which is one strong assumption for which there is no direct evidence), implying that faculty don't prefer them over equally qualified men in real hiring contexts, and that, nonetheless, faculty DO prefer them in hypothetical situations (another strong assumption for which there is no direct evidence). By far the most sensible explanation is the most economical one: faculty prefer women both in the hypothetical case and the real case; their preferences don't swing wildly from the actual to the hypothetical."

5. "The process of assigning a rating to a woman's dossier is inherently prone to sexist bias; thus, women are less likely to receive an equivalent rating to that of male competitors." This is a popular view; however, we found that subjects evaluating a single dossier, presented as either female or male, assigned a significantly HIGHER rating to that dossier when it belonged to a woman than a man (8.20 vs. 7.14, p < 0.01). The translation of traditional indicia (publications, letters, etc.) into ratings seems to work at least as well when ranking a female applicant.

### Limitations of Present Study

No experiment is perfect, and this one is no exception. It is possible that the faculty raters rarely chose the less competent candidate because they were supplied with "preranked" quantitative ratings of the candidates (e.g., 9.3 or 9.5 on a 10-point scale). Hence, the present results may have been influenced by giving faculty "pre-ranked" ratings. Perhaps in the absence of being given quantitative ratings, faculty will shift criteria to justify their final decisions (e.g., be influenced by gender to give more credence to the eminence of an applicant's advisor/institution if a woman's list of publications is shorter than her male competitor's). Assigning pre-ranking scores will likely be variable in actual hiring; this variability in assigning scores could increase the rate of selecting someone who's rated a 9.3 on average. In other words, disagreements would likely be more common in actual hiring decisions due to the variable ways faculty translate their impressions. Since concerns about personality and teaching performance were raised for Dr. Y, but not for Drs. X or Y the primary reason someone might want to hire Dr. Y was gender when Y was a woman.

The present data provide no hint of the extent to which this occurs. However, in Experiment 5 of the Williams and Ceci (2015) paper, 127 faculty were given only one applicant to rank, either a man or woman who were identically accomplished. When the applicant was a man the faculty who were asked to rate his strength gave him a rating of 7.14 but when the identical portfolio belonged to a woman, the faculty who were asked to rate her gave her a rating of 8.2 (p < 0.01). So there is some suggestion that faculty shift their quantitative ratings to justify their preference for women, even when they are asked to generate the rating themselves, for what are actually identical accomplishments of both genders. If true, the present findings suggest this shift is limited to conditions in which candidates are identically competent and very accomplished.

In future research it would be interesting to vary the CVs of the 9.3-rated female applicant and the 9.5-rated male applicants in terms of their number of publications, advisor eminence, teaching awards during graduate school, the prestige of their PhD-granting institutions, etc. to determine how much shift in faculty-assigned quantitative ratings is observed as a function of applicant gender. In this experiment we began with the smallest difference of 9.5 vs. 9.3, with a plan to widen this gap if it turned out that faculty preferred slightly weaker women; but since they did not, there was no reason to widen the gap.

The low baserate for choosing the Y foil presents statistical issues: The rate of selecting the female Dr. Y (4.8%) was slightly higher than rate of selecting the male Dr. Y (1.2%), although this difference was not statistically reliable. Statisticians have written about the challenges of comparing frequencies of rare events (e.g., Bradburn et al., 2007). This has ramifications if the null result is affected by low statistical power, and future research might enlarge the sample size to see whether weaker women may be preferred over stronger men. However, faculty preference for the less qualified Dr. Y candidate was always rare in this experiment and in the Williams and Ceci (2015) one (<5%), regardless of applicant gender, so even if a preference for the weaker female became significant, the magnitude of such an effect would likely be quite small.

Although the current study is well-suited to address the specific question it posed, it employed a very specific methodology and DV that may have limited the operation and detection of implicit bias. It is possible that the use of implicit measures may have revealed bias as has been observed to occur even among university professors. Measures of explicit bias may not always be collinear with implicit measures (see Smyth and Nosek, 2015). As was noted in the introduction, findings from real-world hiring audits (not experiments, but actual hiring of university professors) indicate female applicants are typically hired at higher rates than their male counterparts—for at least the last two decades (Williams and Ceci, 2015).

Many have argued that the pro-women hiring preference is because women are on average stronger applicants, by dint

# References

of the winnowing process they have survived from college-to graduate school-to applying for tenure track jobs: it is argued that the reason women are more likely to be hired than their male counterparts for tenure track jobs in the real world is because those women who end up applying for tenure-track jobs represent the "cream of the cream," a higher mean quality than the typical male applicant. Williams and Ceci (2015) designed their experiments to test this claim and reported that even when applicant strength was equated (experiments 1–3), faculty still preferred female applicants over identical male applicants. And as noted above, in their fifth experiment 127 faculty were asked to assign their own strength ratings (on a 10-point scale) to either a man or woman applicant. Faculty rated the same applicant 8.2 when it had a woman's name on it but only 7.14 when it had a man's name on it. So Dr. Y did not receive lower scores when described as a woman, and higher scores when described as a man, as some would predict.

Finally, the experimental condition that involved two female finalists (out of three) might have seemed odd for a STEM faculty member in math-intensive fields where 70%-plus of applicants are often male. On the flip side, having the woman be lowerrated than two men might have also made gender more salient. To the extent that either of these is true, it is an important issue that future research should address (e.g., by conducting focus groups or using a shortlists of only two applicants, only one of whom is female—a situation we deliberately rejected because we felt it might make the gender contest overly salient and explicit). However, in view of the media and publicity surrounding findings from these type of experimental designs, follow-up research cannot be undertaken in the near future without compromising the experimental reactivity of participants.

# Funding

This research was supported by NIH Grant 1R01NS069792-01.

# Supplementary Material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg. 2015.01532

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Ceci and Williams. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Leaky Pipeline Myths: In Search of Gender Effects on the Job Market and Early Career Publishing in Philosophy

#### Sean Allen-Hermanson\*

Department of Philosophy, Florida International University, Miami, FL, United States

That philosophy is an outlier in the humanities when it comes to the underrepresentation of women has been the occasion for much discussion about possible effects of subtle forms of prejudice, including implicit bias and stereotype threat. While these ideas have become familiar to the philosophical community, there has only recently been a surge of interest in acquiring field-specific data. This paper adds to quantitative findings bearing on hypotheses about the effects of unconscious prejudice on two important stages along career pathways: tenure-track hiring and early career publishing.

Keywords: underrepresentation, gender bias, sexism, hiring, philosophy

#### Edited by:

Stephen J. Ceci, Cornell University, United States

#### Reviewed by:

Rafael De Clercq, Lingnan University, China Matt L. Drabek, ACT, Inc., United States

\*Correspondence: Sean Allen-Hermanson<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

Received: 27 March 2017 Accepted: 23 May 2017 Published: 14 June 2017

#### Citation:

Allen-Hermanson S (2017) Leaky Pipeline Myths: In Search of Gender Effects on the Job Market and Early Career Publishing in Philosophy. Front. Psychol. 8:953. doi: 10.3389/fpsyg.2017.00953

# INTRODUCTION

That philosophy is an outlier in the humanities when it comes to the underrepresentation of women has been the occasion for a lot of discussion about possible effects of subtle forms of prejudice, including implicit bias and stereotype threat. Though real-world effects are not strongly evidenced (Forscher et al., 2017), there is widespread concern in philosophy that involuntary and unconscious implicit associations might diverge from a person's declared beliefs affecting our actions, judgments, and attitudes. Unconscious bias might influence how we treat junior colleagues from socially stigmatized groups when it comes to sharing opportunities for professional development, advancement, and in evaluating scholarly potential and credentials. For example, a departmental committee might implicitly prefer a male candidate to a female candidate with the same qualifications despite holding conscious and explicit attitudes about the equality of the sexes. Meanwhile, stereotype threat is when awareness of and identification with stereotypes (such as that philosophy is for white males) results in heightened anxiety, performance disparities, and reduced interest.

These ideas have become familiar to the philosophical community, which continues to debate policy initiatives and other measures for improving diversity, such as making syllabi and conference line-ups more inclusive, adjusting the management of professional organizations, and reforming journal and hiring practices. These ongoing discussions need to be informed by the best possible evidence, and there is a growing interest in acquiring field-specific data. The investigatory model informing this study is inspired by the hiring audits used in STEM disciplines. This paper contributes data pertinent to hypotheses about the effects of prejudice on two important stages of career pathways: tenure-track hiring and early career publishing.

If women are evaluated more harshly because of unconscious bias on the part of letter writers and hiring committees, or have weaker files and perform less well in interviews because of stereotype threat, or even face conscious and explicit discrimination, then they might be expected

to be less successful at finding tenure-track employment. Indeed, biases are often conjectured to be a major cause of the underrepresentation of women in philosophy.<sup>1</sup> Fortunately there have been several recent studies of employment trends, including Jennings' for a 2-year period (2012 and 2013) and a follow-up funded by the American Philosophical Association known as the APDA report.<sup>2</sup> These and other resources can help test hypotheses predicting effects of biases on hiring.<sup>3</sup> Working from her original data, it was decided that post-doctorate appointments would be ignored in order to focus on more desirable tenure-track lines, leaving us with 229 men and 109 women in the pool. Since this manuscript was written, the data used in the APDA report has been corrected and revised and will also be taken into account. So, how are women doing on the job market?<sup>4</sup> .

# RESULTS

Analysis of Jennings' original data suggests women and men are hired at a rate roughly proportionate to their numbers for entry-level tenure-track jobs in philosophy.<sup>5</sup> Concerning the follow-ups, the first APDA report in 2015 actually found women were hired significantly more often, increasing the odds of obtaining a permanent academic position by 85%.<sup>6</sup> A 2016 update corroborated this finding notwithstanding Jennings' statement that "we did not find a significant effect of gender on placement. . ." <sup>7</sup> While technically true, however, this was only because in 2016 they elected not to examine this low hanging fruit. Despite this flagging of interest in this aspect of the gender question, she did acknowledge there were about 10% more women than men among those obtaining a permanent position over the entire data set (chi-squared test p < 0.01) and (with prompting by an anonymous commenter) admitted the number was much higher (around 23%) concerning those graduating within the most recent hiring cycles (2012–2015). Another commentator also brought the high significance of this result to our attention (chi-square, p = 0.0007). The upshot is that with the help of various anonymous commentators, we can be confident that the APDA findings offer strong support that men are significantly less likely to obtain permanent positions.

Another noteworthy finding obtained from Jennings' earlier results is that female candidates had about half as many publications as their male counterparts. The average publication counts for candidates (having no prior academic appointment) were 1.37 for men and.77 for women (medians 1 and 0; p = 0.000808)<sup>8</sup> and is also extremely significant. However, as the quantity of publications is only one very crude measure of a candidate's strengths, we can also look at how several other variables might depart from these aggregated results. For example, besides quantity, Jennings' data also contained information about the putative "quality" of a publication (defined as a "top-15" journal according to a poll at the Brooks Blog). Here, male tenure-track hires are about three times more likely to have published in a highly regarded venue (see **Appendix** and **Figure 1**).

It is natural to wonder how important publications are when it comes to assessing job candidates, and certainly we can agree publications are not the only relevant factor. Even for a research-oriented position the quality of writing samples, the reputation of doctoral institutions, and the weight assigned to letters of recommendation will also be taken into account. As a rough proxy for reputational factors rankings of degree-granting programs obtained from the 2006–2008 edition of the Gourmet Report were utilized.<sup>9</sup> How publication records of new hires might differ depending on whether they had a prior position or accepted a tenure-track job straight out of graduate school was also considered.

Some have claimed that prestige interacts with gender in that women from highly regarded programs tend to publish the least, whereas men from less fancy programs publish the most.<sup>10</sup> However, we find the relationship between gender and prestige to be somewhat murkier. Although the finding men in general tend to publish more and in more prestigious places was corroborated, program prestige correlated positively with the output of high-quality publications regardless of gender. Gendered differences also depended somewhat on whether we were looking at candidates who had held a prior academic appointment.

First, mean Gourmet Report scores were incorporated within Jennings' spreadsheet revealing a disparity in average home department rankings of 3.31 for men and 2.93 for women (medians were 3.6 and 3.2). High prestige "top-20" departments have a score of at least 3.4, and so next men and women were divided into elite ("top-20") and non-elite ("non-top-20") subgroups to see if there would be any interesting effects.<sup>11</sup> The rankings for male and female "top-20" hires turn out to be very similar with mean scores of 3.94 for men and 4.02 for women (with medians of 3.7 each). Given this, we expect to find a small gendered difference in prestige among the remainder, and

<sup>1</sup> "Implicit bias and stereotype threat. . .will make it harder for women to do well. . .to be recognized in graduate school, less likely to get strong letters of recommendation, and less likely to be hired. The women who, despite this, get hired at strong research departments are likely to be especially exceptional philosophers" (Saul, 2012).

<sup>2</sup>The Academic Placement and Data Analysis project's results can be found here: http://webcache.googleusercontent.com/search?q=cache:szvEA0v8tSgJ:dailynous. com/wp-content/uploads/2016/04/apdareportupdateto2015report.pdf+&cd=2&hl =en&ct=clnk&gl=us&client=safari

<sup>3</sup>http://www.newappsblog.com/2014/12/gender-and-publications.html#more. See also Solomon and Clarke (2009).

<sup>4</sup>Here and there minor corrections were made for errors, such as duplicate entries.

<sup>5</sup>All of our raw data can be accessed at Genderandphilosophy.blogspot.com

<sup>6</sup> See p. 11 of the 2015 report: http://dailynous.com/wp-content/uploads/2016/04/ apdafinalreport2015.pdf

<sup>7</sup>http://dailynous.com/2016/04/15/philosophy-placement-data-and-analysis-anupdate/

<sup>8</sup>Meaning a 99.9192% confidence that the result is not due to chance. P was obtained using a Fisher exact test.

<sup>9</sup> It was reasoned that the reputational ranking should reflect the fact that candidates take around 5 or 6 years to obtain their degrees. But the results do not differ much if a slightly more recent or less recent edition is used instead.

<sup>10</sup>See http://genderandprestige.blogspot.com

<sup>11</sup>Note that candidates from top-20 schools appear to fill half of new tenure-line positions.

indeed the averages here are 2.26 for men and 1.9 for women (with medians of 2.6 and 2.3).<sup>12</sup> It was also noted that there was no significant interaction between gender and the prestige of hiring departments, though there was evidence candidates from relatively lower prestige institutions lack upward mobility: Whereas top candidates of either gender could expect to find a position at a Gourmet-ranked institution a bit less than half the time, this was true of other candidates only 7–8 percent of the time (**Figure 2**). This might indicate that there are, in effect, two semi-independent job markets. In terms of outcomes, there seems to be a top-20 market mostly closed to non-elite candidates and a non-top-20 market open to all.

Next, turn to consider how prestige might interact with gender when it comes to publishing. As mentioned earlier, differences depended on whether candidates had a prior appointment. In considering those with no prior appointment, it was found that top-20 men stand out: they publish more, and in "better" places than the others. Meanwhile, top-20 women publish less often than non-top-20 men and women, nevertheless they tend to do better when it comes to quality (**Figure 3**). As it is unclear how to weight quantity versus "quality" in assessing candidate strength, no conclusions are drawn here about the advantages or disadvantages of the remaining subgroups. We can observe that top-20 women have much more access to top-20 jobs, which might suggest "quality" counts for more across the market. Alternatively, there might be different standards for the different "markets" proposed above: top-20 individuals appear to be a little stronger concerning "quality" and non-top-20 are stronger for quantity (**Figure 4**). Perhaps then publishing counts, but counts differently depending only whether one is competing on the "elite" market favoring "quality" or the "non-elite" market favoring raw output.<sup>13</sup>

FIGURE 2 | Gourmet-ranked TT positions.

<sup>12</sup>Women seem to be slightly more likely to obtain degrees from unranked programs, which were scored as a "0." Hence, if we ignore unranked programs these small differences in the overall rankings disappear.

<sup>13</sup>Against this the reader is asked to compare the data in **Figures 3**, **5**, which might suggest that when it comes to re-entering the market with a prior position it may

Now we can consider the candidates who did have a prior position. Here, men had significantly higher averages for quantity and "quality" (**Figure 5**). For example, low-prestige men published almost three times as much as the average high-prestige women and were about two times more likely to have a top-15 publication. This might indicate that women, regardless of prestige, tend to submit to journals less frequently because they are less confident, as expected by hypotheses invoking stereotype threat<sup>14</sup> or even disadvantages in the reviewing process.<sup>15</sup> Then again, there are several other explanations for the publishing gap. Notwithstanding this uncertainty, men and women appear to be held to different standards.

Returning to an earlier suggestion, might it be the case that publications are not that important in hiring? This is hard to accept given that productivity is so often tied to securing research-intensive positions in the competitive academic environment and critical to determinations about prospects for earning tenure. This seems clear when we consider lateral hires, which constitute much of the data, and as just mentioned indicate upward trends in output. That candidates from less fancy programs publish more regardless of gender also suggests a widespread presumption that publishing compensates for other deficiencies. We can also note that previous research indicates that publication records are a critical indicator of candidate strength (Steinpreis et al., 1999).

In a blog comment, Jennings<sup>16</sup> attempts to explain away the publishing gap by proposing that enhanced opportunities are more often offered to males. Others have also worried that "at the graduate level, supervisors may be more likely to encourage men to publish their work" (Saul, 2013). Jennings wonders if most of

be more important for non-elite candidates of either gender to improve "quality" and elite candidates to improve quantity.

<sup>14</sup>Though we note that enthusiasm for stereotype threat theory is in rapid decline thanks to concerns about ecological validity, experimental design and interpretation, replicability, and evidence of publication bias, see Sesardic and De Clercq (2014).

<sup>15</sup>This finding of a gender gap in publishing is in step with Krishnamurthy et al. (forthcoming).

<sup>16</sup>http://www.newappsblog.com/2014/12/gender-and-publications.html#more

the difference between genders is attributable to a handful (15%) of high productivity (HP) men, defined as those with at least five publications at the time of hiring (5% of women are HP by the same standard).<sup>17</sup> Yet these numbers are derived from looking at all hires, including those candidates who had a prior academic appointment, and therefore more opportunities to publish. When we consider those with no prior position, none of women and only 3% of the men (n = 7) are HP. Since there are so few, the gap cannot be explained by those who are highly productive.

Nevertheless, all HP hires were examined in order to see what proportion of their work might be attributable to enhanced opportunities.<sup>18</sup> Using Google searches of cvs the number of such publications for each of the 61 HP candidates was obtained by counting works that were co-authored with a senior figure, articles or chapters in edited volumes, conference proceedings, and publications which otherwise appeared to be by invitation, such as introductions to special issues.<sup>19</sup> Although the pool of HP women is small<sup>20</sup> it was found that 37.5% of their publications fell into this category. Turning to the men, first those who were exceptionally productive (having at least 10 publications) were examined. The rationale here is that if the HP men are favored with extra opportunities, this will likely be reflected in the output of those who publish the most. Yet for this group, only 34.3% of their work was attributable to enhanced opportunities<sup>21</sup> while the result was 37.7% for all HP men.<sup>22</sup> In addition, the means, medians, and modes for those in the HP group did not significantly vary by gender. While not exhaustive, as there could be other kinds of special opportunities, favoritism in a non-blind review process, as well as differential barriers to obtaining prior positions, the data offered here suggests HP men and women are treated about equally. It was found that highly productive men were about twice as likely to publish in well-regarded ("top-15") journals.<sup>23</sup>

Returning to market outcomes, the previous results were augmented by placement data obtained from two additional sources: the American Philosophical Association's Guide to Graduate Programs<sup>24</sup> and the Philjobs website<sup>25</sup> and cohere with similar findings from hiring audits in STEM fields (Williams and Ceci, 2015). In addition, individual notices of new appointments from Philjobs for the 2014 hiring season were monitored.<sup>26</sup> Next the analysis of the APA data is presented followed by a consideration of the findings obtained from Philjobs.

Data was transcribed about gender and hiring found in the APA's 2013 and 2014 Guides to Graduate Programs for two 5 year periods: 2008–2013 and 2009–2014. Only programs that allowed for a comparison between hiring outcomes and how many men and women went to market were included in the calculations. The Guides provided data for 64 schools in the 2013 edition and 65 for 2014 (37 schools provided data twice, so there is placement information available for 92 distinct programs for these mostly overlapping timespans). For 2008–2013 it was found that 40% of men who went on the market eventually landed a tenure-track job compared to 50.6% of the women, meaning a woman's probability of obtaining tenure-track employment was about 25% better (p = 0.037).<sup>27</sup> The corresponding probabilities of obtaining any kind of academic position (including much less desirable temporary appointments) were a lot closer at 86 and

<sup>17</sup>HP candidates were very likely to have had at least one prior position (median for both genders = 1; means were 0.88 for men and 0.86 for women).

<sup>18</sup>In this case, we also included 10 highly productive individuals with postdoctorates in order to increase the population. M = 54; F = 7. Post-docs are shaded in blue in the spreadsheet titled "high performers" and tenure-track hires are in yellow.

<sup>19</sup>We didn't count book reviews as peer-reviewed publications. If we do, the proportion of work attributable to enhanced opportunities falls to 31%.

<sup>20</sup>There are about a third as many as one would expect given that women account for 32.2% of the hires.

<sup>21</sup>Falling to 31% with book reviews.

<sup>22</sup>Falling to 32.8% with book reviews.

<sup>23</sup>Using Jennings' data, we found that the highly productive men (with at least five publications) had an average of 1.98 publications in top journals. Women had an average of 1.14. The median was 1 in both cases.

<sup>24</sup>http://www.apaonline.org/?page=gradguide

<sup>25</sup>http://philjobs.org/appointments/dataFeed

<sup>26</sup>Philjobs http://philjobs.org/appointments

<sup>27</sup>Calculated using a Fisher Test.

89%. Women also made up 26.3% of the market and 31.1% of the tenure-track placements. The 2014 Guide reinforces this pattern, with 35.3% of men and 46.7% of women finding tenure-track employment from 2009 to 2014 meaning the probabilities were about one-third better for women (p = 0.016).<sup>28</sup> Similar to before, 83.6% of men and 87.8% of women found any kind of academic job. Women made up 25.2% of the market and 31% of junior tenure-track hires.

One might wonder if schools with good placement records, and, especially, good records for placing women might be overrepresented in the APA data. However, this concern is not realistic. Consider what it would take for the schools where we didn't have data to close the gender gap. According to the APA, the 2008–2013 period comprised 530 junior tenure-track placements, and yet we would have to suppose an additional 200 competitions went unreported in which a man won every single time—in that case the chances equalize to 50%. There would have to be more than 500 unreported tenure-earning jobs going solely to men for the disproportion to be reversed (i.e., for men to have a 25% greater chance). In such a small profession, there are probably not enough unreported jobs for this to be the case: while Philjobs reported 816 junior tenure-track placements for the same period, many of these are lateral moves that placement officers would not normally pass on to the APA.

Adding to uncertainty about possible unreported hires, one might also wonder if these results would hold up for periods other than 2009–2014, and what the year-to-year results look like. With these concerns in mind we can turn to data provided by Philjobs. This process began by examining the 2014 hiring season, which was arbitrarily defined as spanning July 1, 2014 to June 30, 2015. Over the course of the year information was gathered about individual tenure-track hires, including those who had a previous academic appointment as well as those going to market straight from graduate school. For 2014 it was found that 56 out of 148 hires (37.8%) went to women. While the number of doctorates awarded to women as a percentage of the total doctorates in philosophy fluctuates somewhat from 1 year to the next, it was assumed that the year immediately prior would give a reasonable approximation of how gender is distributed on the job market; in 2013, for example, 27% were awarded to women.<sup>29</sup>

To add more depth to the investigation hiring outcomes for nine further years (2005–2013) were also examined using data provided by the Philjobs website. In order to make this information useable certain corrections and additions to their spreadsheet were necessary, including the elimination of duplicated entries, filtering out senior appointments and nontenure-track hires, spot-checking for accuracy, and using Google searches to ascertain gender where it was missing or in doubt. Next, year-by-year comparisons were made between placement and the distribution of philosophy PhDs using the NSF's Survey of Earned Doctorates. The relationship between awarded PhDs and junior hiring from 2005 to 2014 is depicted in **Figure 6** and gives a general sense of the market. The distribution of philosophy doctorates by gender for the same period is found in **Figure 7**. For some years (2005, 2006, 2008, 2009, 2012) there was

<sup>29</sup>See the 2013 edition of the NSF's Survey of Earned Doctorates.

<sup>28</sup>Fisher Test.

FIGURE 6 | Earned PhDs and TT hiring.

a rough correspondence between the percentage of women who were hired and their share of philosophy doctorates awarded in the year immediately prior. As a further check the rankings for the 2005 market (using the 2001 edition of the Gourmet Report) were consulted, though there were no significant differences in the means (3.00 for men and 3.01 for women) or medians (men: 3.3; women: 3.35) of candidates. For the remaining years (including most recent hiring seasons) women appear to be overrepresented, accounting for 28.4% of the earned doctorates but 35.73% of tenure-track hires (**Figure 8**).<sup>30</sup>

Finally, these results were compared to updates found in the 2016 APDA report. First, my list of successful job candidates for the 2012 season was merged with the APDA's. Although these mostly overlapped, there were some differences. In order to seek greater accuracy every candidate was re-checked, one-byone, in attempts to verify gender and success in a tenure-track competition in 2012 (e.g., by consulting cvs, locating welcome messages at hiring Departments, etc.). Both data sets contained errors resulting in 56 changes to my list (37 additions and 19 deletions) and 36 changes to the APDA's (29 additions and 7 deletions), thus bringing the two into harmony.<sup>31</sup> Though this process was tedious and time-consuming, it was hoped it would maximize the accuracy of the data for at least 1 year and so allow us to see if this additional scrutiny would alter the results

<sup>30</sup>p = 0.000372.

<sup>31</sup>The final tally for 2012 was 140 men and 61 women. Note that there was only one instance where a gender was assigned incorrectly due to a limitation of the software used by the APDA project.

in any significant way. With this revised data it was then a simple task to recalculate the hiring figures. According to my original survey 32.7% of tenure-track hires went to women in 2012 whereas the APDA's 2016 report puts this a little lower at 30.7%. The outcome for the revised and re-verified data is just shy of their result at 30.3%. To place this in context, note that in the previous year 31.3% of doctorates in philosophy went to women. Hence, it can be reaffirmed that the 2012 market outcomes do not attest to a significant gender effect in hiring. However, 2012 was also unusual in light of the pattern for the years 2010, 2011, 2013, and 2014, which might indicate significant bias in favor of female candidates (**Figure 8**). Would this pattern also stand up to further scrutiny? This time instead of more forensic checking of merged data sets, the APDA's numbers were taken at face value with a result in keeping with my original findings provided in **Figure 8**. Going by the APDA's data women obtained 32.5% of the tenure-track jobs in 2013 and 39% in 2014 whereas my results were 35.1% (with 26.7% earning doctorates) and 37.8% (27% earning doctorates). Instead of quibbling about a percentage point here or there, it can be agreed there is no evidence women are underrepresented among those obtaining tenure-track jobs for at least a decade. To the contrary, recent years seem to attest to a reverse gender effect.

# DISCUSSION

Market outcomes starting in 2014 and going back 10 years offer no evidence women are at a disadvantage in tenuretrack competitions. The same can be said for the other objective measures that were examined including publishing and the reputations of home and hiring departments. No statistically significant evidence that pervasive dysfunction in departmental cultures is harming early career market outcomes of budding women philosophers could be found. Meanwhile, the biggest drop in women's participation appears to occur almost immediately, right after first exposure to philosophy's themes, methods, and traditions (Adelberg et al., 2013; Dougherty et al., 2015). Although evidence that the gender gap in philosophy is attributable to pre-university influences has been available since at least 2012 (Paxton et al., 2012) the present study adds to the case against the hypothesis that sexist attitudes (whether conscious or unconscious) held by philosophers are a major cause of disproportion according to gender.

All the same, we can be somewhat reticent to draw strong conclusions about the extent of philosophy's climate problems, and it might be premature to say that there is no systemic antifemale prejudice. Bias that was present but somehow neutralized

# REFERENCES

by measures departments have taken or coping strategies adopted by women might have been overlooked. Then again it seems doubtful that explicit policy changes and coping strategies were adopted more than 10 years ago, long before there was wider awareness of the issue of unconscious bias. It is also conceivable that bias shows up elsewhere, affecting outcomes for tenure and promotion, though keep in mind this conjecture is not supported even by mainstays of the implicit bias literature, such as Steinpreis et al. (1999) whose name-swapping experiments found "no main effects" for tenurability. The present findings are a better fit with the strong preference for women in STEM found by experimental manipulations (Williams and Ceci, 2015).

While counter thoughts are not to be dismissed lightly, the hypothesis that unconscious bias works against women in hiring and early career publishing is not well supported. Although it is conceivable implicit bias initially reduces perception of a woman's cv. and then "affirmative actors" reverse its impact, this proposal strikes one as overly complicated: why not just assume people are not downgrading the accomplishments of talented women?

The suggestion that there is a shyness effect making bias hard to detect is also hard to square with the evidence about premarket publishing opportunities. Why doesn't bias reveal itself in disparities for special invitations to publish where there are no equity policies or structures, little to no collegial oversight, and it is hard to conceive of coping strategies? We should also worry that efforts to improve the representation of women could even backfire, e.g., if committees adopted blind review of candidates under the dubious assumption that more accomplished women are systematically undervalued.

# AUTHOR CONTRIBUTIONS

The author confirms being the sole contributor of this work and approved it for publication.

# ACKNOWLEDGMENTS

The author is indebted to the referees, Calvin K. Lai, Shen-yi Liao, Paul Draper, Neb Kujundzic, Matthew Mosdell, Monika Piotrowska, and Louis-Philippe Hodgson, as well as audiences at the Atlantic Region Philosophers Association, the University of Louisville, and the University of Miami for their insightful feedback and suggestions.

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 Allen-Hermanson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# APPENDIX

Raw data is available at genderandphilosophy.blogspot.com

# Are recent cohorts of women with engineering bachelors less likely to stay in engineering?

Shulamit Kahn<sup>1</sup> \* and Donna K. Ginther <sup>2</sup>

<sup>1</sup> Markets, Public Policy and Law Department, Questrom School of Business, Boston University, Boston, MA, USA, <sup>2</sup> Department of Economics and Center for Science, Technology and Economic Policy, University of Kansas, Lawrence, KS, USA

Women are an increasing percentage of Bachelors in Engineering (BSEs) graduates—rising from 1% in 1970 to 20% in the 2000s—encouraged by increasing K-12 emphasis on attracting girls to STEM and efforts to incorporate engineering and technology into K-12 curricula. Retention of women in STEM and in engineering in particular has been a concern historically. In this paper, we investigate whether this gap has increased because a larger proportion of females entering engineering find themselves ill-matched to this field, or whether the gap has decreased as engineering becomes more accommodating to women. Using 1993–2010 nationally representative NSF SESTAT surveys, we compare cohorts of BSEs at the same early-career stages (from 1–2 to 7–8 years post-bachelors). We find no evidence of a time trend in the gender gap in retention in engineering and a slightly decreasing gender gap in leaving the labor force. We find, as others have, that the majority of the gender retention gap is due to women leaving the labor force entirely and that this exit is highly correlated with child-bearing; yet women with engineering majors are half as likely as all college-educated women to leave the labor market. There are no clear time trends in female BSEs leaving the labor market. Single childless women are actually more likely than men to remain in engineering jobs. Some of the gender differences in retention we find are caused by differences in race and engineering subfield. With controls for these, there is no gender retention difference by 7–8 years post-bachelors for those full-time employed. There were two unusual cohorts—women with 1991–1994 BSEs were particularly likely to remain in engineering and women with 1998–2001 BSEs were particularly likely to leave engineering, compared to men. Cohorts before and after these revert toward the mean, indicating no time trend. Also, women who leave engineering are just as likely as men to stay in math-intensive STEM jobs.

Keywords: engineering careers, gender, leaving STEM, women engineers, retention

# Introduction

Engineering has been and continues to be a field dominated by men. However, the percentage of women getting bachelors in engineering (BSE) has grown dramatically over the decades, from approximately from 1% in 1970 to 10% in 1980, 15% in 1990 and stabilizing near 20% in the 2000s (NSF WebCASPAR). This has been a period of consciousness-raising

#### Edited by:

Jessica S. Horst, University of Sussex, UK

#### Reviewed by:

Beth Livingston, Cornell University, USA Katherine Michelmore, University of Michigan, USA

#### \*Correspondence:

Shulamit Kahn, Markets, Public Policy and Law Department, Questrom School of Business, Boston University, 595 Commonwealth Avenue, Boston, MA 02215, USA<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

Received: 14 April 2015 Accepted: 23 July 2015 Published: 19 August 2015

#### Citation:

Kahn S and Ginther DK (2015) Are recent cohorts of women with engineering bachelors less likely to stay in engineering? Front. Psychol. 6:1144. doi: 10.3389/fpsyg.2015.01144 about the paucity of women in STEM fields, of rising math test scores among K-12 girls, of more girls taking high school math and science courses, and of women increasing their general college attendance relative to boys (Ceci et al., 2014). **Figure 1** illustrates the growth in representation of females among BSE and in other STEM fields.

There has been considerable interest and research on women's retention in STEM in general, and in engineering in particular. Most recently, the National Academy of Engineering and National Research Council (National Academy of Engineering and National Research Council, 2014) convened a workshop on this topic. Women working in the engineering profession, represented by the Society of Women Engineers (SWE), have been very active in surveying women in their field to understand women's greater exit rates. In addition to the Society of Women Engineers (2009) and the National Academy of Engineering and National Research Council (2014) studies, Morgan (2000); Hunt (2010), and Singh et al. (2013) addressed women's exit from engineering particularly, while work such as Preston (1994, 2004), Xie and Shauman (2003), and Xu (2008) addressed exit more generally in all STEM fields.

Previous work on women's retention in engineering was primarily based on cross-sectional data which combines people from many different cohorts (which we identify here by the year of their bachelor's degree in engineering). Measuring retention at different career stages in a cross-section actually combines differences across career stages and differences across cohorts. For instance, in a 2010 cross-section, the only people who would be observed 1 year from their bachelor's degree are the millennials who graduated in 2009, and the only ones who would be observed at 20 years from their bachelors are the Gen X'ers who graduated in 1990.

There are reasons to believe that recent cohorts of engineering majors may behave differently than earlier cohorts did when they were the same age. On the one hand, we might expect later cohorts of women to be more likely to remain in the field because of women's increasing representation among engineering graduates. Hunt (2010) has shown that scientific fields of study with lower female percentages tend to have higher exit rates of women from the field.

On the other hand, we might expect that later cohorts of women engineering majors will be less likely to remain in the field than earlier cohorts. Women might be majoring in engineering in greater numbers because high school curricula have increasingly included engineering and computer education and educators have been encouraged to attract women to engineering (Carr et al., 2012). It may be that some of the women choosing engineering majors today might be less wellmatched to the occupation and not find working in engineering satisfying. Therefore, a larger proportion of later cohorts of engineering BSE women may leave engineering after they have spent a few years working in non-engineering fields. In a similar vein, the recent National Academies conference report indicates that excessive workloads, unclear expectations, lack of work-life balance, and a "chilly climate" were associated with women leaving engineering (National Academy of Engineering and National Research Council, 2014). If it is the case that recent cohorts of BSE women are less well-matched to the engineering occupation, these climate issues may increase

the propensity of women in more recent cohorts to leave engineering.

These possibilities suggest that we should compare different cohorts of BSE, particularly during the first years after they graduate. We compare whether recent cohorts of women with a BSE leave the engineering field with greater or lesser frequency than previous cohorts. We also test whether there is a general time trend in gender retention differences over the last few decades. Along with this, we might expect that those women who leave engineering might move to non-math-intensive occupations with greater proportions of women.

We test these hypotheses using NSF longitudinal SESTAT data that allow us to study cohorts as recent as 2009 bachelors in engineering (BSE) and as early as those with BSEs in 1985. We use data from eight different waves of the same survey spread over 18 years (1993–2010), allowing us to tease apart differences across cohorts from differences in retention that occur as careers develop, and to further to identify whether the career pattern is different across the cohorts. Moreover, given the panel nature of these surveys, we can follow specific individuals longitudinally for periods as long as 8 years which gives us a better sense of the timing of exit.

# Previous Research

Preston (1994, 2004), Xie and Shauman (2003), Xu (2008), and Glass et al. (2013) have studied women's exit from science and engineering as a whole using a variety of national data sources. Preston found large differences in the 1980s and early 1990s. Using data from the 70s, 80s, and early 90s, Xie and Shauman found that women with bachelors in STEM (excluding social sciences) are about one quarter less likely than men to work in STEM occupations and that married women with children are the most affected. Xu (2008), using the 1999 National Survey of Postsecondary Faculty, found that women and men were equally likely to seek to leave STEM academic careers but that women had greater intentions to seek another position within academia. Glass et al. (2013) followed female college graduates from the National Longitudinal Survey of Youth 1979 and found that women in STEM occupations were more likely to leave their field early in their career compared with women in other professional occupations. They find that women in STEM occupations move to non-STEM occupations at very high rates and attribute women's departure from STEM careers to climate issues or job matching.

Research on gender differences in retention in engineering specifically are most germane to this paper. The Society of Women Engineers (2009) surveyed engineering alumni of 21 colleges from 1985 and later. In their 2005 cross section of graduates from these 21 schools whose BSE was their highest degree, there was an average 10% gender gap in the likelihood of working in engineering. Further, they found that 90% of this gender gap was a result of women leaving the labor force entirely. These gender differences were similar to those from the more nationally representative 2003 NSF SESTAT, although overall their retention rates were higher than those in SESTAT.

Morgan (2000) used the 1993 National Survey of College Graduates (NSCG) and captured employment of those who received BSEs between 1965 and 1989 but measured the gap only for those with highest degrees in engineering (i.e., only those who did not choose immediately post-bachelors to enter into a different field via a degree). As such, her estimate of exit is likely to be lower than ours. She found a 3 percentage point (ppt.) gender gap in the likelihood that full-time workers with highest degrees in engineering were employed in engineering jobs, defined using a survey question asking whether respondents were working in a field closely or somewhat related to their field of highest degree. In contrast, women in other fields were 6 ppt. more likely than men to remain in the field of their highest degree. She also found these women were 9 ppt. more likely than men to be out of the labor force and 7 ppt. more likely to be working part-time.

Hunt (2010) also uses the NSCG, but from both the 1993 and 2003 surveys. Like Morgan, she studied those with highest degrees in engineering and based her analysis on the question of how closely their job related to the field of highest degree. Hunt found about a 10% average gender difference in overall retention<sup>1</sup> , of which 70% could be accounted for by women leaving the labor force (similar to Morgan's 3% gender gap among full-time workers). Also like Morgan (2000), Hunt found that the gender differences in engineering were slightly larger than gender differences in other sciences or in non-STEM fields. Unlike Morgan (2000) and Society of Women Engineers (2009), Hunt estimated gender differences with regression models allowing her to control for field, age, degree level, and race among other factors. Holding these constant, women who studied engineering were slightly more likely than women in other fields to be working (about 1 ppt.) but considerably less likely than women in other fields to have a job related to her highest degree (on the order of 5 ppt. of those working or about 4 ppt. of those irrespective of whether they worked). Finally, Hunt finds that including the male share of the field in the regression model that estimates female exit more-than-explains the lower female retention of women in engineering compared to other non-STEM fields.

The only research using longitudinal data to examine retention in engineering was Greenfield's presentation in National Academy of Engineering and National Research Council (2014), which used data from the Department of Education's Baccalaureate and Beyond. She primarily analyzed the 1992–1993 BSE cohort whose sample was small (560, with 80 women). She measured retention as working in an engineering or architecture job. She found that retention rates for employed women engineering BSEs were higher than those of men's in engineering—13.7 ppt. higher after 1 year, 14.8 ppt. higher than men after 4 years, and 6.8 ppt. higher after 10 years. The retention rate of women in engineering was not lower than other fields at 4 years, but was substantially lower at 10 years. She also looked at 1-year retention rates across several later cohorts and found

<sup>1</sup>This number is computed from Hunt's figures although she herself did not make this calculation.

that later cohorts of women were less likely to stay in engineering immediately after receiving their bachelors.

A final relevant finding in Hunt (2010) is that the share of men in the specific sub-field of STEM study was positively highly correlated with women's exit from science (r = 0.51) She finds that including the male share of the field in a regression of female exit more-than-explains the lower female retention of women in engineering compared to other non-STEM fields.

Thus, all of these studies find gender differences in retention in engineering that are small relative to the percentages who stay in engineering, contradicting the general impression of much higher exit rates from engineering (e.g., see Singh et al., 2013). One (National Academy of Engineering and National Research Council, 2014) even found women more likely to remain in engineering.

# Materials and Methods

SESTAT is collected by the National Science Foundation (NSF) and is the most comprehensive database on the employment, educational, and demographic characteristics of U.S. scientists and engineers available. SESTAT actually includes observations from three NSF surveys: the National Survey of Recent College Graduates (NSRCG), the National Survey of College Graduates (NSCG) and the Survey of Doctorate Recipients (SDR). From the NSCG respondents, SESTAT includes only those who received a degree in STEM or had ever worked in a STEM occupation. From the NSRCG, SESTAT includes recent bachelor's and master's degree recipients in STEM fields. The SDR samples US-awarded PhDs in STEM disciplines.

Within each decade, SESTAT followed individuals through the different waves, adding new people to represent more recent graduates (from the NSRCG). The 1990s panel includes 4 waves: 1993, 1995, 1997, and 1999. The 2000s panel includes 4 waves: 2003, 2006, 2008, and 2010. SESTAT thus includes as many as four observations on a single individual over a 7 or 8 year span in each decade (although for various reasons many people are seen for fewer than four surveys<sup>2</sup> ). Note that there are primarily 2-year gaps between survey waves, although there is one 4-year and one 3-year gap.

SESTAT collects information on education, employment including labor force status, occupation, employer characteristics, work activities, and comprehensive demographic information on gender, race/ethnicity, marital status, children, citizenship, and immigration status.

The measurement of who is working as an engineer is not straightforward. In the majority of this analysis, we define people as working in engineering if their primary occupation is categorized by the NSF as engineering. This excludes all jobs categorized as computer and information scientists, such as computer system analysts. Moreover, it excludes jobs categorized as being engineering-related, such as "electrical, electronic, industrial, and mechanical technologists and technicians" or architects. Based on the 2010 SESTAT, we calculate that 1.73 million people were employed full-time in engineering jobs, 2.31 million in computer jobs, and 0.46 million in engineering-related jobs. Beginning in 2003, SESTAT began including low to midlevel "engineering managers" within engineering occupations, but not "top level managers, executives, and administrators." "Engineering managers" (or manageers, a term we have coined) represented 15.6% of the 1.73 million full-time engineering jobs in 2010. Because we want to compare cohorts working in the 1990s as well as the 2000s, we exclude engineering managers in our analysis of engineering retention across cohorts. That said, we also analyze whether BSEs moved into management jobs and if so, whether the job was required technical STEM education.

We use the SESTAT data to examine gender differences in remaining in engineering by cohort and years since degree. Our cohort analysis is based on the 28,117 individuals in SESTAT surveyed who received their first bachelor's degree in engineering (BSE)<sup>3</sup> between 1985 and 2009. For ease of presentation, we divide cohorts into approximately 3- to 5-year BSE groupings starting with the 1985–1990 cohort and ending with the 2006– 2009 cohort, choosing endpoints so each cohort has enough observations to create reasonably accurate statistics. Individuals in the analysis were observed in a SESTAT survey at either 1– 2 years, 3–4 years, and/or 7–8 years post-BSE. We also examine outcomes for people working 15–16 years after the degree, but the number of women in this older cohort is small.

We begin our cohort analysis using descriptive statistics to examine gender differences in remaining in engineering by years since PhD for the outcomes of (1) being "engaged in engineering," defined as working in an engineering occupation or enrolled in an advanced engineering degree program<sup>4</sup> ; (2) working fulltime in an engineering occupation for the subsample that is employed 35 or more hours per week; and (3) being out of the labor force—defined as not working and not looking for work. We then use linear probability regressions to estimate gender differences in these same outcomes, controlling for things that might be responsible for gender differences but that are not directly attributable to gender per se, including engineering subfield, survey year, immigrant status, race, and one measure of socioeconomic class, whether the parent had graduated college. We present the coefficient on gender from these models in order to examine differences in remaining in engineering across cohorts. We then take a closer look at factors associated with leaving the labor force by adding interaction terms to our linear probability models, specifically interaction terms for female X cohort X family-status. Finally, for those who leave engineering, we examine where they go—to engineering related, other mathematically intensive STEM, non-mathematical STEM, or non-STEM occupations.

<sup>2</sup>This includes: adding new cohorts; adding others if needed to balance others who had dropped out of the survey; non-response for one wave (people were dropped if they did not respond for 2 waves); aging out at age 75 etc.

<sup>3</sup>We limit this analysis to first bachelors because we are interested in those who originally chose engineering as a field in college, not those who came to it later. Also, those for whom the engineering BS is not their first bachelors degree may be at a different career stage. The vast majority of BSEs are first bachelors.

<sup>4</sup>After a handful of years from the BSE when some complete a masters, there is no distinction between engaged in and working in engineering.

Stata 13 was used for all statistical analysis including the linear probability multiple regression models. The paper only includes those results related to gender differences. Full regression results for all regression tables are available in the Supplementary Material.

# Results

# Average Gender Differences in Retention Post-bachelors

#### 2010 Averages

**Figure 2** shows the proportion of women and men, respectively with BSEs who in 2010 are "engaged in engineering" graphed by years since the BSE. We use 3-year moving averages because of the erratic periodicity of SESTAT surveys and the small number of females at each point. **Figure 2** demonstrates the starting point of this paper, that in the 2010 cross-sectional data, after a few years post-BSE a gap appears and women with BSEs become less likely to be working in engineering jobs than men. The average gender difference in remaining in engineering (for those within 30 years of the BSE) is 7.8 percentage points (or ppt.) At 10 years post-bachelors, the gender difference is 8.2 ppt.; at 20 years, it is 15.5 ppt. and at 30 years, it is 10.4 ppt. We note, however, that the sample size of women engineers who in 2010 were more than 18 years post-BSE is very small (<100 individuals per year), so the right-hand side of the graph must be considered only suggestive.

Some of the gender difference in engineering retention may simply be due to the fact that more women than men are not working at all (either unemployed or out of the labor force) or working part-time. Among those in the 2010 SESTAT within 30 years of their BSE, 19.2% of women but only 5.6% of men were not working, a difference of 13.6 ppt. The 2010 percentage of women not working among BSEs is similar to the 20.0% not working in 2010 among all US women with a bachelors or higher<sup>5</sup> .

Moreover, rather than leave the labor force, some people instead choose to work part-time. In 2010, 5.7% of those with

<sup>5</sup>Also within 30 years of their bachelors. Calculated by the authors from the Bureau of the Census's American Community Survey.

BSEs in engineering (within the past 30 years) worked part-time. There is a large gender difference in the likelihood of working part time (as would be expected if women are the primary childcaregivers): 12.7% of women with BSEs but only 4.1% of men were working part-time.

Two facts suggest that there are fewer part-time jobs available within engineering than are desired by BSEs. First, 32.4% of women with BSEs who worked part-time were in engineering jobs compared to 38.5% of women with BSEs who worked fulltime. Second, only 5.7% of all those with a BSE work part-time, much less than the 14.4% working part-time of those with nonengineering STEM bachelors. This suggests that if a person with a BSE wants to work part-time, she/he is much more likely to be forced to work outside of engineering. This paucity of parttime jobs within engineering may be due to choices made by employers insensitive to women's flexibility needs, a point we discuss in the conclusion.

Including only those BSE's working full-time eliminates 32.4% of female BSEs compared to 10.3% of male BSEs. The average gender difference in remaining in engineering among full-timeworking BSEs (2010, first 30 years) is 1.6 ppt., much less than the 7.8 ppt. average for the entire population.

**Figure 3** includes only those BSEs who are working full-time and graphs the percent in engineering for men and women separately. We see that in the 15 years after their undergraduate diploma, on average men and women are equally likely to remain in engineering, with periods when women are more likely than men to do so. Beyond 15 years post-BSE, however, men are consistently more likely to remain in engineering, with the gap fluctuating considerably due to even smaller sample sizes of full-time working women than in **Figure 2**.

#### 1993–2010 Averages

As noted earlier, using a single SESTAT year (2010) confuses cohort and career stage differences. Instead, we use the data from all 8 SESTAT waves from 1993 to 2010 to measure the gender retention gap at three different early career stages (measured by years from BSE): 1–2 years after their bachelors, 3–4 years after their bachelors, and 7–8 years after their bachelors. We use 2-year career-stage spans because in most cases, SESTAT surveys were

administered every 2 years (We also do limited analyses for the stage 9–16 years post-BSE).

**Table 1** gives the average probability that men and women remain in engineering (either working or getting higher degrees) at the three different career stages averaging over individuals in the sample observed at this career stage. Before we discuss cohort-specific gender retention, we first describe this average retention at each career stage using both descriptive statistics (**Table 1**) and regression analysis (**Table 2**).

The first row of **Table 1** tells us that 61% of both male and female BSEs enter an engineering job (or schooling) in the 1–2 years immediately after graduating with a BSE, 39% do not. There is no (significant) gender difference. By 3–4 years post-BSE, a gender difference had appeared, where women were 3.6 percentage points (ppt.) less likely than men to remain in engineering; and by 7–8 years, this gender difference had widened to 8.3 ppt. Columns 4 through 6 include only those working full time. Since women are more likely than men to leave the labor force as well as more likely to work part-time, excluding these two groups from the population (as well as the unemployed<sup>6</sup> ) changes

<sup>6</sup>Unemployment rates of BSE engineers are similar for men and women.

the gender difference considerably at all career stages. At 1–2 years, those women working full-time were significantly more likely than men (3.1 ppt.) to remain in engineering on average; at 3–4 years men and women were insignificantly different; and only by 7–8 years were women less likely to remain in engineering, with a significant gender difference of 3.0 ppt.

The last three columns confirm that at each career stage, on average females are more likely than men to be out of the labor force completely, but that the main movement out of the labor force occurs between 4 and 8 years of the BSE.

#### Regression Analyses of Average Retention

**Table 2** uses linear probability regressions to calculate these same measures at the same three career stages, controlling for engineering subfield, survey year, immigrant status, race, and one measure of socioeconomic class, whether the parent had graduated college.