Friday, October 13, 2017

As Law School Hiring Season Begins, a Look at Gender Bias in the Academy

As hiring season in U.S. law schools is upon us, a few posts today on gender bias in the academy.

Virginia Valia, Beyond Gender Schemas: Improving the Advancement of Women in Academia, 20 Hypatia 198 (2005):

The statistics on women in academia are well documented and summarized in a number of places.

The generality and ubiquity of the problem shows the necessity for a general explanation. Since the phenomena are not confined to a single profession, we need to understand what underlies them. The explanation I focus on is social cognitive; it examines the moment-by-moment perceptions and judgments that disadvantage women. The social-cognitive account relies on two key concepts: gender schemas and the accumulation of advantage. Very briefly: the gender schemas that we all share result in our overrating men and underrating women in professional settings, only in small, barely visible ways: those small disparities accumulate over time to provide men with more advantages than women.

Constance Wagner, Change from Within: Using Task Forces and Best Practices to Achieve Gender Equity, 47 Journal of Legal Education (forthcoming).

This article focuses on the search for gender equity among women faculty in the university setting in the United States. The author advocates for the use of university task forces and the institutionalization of best practices for achieving gender equity as means to remove the persistent barriers to professional advancement experienced by many women faculty. Discriminatory treatment of faculty based on gender may be hidden and remain unacknowledged in some universities, so the process of uncovering such treatment and formulating recommendations for change is an important first step in the process of creating a work environment that is both fair and inviting to women. Many universities have achieved positive outcomes for faculty using this approach, which has the potential to benefit a wider group of women faculty in a more targeted fashion than a strategy that relies on the use of litigation and government agency proceedings. This article documents the disparities in employment status experienced by women faculty in U.S. universities compared to their male counterparts through the use of statistically based gender equity indicators, explores explanations for the existence of such inequities and proposes reasons for their elimination, develops a model framework for the structure and process to be used by a successful gender equity task force, and identifies best practices that have the greatest potential to advance the status of women university faculty. The author draws upon case studies of successful task forces at several U.S. universities, the work of professional organizations representing university faculty and administrators, and the academic literature on the employment status of women faculty in the United States.

This piece contributes to the literature on employment discrimination based on gender in the United States in a novel way by approaching the topic from the perspective of mechanisms for institutional change rather than from a litigation perspective. It fills a gap in the literature by exploring the topic of gender inequity among university faculty from a strategic perspective by drawing on the work of successful task forces and emerging best practices that show promise to improve the status of university women faculty.

Gender Bias in Academe: An Annotated Bibliography:

Studies of the hard data of gender bias—in an era of hard data—should be required reading of all administrators and all faculty who are called upon to make decisions about hiring, tenure, and promotion based on purely quantitative measures such as “productivity” or “citation counts.”  An adage of data scientists is “garbage in, garbage out.” That means if the sample or the data is corrupt or biased when it is first entered, then any conclusions based on mining or crunching that data must be regarded with keen skepticism. You cannot simply count the end product (such as number of articles accepted, reviewed, awarded prizes, or cited) without understanding the implicit bias that pervades the original selection process and all the subsequent choices on the way to such rewards.


Book Review, Deborah Rhode, Women and Leadership, 8 ConLawNOW 1 (2017).

Education, Equal Employment, Gender | Permalink


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