Critical Context Theory
The effect of the 2016 United States presidential election on employment discrimination
Marina Mileo Gorzig & Deborah Rho
Journal of Population Economics, January 2022, Pages 45–88
Abstract:
We examine whether employment discrimination increased after the 2016 presidential election in the United States. We submitted fictitious applications to publicly advertised positions using resumes that are manipulated on perceived race and ethnicity (Somali American, African American, and white American). Prior to the 2016 election, employers contacted Somali American applicants slightly less than white applicants but more than African American applicants. After the election, the difference between white and Somali American applicants increased by 8 percentage points. The increased discrimination predominantly occurred in occupations involving interaction with customers. We continued data collection from July 2017 to March 2018 to test for seasonality in discrimination; there was no substantial increase in discrimination after the 2017 local election.
“Potential” and the Gender Promotion Gap
Alan Benson, Danielle Li & Kelly Shue
MIT Working Paper, October 2021
Abstract:
We show that widely-used subjective assessments of employee “potential” contribute to gender gaps in promotion and pay. Using data on 30,000 management-track employees from a large retail chain, we find that women receive substantially lower potential ratings despite receiving higher job performance ratings. Differences in potential ratings account for 30-50% of the gender promotion gap. Women’s lower potential ratings do not appear to be based on accurate forecasts of future performance: women outperform male colleagues with the same potential ratings, both on average and on the margin of promotion. Yet, even when women outperform their previously forecasted potential, their subsequent potential ratings remain low, suggesting that firms persistently underestimate the potential of their female employees.
Hidden Performance: Salary History Bans and Gender Pay Gap
Jesse Davis, Paige Ouimet & Xinxin Wang
University of North Carolina Working Paper, September 2021
Abstract:
As of 2019, salary history bans have been enacted by 17 states and Puerto Rico with the stated purpose of reducing the gender pay gap. We argue that salary history bans may negatively affect wages as employers lose an informative signal of worker productivity. We empirically evaluate these laws using a large panel dataset of disaggregated wages covering all public sector employees in 36 states and find, on average, salary history bans lead to a 3% decrease in new hire wages. We find no decrease in the gender pay gap in the full sample and a modest 1.5% increase in the relative wages of women, as compared to men, among new hires most likely to have experienced gender discrimination historically.
Salary History and Employer Demand: Evidence from a Two-Sided Audit
Amanda Agan, Bo Cowgill & Laura Gee
NBER Working Paper, November 2021
Abstract:
We study how salary history disclosures affect employer demand by using a novel, two-sided field experiment featuring hundreds of recruiters reviewing over 2000 job applications. We randomize the presence of salary history questions as well as candidates' disclosures. We find that employers make negative inferences about non-disclosing candidates, and view salary history as a stronger signal about competing options than worker quality. Disclosures by men (and other highly-paid candidates) yield higher salary offers, however they are negative signals of value (net of salary), and thus yield fewer callbacks. Male wage premiums are regarded as a weaker signal of quality than other sources (such as the premiums from working at higher paying firms, or being well-paid compared to peers). Recruiters correctly anticipate that women are less likely to disclose salary history at any level, and punish women less than men for silence. In our simulation of bans, we find no evidence that bans affect the gender ratio of callback choices, but find large reductions in gender inequality in salary offers among candidates called back. However, salary offers are lower overall (especially for men). A theoretical framework shows how these effects may differ by key properties of labor markets.
Extension request avoidance predicts greater time stress among women
Ashley Whillans et al.
Proceedings of the National Academy of Sciences, 9 November 2021
Abstract:
In nine studies using archival data, surveys, and experiments, we identify a factor that predicts gender differences in time stress and burnout. Across academic and professional settings, women are less likely to ask for more time when working under adjustable deadlines (studies 1 to 4a). Women’s discomfort in asking for more time on adjustable deadlines uniquely predicts time stress and burnout, controlling for marital status, industry, tenure, and delegation preferences (study 1). Women are less likely to ask for more time to complete their tasks because they hold stronger beliefs that they will be penalized for these requests and worry more about burdening others (studies 1 to 2d). We find no evidence that women are judged more harshly than men (study 3). We also document a simple organizational intervention: formal processes for requesting deadline extensions reduce gender differences in asking for more time (studies 4a to 5).
“Un”Fair Machine Learning Algorithms
Runshan Fu et al.
Management Science, forthcoming
Abstract:
Ensuring fairness in algorithmic decision making is a crucial policy issue. Current legislation ensures fairness by barring algorithm designers from using demographic information in their decision making. As a result, to be legally compliant, the algorithms need to ensure equal treatment. However, in many cases, ensuring equal treatment leads to disparate impact particularly when there are differences among groups based on demographic classes. In response, several “fair” machine learning (ML) algorithms that require impact parity (e.g., equal opportunity) at the cost of equal treatment have recently been proposed to adjust for the societal inequalities. Advocates of fair ML propose changing the law to allow the use of protected class-specific decision rules. We show that the proposed fair ML algorithms that require impact parity, while conceptually appealing, can make everyone worse off, including the very class they aim to protect. Compared with the current law, which requires treatment parity, the fair ML algorithms, which require impact parity, limit the benefits of a more accurate algorithm for a firm. As a result, profit maximizing firms could underinvest in learning, that is, improving the accuracy of their machine learning algorithms. We show that the investment in learning decreases when misclassification is costly, which is exactly the case when greater accuracy is otherwise desired. Our paper highlights the importance of considering strategic behavior of stake holders when developing and evaluating fair ML algorithms. Overall, our results indicate that fair ML algorithms that require impact parity, if turned into law, may not be able to deliver some of the anticipated benefits.
Gender, bottom-line mentality, and workplace mistreatment: The roles of gender norm violation and team gender composition
Kenneth Tai et al.
Journal of Applied Psychology, forthcoming
Abstract:
Although gender has been identified as an important antecedent in workplace mistreatment research, empirical research has shown mixed results. Drawing on role congruity theory, we propose an interactive effect of gender and bottom-line mentality on being the target of mistreatment. Across two field studies, our results showed that whereas women experienced more mistreatment when they had higher levels of bottom-line mentality, men experienced more mistreatment when they had lower levels of bottom-line mentality. In another field study, using round-robin survey data, we found that team gender composition influenced the degree to which the adoption of a bottom-line mentality by female team members was perceived to be a gender norm violation, which subsequently predicted their likelihood of being mistreated. Specifically, women who had higher (vs. lower) levels of bottom-line mentality were more likely to be perceived to violate gender norms in teams with a lower proportion of women, and in turn, perceived gender norm violation was positively associated with being mistreated. We discuss theoretical and practical implications of our findings and directions for future research.
Paid Family Leave and Corporate Innovation
Hyuksoon Lim
University of Arizona Working Paper, October 2021
Abstract:
I investigate the effect of labor market frictions for female employees on corporate innovation. Following the implementation of state-level paid family leave acts, which exogenously increase female talent allocation by facilitating labor market participation of female inventors, firms headquartered in affected states show significant increases in their innovation relative to unaffected firms. This effect is stronger for firms in innovative industries, for firms with a skilled workforce, for firms in industries with lower labor mobility, for firms in less competitive local labor markets, and for firms with lower female employment. Overall, my results imply that labor market frictions for working mothers inhibit corporate innovation.
A (Dynamic) Investigation of Stereotypes, Belief-Updating, and Behavior
Katherine Coffman, Paola Ugalde Araya & Basit Zafar
NBER Working Paper, October 2021
Abstract:
Many decisions – such as what educational or career path to pursue – are dynamic in nature, with individuals receiving feedback at one point in time and making decisions later. Using a controlled experiment, with two sessions one week apart, we analyze the dynamic effects of feedback on beliefs about own performance and decision-making across two different domains (verbal skills and math). We find significant gender gaps in beliefs and choices before feedback: men are more optimistic about their performance and more willing to compete than women in both domains, but the gaps are significantly larger in math. Feedback significantly shifts individuals' beliefs and choices. Despite this, we see substantial persistence of gender gaps over time. This is particularly true among the set of individuals who receive negative feedback. We find that, holding fixed performance and decisions before feedback, women update their beliefs and choices more negatively than men do after bad news. Our results highlight the challenges involved in overcoming gender gaps in dynamic settings.
Gender Differences in Advice Giving
Elif Osun
University of Maryland Working Paper, October 2021
Abstract:
I experimentally investigate whether there is a gender difference in advice giving in a gender-neutral task with varying difficulty in which the incentives of the advisor and the decision maker are perfectly aligned. I find that women are more reluctant to give advice compared to men for difficult questions. The gender difference in advice giving cannot be explained by gender differences in performance. Self-confidence explains some of the gender gap, but not all. The gender gap disappears if advice becomes enforceable. I show that gender differences in rejection aversion and propensity to take responsibility are both consistent with the findings.
Workplace Routinization and the Gender Gap in College Enrollment
Amanda Chuan & Weilong Zhang
Michigan State University Working Paper, September 2021
Abstract:
Women used to lag behind but now exceed men in college enrollment. We show that changes in non-college job prospects contributed to these trends. We first document that routine-biased technical change disproportionately displaced non-college occupations held by women. We then show that these lower non-college job prospects for women increase female enrollment using a shift-share instrument for the impact of routinization: a one percentage point decline in the share of routine task intensive jobs leads to a 0.6 percentage point rise in female college enrollment, while the effect for male enrollment is smaller at 0.4 percentage points and not systematically significant. We next embed this instrumental variation into a dynamic model that links education and occupation choices. The model finds that routinization decreased returns in non- college occupations for women, leading them to shift to cognitive work and increasing their college premiums. In contrast, non-college men’s occupations were less susceptible to routinization. Altogether, our model estimates that workplace routinization accounted for 67% of the growth in female enrollment and 31% of the change in male enrollment between 1980 to 2000.
Challenging conclusions about predictive bias against Hispanic test takers in personnel selection
Paul Sackett, Charlene Zhang & Christopher Berry
Journal of Applied Psychology, forthcoming
Abstract:
Berry et al. (2020) noted that predictive bias is a function of three factors: subgroup mean difference on the predictor (dx), subgroup mean difference on the criterion (dy), and test validity (rxy). They used meta-analytic estimates of each of these three to examine predictive bias against Hispanic test takers when cognitive tests are used in personnel selection. They found that tests underpredict Hispanic job performance by an average of .21 SDs, which would call into question the fairness of cognitive test use in personnel selection. We located 119 studies in which all three parameters—dy, dx, and rxy—could be obtained, thus holding sample, setting, and operationalization constant in estimating the three parameters within each study. This produced a substantially different conclusion: We find that tests overpredict Hispanic performance by .04–.20 SDs, depending on assumptions made about artifact corrections. Factors contributing to differences between the two studies include differences in range restriction corrections, sample incomparability, and Berry et al.’s use of rxy estimated from the total sample rather than within the majority subgroup.
When Gender Matters in Scientific Communication: The Role of Generic Language
Jasmine DeJesus, Valerie Umscheid & Susan Gelman
Sex Roles, November 2021, Pages 577–586
Abstract:
Prior research has documented gender differences in self-presentation and self-promotion. For example, a recent analysis of scientific publications in the biomedical sciences reveals that articles with women in lead author positions (first and last) included fewer positive words to describe their results than articles with men in lead author positions. Here we examined the role of gender in peer-reviewed publications in psychology, with a focus on generic language. When authors describe their results using generic statements (e.g., “Introverts and extraverts require different learning environments”), those statements gloss over variability, frame an idea as broad, timeless, and universally true, and have been judged to be more important. In a sample of 1,149 psychology articles published in 2015–16 from 11 journals, we found that women in lead author positions were less likely to employ generic language than men in lead author positions, and that publications with more generic language received more citations (as did publications authored by men). We discuss how a subtle gender difference in self-presentation may have direct consequences for how a scientific finding is interpreted and cited, with potential downstream consequences for career advancement for women and men.
Risqué business? Interpersonal anxiety and humor in the #MeToo era
Jamie Gloor et al.
Journal of Applied Psychology, forthcoming
Abstract:
Interpersonal anxiety (i.e., the fear of negative consequences from interacting with someone) may be more prominent in post-#MeToo organizations when interacting with someone of a different gender. Initial exchanges may particularly trigger this anxiety, obfuscating key organizational decisions such as hiring. Given humor’s positive, intrapersonal stress-reduction effects, we propose that humor also reduces interpersonal anxiety. In three mixed-methods experiments with hiring managers, we examined the effects of applicant and evaluator gender (i.e., same-/mixed-gender dyad), positive applicant humor (i.e., a pun), and context (i.e., gender salience) in job interviews. Results showed that mixed-gender (vs. same-gender) interactions elicited more interpersonal anxiety, particularly when gender was more salient; mixed-gender interactions also predicted downstream attitudinal outcomes (e.g., social attraction and willingness to hire) and hiring decisions (e.g., selection and rejection) via interpersonal anxiety. Although humor reduced interpersonal anxiety and its consequences for female applicants, the opposite was true for male applicants when gender was salient, because it signaled some of the same expectations that initially triggered the interpersonal anxiety: the potential for harmful sexual behavior. In sum, we integrated diversity and humor theories to examine interpersonal anxiety in same- and mixed-gender interactions and then tested the extent to which humor relieved it.
Prosocial option increases women’s entry into competition
Alessandra Cassar & Mary Rigdon
Proceedings of the National Academy of Sciences, 9 November 2021
Abstract:
We provide evidence that women enter competitions at the same rate as men when the incentive for winning includes the option to share part of the rewards with the losers (i.e., when the incentive system is socially oriented). Using an experiment (with N = 238 subjects from three laboratories), we find that about 16% more men than women choose to compete in the standard tournament; this gender gap is eliminated in the socially oriented incentive treatment. While men’s choice to compete remains unchanged, at around 52% in both conditions, women increase their entry rate from 35% in the standard tournament to 60% when the incentive includes a socially oriented option.
What’s in an Occupation? Investigating Within-Occupation Variation and Gender Segregation Using Job Titles and Task Descriptions
Ananda Martin-Caughey
American Sociological Review, October 2021, Pages 960-999
Abstract:
Occupations have long been central to the study of inequality and mobility. However, the occupational categories typical in most U.S. survey data conceal potentially important patterns within occupations. This project uses a novel data source that has not previously been released for analysis: the verbatim text responses provided by respondents to the General Social Survey from 1972 to 2018 when asked about their occupation. These text data allow for an investigation of variation within occupations, in terms of job titles and task descriptions, and the occupation-level factors associated with this variation. I construct an index of occupational similarity based on the average pairwise cosine similarity between job titles and between task descriptions within occupations. Findings indicate substantial variation in the level of similarity across occupations. Occupational prestige, education, and income are associated with less heterogeneity in terms of job titles but slightly more heterogeneity in terms of task descriptions. Gender diversity is associated with more internal heterogeneity in terms of both job titles and task descriptions. In addition, I use the case of gender segregation to demonstrate how occupational categories can conceal the depth and form of stratification.