Research on how discrimination lawsuits affect corporate diversity has yielded mixed results. Qualitative studies highlight the limited efficacy of lawsuits in the typical workplace, finding that litigation frequently elicits resistance and even retribution from employers. But quantitative studies find that lawsuits can increase workforce diversity. This article develops an account of managerial resistance and firm visibility to reconcile these divergent findings. First, we synthesize job autonomy and group conflict theories to account for resistance that occurs when dominant groups perceive non-dominant groups to be attempting to usurp managerial authority, in this case through litigation. Second, we integrate insights from organizational institutionalism, which suggests that highly visible firms seek to demonstrate compliance with legal and societal norms. Drawing on this theory, we predict that only large, visible firms will see increases in diversity following lawsuits, and, by the same token, that the most visible workplaces of those large firms, their headquarters, will see the greatest changes. We test our hypotheses with data on litigation and workforce composition from a diverse set of 632 firms that were sued by the EEOC between 1997 and 2006. This study shows that understanding the consequences of lawsuits across firms, and across organizations within them, is key to tackling workplace discrimination.

Certain subpopulations like female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have higher prevalence of HIV/AIDS and are difficult to map directly due to stigma, discrimination, and criminalization. Fine-scale mapping of those populations contributes to the progress toward reducing the inequalities and ending the AIDS epidemic. In 2016 and 2017, the PLACE surveys were conducted at 3290 venues in 20 out of the total 28 districts in Malawi to estimate the FSW sizes. These venues represent a presence-only dataset where, instead of knowing both where people live and do not live (presence–absence data), only information about visited locations is available. In this study, we develop a Bayesian model for presence-only data and utilize the PLACE data to estimate the FSW size and uncertainty interval at a 1.5×1.5-km resolution for all of Malawi. The estimates can also be aggregated to any desirable level (city/district/region) for implementing targeted HIV prevention and treatment programs in FSW communities, which have been successful in lowering the incidence of HIV and other sexually transmitted infections.