We study the effect of hearing cases alongside female judicial colleagues on the probability that a federal judge hires a female law clerk. Federal judges are assigned to judicial panels at random and have few limitations on their choices of clerks. Using a unique dataset of federal case records merged with judicial hiring information, we find a significant effect of the fraction of copanelists who are female on a male judge’s likelihood of hiring a female clerk. This finding suggests that increases in the diversity of the upper rungs of a profession can create opportunities at the entry level.

The unprecedented contagion of the SARS-CoV-2 virus, causative of COVID-19, has spawned watershed economic, social, ethical, and political upheaval—catalyzing severe polarization among the global populace. Ostensibly, to demonstrate the most appropriate path towards responding to the virus outbreak, public officials in the United States (“U.S.”), representing both Democratic and Republican parties, stand accused of unduly influencing COVID-19 records in their respective jurisdictions. This study investigates the role political partisanship may have played in decreasing the accuracy of publicly reported COVID-19 data in the U.S. Leveraging social identity theory, we contend that public officials may have manipulated the reporting records in accounting for COVID-19 infection cases and deaths to validate the effectiveness of political party objectives. We employ Benford's Law to assess misreporting and evaluate the integrity of county-level COVID-19 reporting data through the construction of four distinct political party classifications. Specifically, we cross the county voting majority for the 2016 presidential candidate for each U.S. state (Democratic and Republican) with the 2020 gubernatorial political party (Democratic and Republican) in which each county resides. For the sample period of January 21, 2020 through November 3, 2020 (Election Day), the study's results suggest that the reported COVID-19 infection cases and deaths in the U.S. violate Benford's Law in a manner consistent with underreporting. Our analysis reveals that Democratic counties demonstrate the smallest departures from Benford's Law while Republican counties demonstrate the greatest departures.