Hiring quotas can reshape who enters the workforce and how organizations perform. Such policies are often intended to redress disparities arising from past discrimination. I study a gender quota that instead preserves the representation of a historically dominant group: men in China's civil service. After merit-based hiring boosted women’s share of new recruits, one-third of county tax bureaus introduced one-to-one gender quotas mandating equal hires by sex. Using a new dataset I built through web-scraping and digitizing position-level civil service exam records and county tax revenues, I show that counties with more recent female hires were more likely to adopt quotas, especially in tax-collection roles. Exploiting variation in the timing and intensity of adoption across counties, I use a matched staggered difference-in-differences and event-study framework to show that quotas decrease female representation, lower candidate quality, and reduce worker productivity: tax revenue falls by 4.7%, or about $4 million per county per year. Evidence on mechanisms suggests these effects stem from reduced personnel ability and gendered institutional practices. These findings show that “reverse” affirmative action can be costly when institutions that serve advantaged groups persist.