When Interpretations of Merit Thresholds Vary and Reproduce Inequality: Entering the Tech Industry Without Computer Science Credentials
研究没有计算机科学学位的求职者如何解读科技行业的技能门槛，发现不同群体采取不同策略，导致就业结果不平等，尤其对弱势群体不利。
Meritocracy is widely believed to be a fair system. Although extant literature focuses on managers’ implementation of meritocratic decisions, less attention has been paid to jobseekers’ responses to meritocratic opportunities. This study addresses this gap by examining how aspiring software developers without computer science (CS) degrees respond to the ostensibly meritocratic promise of entering tech through open-access coding skills. Drawing on interview, social media, and ethnographic data, I find that although all aspirants agreed coding skills were the key meritocratic criteria for entering tech without CS degrees, they interpreted the merit threshold (the level of coding competency needed to get their first job) differently and adopted three distinct entry strategies that varied in timing and scope—Early/Broad, Standard, and Late/Narrow. Follow-up data collected three years later revealed that one strategy (Early/Broad) was associated with high employment rates across all subgroups of aspirants and substantially increased employment chances for those historically underrepresented in tech. Yet, most did not opt for it. Indeed, only one group (White men with white-collar/professional backgrounds) clustered in strategies with higher employment rates, resulting in this population securing jobs at a higher rate than others. To explain the variation in merit thresholds and accompanying entry strategies, this study highlights aspirants’ previous encounters with demand-side actors—particularly, their perceptions of whether, and to what extent, employers had previously been willing to give them a chance. These findings contribute to research on meritocracy and labor markets and offer insights into building a more diverse workforce. Funding: This work was supported by the American Sociological Association Doctoral Dissertation Research Improvement [Grant 55209764] and the Washington Center for Equitable Growth [Grant 5510223]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.17752 .