The Sisyphus Effect: Dynamic Gender Discrimination in the Music Industry

This paper examines gender inequality in popular music using a newly constructed, comprehensive dataset covering the universe of songs that entered the Billboard Hot 100 between 1958 and 2025. By integrating chart histories with artist-level characteristics across multiple sources, the dataset enables dynamic analyses of participation, performance, and survival that were previously infeasible at this scale and horizon. Combining structural break analysis, dynamic participation models, and artists’ performance regressions, we show that non-male representation does not evolve cumulatively but is repeatedly reset at moments of technological and institutional change. Participation rises within regimes but drops sharply at structural transitions, consistent with renewed uncertainty and gatekeeping. Conditional on chart entry, non-male artists systematically over-perform at entry and peak visibility, yet exhibit weaker chart persistence, a pattern strongest in periods of stagnating participation. We interpret these findings as evidence of a Sisyphus Effect in the music industry, whereby higher effective entry thresholds force non-male artists to repeatedly rebuild representation under changing industry conditions. More broadly, the paper highlights conditional over-performance as a general empirical strategy for identifying discrimination in truncated markets when under-representation is observed in-sample.