Gender-Targeted Job Ads in the Recruitment Process: Evidence from China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We document how explicit employer requests for applicants of a particular gender enter the recruitment process on a Chinese job board. We find that 95 percent of callbacks to gendered jobs are of the requested gender; worker self-selection (compliance with employers' requests) and employer callback decisions from applicant pools (enforcement) both contribute to this association, with compliance playing the larger role. Explicit gender requests account for over half of the gender segregation and gender wage gap observed on the board.Ad-level regressions with job title and firm fixed effects suggest that employers' explicit gender requests have causal effects on the gender mix of applications received, especially when the employer's likely gender preference is hard to infer from other contents of the ad. Application-level regressions with job title and worker fixed effects show that both men and women experience a callback penalty when applying to a gender-mismatched job; this penalty is significantly greater for women (44 percent) than men (26 percent).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it