A field study of the impacts of workplace diversity on the recruitment of minority group members
Bibliographic record
Abstract
Increasing workplace diversity is a common goal. Given research showing that minority applicants anticipate better treatment in diverse workplaces, we ran a field experiment (N = 1,585 applicants, N = 31,928 website visitors) exploring how subtle organizational diversity cues affected applicant behaviour. Potential applicants viewed a company with varying levels of racial/ethnic or gender diversity. There was little evidence that racial/ethnic or gender diversity impacted the demographic composition or quality of the applicant pool. However, fewer applications were submitted to organizations with one form of diversity (that is, racial/ethnic or gender diversity), and more applications were submitted to organizations with only white men employees or employees diverse in race/ethnicity and gender. Finally, exploratory analyses found that female applicants were rated as more qualified than male applicants. Presenting a more diverse workforce does not guarantee more minority applicants, and organizations seeking to recruit minority applicants may need stronger displays of commitments to diversity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".