Job Type, Religion, and Muslim Gender as Predictors of Discrimination in Employment Settings
Bibliographic record
Abstract
Most employment discrimination research has focused on race and gender. The relatively fewer papers dealing with religion suggests that discrimination exists. We extend the literature by examining the effects of job type (public safety/non-public safety), religion (Muslim/non-Muslim) and Muslim gender on selection decisions. Participants ranked applicants and made judgments on trust and whether to interview applicants after evaluating seven resumes for either a shipping clerk or a security guard position. Participants rated Muslim applicants lower than non-Muslim applicants for the security guard position. We found no evidence of discrimination in the shipping clerk position. Perceived trust may be a possible explanation for some of the decisions people made. We also found that the Muslim female candidate was rated higher than the Muslim male candidate for the security guard position; no gender differences existed for the shipping clerk position. Our findings are consistent with the gender discrimination literature in that job type affected the extent to which religious-based discrimination occurred and the intersectionality literature/models specifying that combinations of demographics can impact judgments. One implication is the need to incorporate religion in discrimination interventions.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".