A trifecta trajectory of moral taint contagion: Women (church) leaders making work dirty
Bibliographic record
Abstract
Abstract This article offers insights into the dynamic and complex nature of moral taint, specifically taint that emanates at the individual level, triggered by gender, and the trajectory of this moral taint at work. Through a qualitative study of women church leaders, it explores how gender might serve as a trigger of moral taint to dirty the work. The women church leaders are perceived to be morally questionable and a source of disgust. Their gender triggers moral taint. This moral taint creates the risk of a reverse trifecta of taint contagion from the women toward the occupation, institution, and stakeholders. Others respond to the women with disgust, deflecting and protecting against contamination. The women leaders perform gendered dirty work in this sacredly masculine context and their leadership privilege is unstable, immoral, and contested because of their gender. We offer a conceptualization of gendered dirty work(ers) and suggest research avenues for women in leadership.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".