Man Up, Man Down: Race–Ethnicity and the Hierarchy of Men in Female-Dominated Work
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
Scholars have largely overlooked the significance of race and socioeconomic status in determining which men traverse gender boundaries into female-dominated, typically devalued, work. Examining the gender composition of the jobs that racial minority men occupy provides critical insights into mechanisms of broader racial disparities in the labor market—in addition to stalled occupational desegregation trends between men and women. Using nationally representative data from the three-year American Community Survey (2010–2012), we examine racial/ethnic and educational differences in which men occupy gender-typed jobs. We find that racial minority men are more likely than white men to occupy female-dominated jobs at all levels of education—except highly educated Asian/Pacific Islander men—and that these patterns are more pronounced at lower levels of education. These findings have implications for broader occupational inequality patterns among men as well as between men and women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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