Hierarchical Structure and Gender Dissimilarity in American Legal Labor Markets
Why this work is in the frame
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Bibliographic record
Abstract
Research on inequality in the legal profession underemphasizes the macro-level factors that structure legal work. This paper introduces two measures that characterize local legal labor markets. The index of gender dissimilarity is the proportion of women required to move into the private law firm sector from the public sector to create gender balance. The index of hierarchical market structure is defined by a concentration of elite law graduates, highly leveraged law firms, lucrative billings, and corporate clients. Women's salaries increase more rapidly than men's in these markets, yet men continue to out-earn women. Furthermore, HLM models indicate that in labor markets with greater gender dissimilarity, women's wages are significantly depressed. We explain this in terms of mechanisms of opportunity hoarding and exploitation (Tilly 1998).
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 it