Not Our Mother's Law School?: A Third-Wave Feminist Study of Women's Experiences in Law School (with Kelly Hradsky, Kristen Jeschke, LaVonne Meyer & Jill Roberts)
Bibliographic record
Abstract
INTRODUCTIONhis article is about a journey and a process as much as it is about a product.In spring 2007, as part of our Gender and the Law class at Chicago-Kent College of Law, we read portions of Lani Guinier"s Becoming Gentlemen: Women, Law School, and Institutional Change, as well as more recent studies regarding women"s experiences in law school.3 Guinier"s book generated strong reactions.Of the twentytwo women in the class, about three-quarters of them deeply related to the sense of alienation that the women law students at the University of Pennsylvania Law School spoke of in Guinier"s work.Many of the Chicago-Kent students commented that they wished they had read the article earlier in their law school careers, as they had assumed their own feelings of alienation, depression, and sinking confidence were individual problems.Importantly, Guinier blamed women law students" problems on the law school as an institution rather than on personal pathologies.Yet, about a quarter of the class strongly felt that they had not experienced discrimination or feelings of alienation in law school and that the sentiments that dissatisfied women law students experienced were shared by all students -men and women.This prompted a number of questions: Had women"s experiences in law school changed since Guinier and her colleagues first undertook their study in 1994?Were women"s experiences at Chicago-Kent different than those at more prestigious schools, especially since 1 The title refers to ASTRID HENRY, NOT MY MOTHER"
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".