entitled "The PhD in Women's Studies: Implications
Bibliographic record
Abstract
September 11, and amid an anthrax scare that was particularly palpable in Atlanta as the home of the American Center for Disease Control, the Women's Studies PhD conference brought together faculty, recent graduates, and current students from a wide variety of American and Canadian institutions. It was co-sponsored by the National Women's Studies Association and the National Council of Research on Women, and was the first American national gathering specifically about the Women's Studies PhD. 1 Participants came from almost all the universities that currently offer a doctorate in Women's Studies or are developing it.2 In addition, there were faculty members from numerous other universities and colleges that offer M A programs and undergraduate programs in Women's Studies. Canadian voices included Katherine Side, the first
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.
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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.020 | 0.015 |
| Insufficient payload (model declined to judge) | 0.050 | 0.006 |
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".