Women's history month 2018: of arts and politics
Bibliographic record
Abstract
March 8 is globally the International Women’s Day; in some countries it is noted, even celebrated, but it is not a civic holiday in the United States, the United Kingdom, and Australia, unlike the post-Soviet countries of Eurasia where it is a national holiday. In Canada, it corresponds to the celebration of Persons Day on October 18 since 1929. The month of March is the “annual declared” Women’s History Month in the United States, following February as the Black History Month3. Preceded by a decade of Women’s History Weeks, since 1988 the celebration of Women in History in America is accompanied by a Presidential Proclamation and has its own website4. The Wikipedia article, last updated on March 30, 2018, notes that “The Women's Progress Commission will soon conduct hearings to promote interest in preserving areas that are relevant in American women's history.” If 2018 marks a 40-year mark of such highlighting of women’s contributions to history and contemporary society, it has been 55 years since the 1963 federal report produced by the Commission on the Status of Women. That was the first comprehensive federal report on women, and it took until March 2011 for it to be followed by another when the Obama administration released a report on Women in America: Indicators of Social and Economic Well-Being.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.267 | 0.065 |
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".