Bibliographic record
Abstract
Millicent Garrett Fawcett (1847-1929), was one of the leaders of the English women’s suffrage movement. The longest-serving worker in this campaign, she began her participation as a very young member of the first Women’s Suffrage Committee in London which formed in 1867, emerging formally as its leader in 1897, when she became president of the National Union of Women’s Suffrage Societies. She finally retired from this position in 1918, feeling that the movement should now be led by younger women—and that her advanced age entitled her to indulge her hatred of the committee work in which she had been immersed for decades (Strachey, 1931:330). In the light of this, it is not surprising that the memorial to her in Westminster Abbey describes her as having ‘won citizenship for women’ ( Oakley, 1983 :184). But Fawcett was not only a suffragist: she was active as a lobbyist, a lecturer and a propagandist in several other campaigns as well. She worked in the campaign to extend higher education to women, in the battles to gain entry for women to medicine and to the other professions and to prevent the exclusion of women from a number of industrial occupations. She was particularly active in a number of campaigns to prevent the sexual exploitation of women and young girls and to establish an equal moral standard for women and men.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".