Bibliographic record
Abstract
This paper was inspired by the incomplete story of Englishwoman Isabel ‘Jack’ May (1875–1970), a media sensation from 1905 to 1912 because she was a ‘lady farmer’, wore ‘male attire’ and adopted the name ‘Jack’. Already well-known in England, May’s celebrity was enhanced when she purchased land in Alberta, Canada in 1911, where she farmed with a female companion. In late 1912 however, May sailed to England, never to return, and disappeared from public view. In Sarah Carter’s 2016 book Imperial Plots, May’s fate was a mystery, but Carter surmised May did not feel welcome in the Canadian West where gender transgressors were shunned. The authors, inspired by Laite’s ‘small history in a digital age’ methodological approach, discovered a deeper, richer and more complex life history. This paper reconstructs May’s life and analyses the intense media scrutiny which positioned her as an aberration against traditional femininity to understand more about the lives of other non-conforming women of this period. While we argue that May was not transgender, rather living openly as a cross-dressing woman, her self-identification as ‘farmer’ and decision to spend her adult life with same-sex companions, offers an alternative view of trans and queer ‘spaces of possibility’.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".