Draft Dodger, Soldier’s Wife: Trans Feminine Lives, Civic Duty, and World War II
Bibliographic record
Abstract
This article examines trans feminine lived experiences in the United States during the Second World War amid persecution amplified by the Selective Training and Service Act of 1940, the May Act of 1941, and heightened visibility through local and national news publications. This article contends that there is a longer and more complicated linked history between trans feminine Americans and the U.S. military than has been acknowledged by both scholarship and public discourse. Federal statutes like the STSA and the May Act lent authority to the state and its auxiliaries beyond the singular municipal or county jurisdiction. These factors aided the legal persecution of innumerable Americans with perjury, draft evasion, ‘moral’, and fraud charges. Through case studies of the disparate circumstances surrounding the ‘discovery of sex’ of three individuals, Sadie Acosta, Lucy Hicks Anderson, and Georgia Black, this study illuminates the role of various actors involved in investigating and policing their ‘moral’ crimes and gender variance in the 1940s and 1950s. In the post-war years, the figure of the ‘ex-G.I.’ woman is seen through numerous well-publicized cases in the U.S. and the U.K., showing that trans feminine experiences of World War II could be found both at home and abroad.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".