Putting the Femme in Feminist: Trans Feminism and the ‘Male Lesbian’ in the American Second Wave
Bibliographic record
Abstract
ABSTRACT A slur, a joke or a post‐structuralist case of mistaken identity. To the extent that the male lesbian has been discussed, she has figured dismissively. Yet throughout the period historicised as American feminism's second wave, potentially thousands of trans femmes organised under this identity. Despite being entirely overlooked in scholarship, the lesbian feminism articulated by a community of femme‐for‐femme trans femmes in the 1970s constitutes one of the most enduring and intellectually significant subsets of lesbian feminism to come out of the second wave. That they have yet to be historicised and theorised represents an injustice at the level of epistemology itself, wherein trans women are able to speak as trans, but not as lesbians. Reconstructing the archive of trans lesbian feminism that was developed by Sally Douglas in 1970 and then popularised through her organisation the Salmacis Society the year after, this article proposes that the existence of Salmacis disrupts dominant ideas of necessary antagonisms between ‘trans’ and ‘lesbian’ in the 1970s, and we highlight how the distinctly trans, sex‐positive, lesbian femme‐inism of the organisation can reanimate lesbian feminism today.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".