Pregnant Men: Repronormativity, Critical Trans Theory and the Re(conceive)ing of Sex and Pregnancy in Law
Bibliographic record
Abstract
This article argues that a critical re(conceive)ing of sex and pregnancy is required in law. Drawing on the dual meaning of conceive – ‘to become pregnant’ and ‘to imagine, or form a mental representation of’, the goal of this article is to better ensure that pregnant men and trans individuals are not denied their reproductive rights, the legal recognition of their gender identities, and the protections of pregnancy discrimination law. Here, I survey molecular biologists’ and critical trans theorists’ scientific and discursive challenges to the understanding of sex as biologically determined; I map the extent to which biological and repronormative discourses – those which materialize and maternalize female identity – underpin legal determinations of trans subjects’ sex and their ability to access state issued documentation; finally, I suggest that feminists’ efforts to construct pregnancy discrimination as sex discrimination may unwittingly factor into discriminatory practice against pregnant men by reifying pregnancy as necessarily female and thus pregnant men as ‘really’ women. Drawing on Darren Rosenblum’s call to unsex parenting, I conclude by briefly considering the opportunities presented by unsexing pregnancy in law.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.092 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| 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".