The true transsexual and transnormativity: a critical discourse analysis of the wrong-body discourse
Bibliographic record
Abstract
How did the wrong-body discourse (WBD) become the dominant medicalised discourse in Canada and the United States? What ideological effects did this dominance have? To address these questions, I conducted a critical discourse analysis informed by Foucauldian genealogy. I analysed texts written in, or translated into, English for a medical-expert audience from the earliest mentions of wrong bodies in 1864 to the institutionalisation of the WBD in the DSM-III diagnosis of transsexualism in 1980. I argue that through the medicalisation of gender variance, the three tenets of the WBD—wrongness of the body; disjuncture between sex and gender; surgical and hormonal solution—developed individually and were brought together by medical experts into a coherent discourse in the mid-1960s. Two main factors likely contributed to the dominance of the WBD: the lack of dependence on any particular etiology that made the WBD compatible with a wide variety of explanations, and the very small number of medical experts responsible for the majority of publications on gender variance all using the WBD. I further argue that medical experts, faced with challenges to their treatment of gender-variant people, turned to the idea of true transsexualism to stabilise the newly-formed WBD and legitimate their treatment of gender variance. In addition to the three tenets of the WBD, true transsexualism also included characteristics and assumptions that medical experts expected gender-variant people to embody if they wanted access to treatment. Through these expectations, medical experts produced a set of norms against which all gender-variant people were judged as legitimate or not, namely, one of the first iterations of transnormativity.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.019 | 0.081 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".