A Discourse Analysis of Transsexuality through Three Fields: Expert Knowledges in Legal. Medical and News Texts
Bibliographic record
Abstract
Employing a Foucauldian discourse analysis, this thesis examines knowledge produced about transsexuality and sex reassignment surgery (SRS) through the fields of medical, legal and news texts. I explore key shifts in Western feminist, queer and trans approaches to sex/gender and the Diagnostic and Statistical Manual o f Mental Disorders’ pathologization of gender-variance in the Gender Identity Disorder diagnosis. I also undertake a case study of trans marriages prior to Bill C-38, and the Ontario Vital Statistics Act’s reliance on medical proof in change of sex designation requests. Finally, I analyze seventy-seven texts from The Globe and Mail, The Toronto Star, National Post and Toronto Sun spanning the 11-years (1998-2008) during which SRS was not funded in Ontario. The news coverage employs expert knowledge in legitimizing and de- legitimizing transsexuality and SRS. Overall, all three fields rely on cisnormative patterns of knowledge production and reflect the privilege granted to cissexuals in Canadian society.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".