Narratives of De/Retransition: Disrupting the Boundaries of Gender and Time
Bibliographic record
Abstract
This dissertation research draws on the lived experience of people who choose to de/retransition in order to complicate simplistic understandings of de/retransition as ‘sex change’ (or postoperative) regret. Specifically, I interpret narratives of de/retransition beyond the dominant framing of ‘sex change’ regret to analyze the ways in which these narratives produce ruptures in normative discourses that constrain trans genders and temporalities of gender transition. My research opens up space for interpreting processes of de/retransition as more complex, nuanced, and productive than they are commonly understood. The dissertation is organized in such a way that each chapter deals with narratives that become progressively personal. As such, the first chapter is an analysis of mainstream media representations of de/retransition, with commentary on topics such as desistance rates, rapid-onset gender dysphoria, and autism. The second chapter rereads Leslie Feinberg’s fictional (or semi-autobiographical?) Stone Butch Blues as a narrative of de/retransition and considers what this narrative adds to contemporary debates in trans studies, specifically with regard to the trans/cis binary and trans temporalities. The third chapter focuses on Brian Belovitch’s memoir, Trans Figured: My Journey From Boy to Girl to Woman to Man, where the topics of trauma, passing, and queer utopia arise. The fourth and final chapter is based on interviews that I have conducted with three participants. In the conclusion to this dissertation I argue that we need to do away with notions of authenticity and regret to an understanding of all (trans) gender subjectivity as relationally constituted and subject to change.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| 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".