A Comparative Analysis of the Treatment of Transgender Prisoners: What the United States Can Learn from Canada and the United Kingdom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The treatment of transgender people while incarcerated is an issue that was catapulted into the national spotlight in 2019 when the Ninth Circuit Court of Appeals ruled in favor of providing a transgender inmate gender confirmation surgery. This decision created a circuit split within the United States regarding the medically necessary treatment a state is legally required to provide an inmate with gender dysphoria. This Comment examines the legal and policy approaches of the United Kingdom and Canada to inform the current circuit split and provide suggestions for improvements that could be made in the United States. Through exploration and comparison, this Comment proposes changes in policy and practice for housing transgender inmates, providing consultation with medical professionals, and treating transgender inmates in daily life. More specifically, this Comment proposes that the United States should employ a more gender-affirming approach when providing healthcare to transgender inmates by adopting policies and regulations in accordance with the medical community’s most recent recommendations. This includes setting up data collection systems able to obtain accurate population statistics for transgender inmates to make sure their needs are met. Additionally, uniform policies should be created to align gender-affirming language and practice, and housing reforms are necessary to ensure transgender inmates avoid solitary confinement placement because they lack alternative housing.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it