nordique: défis et possibilités
Bibliographic record
Abstract
Gender remains one of the most persistent and all-encompassing binary systems of clas-sifying people. As a result, transgender individuals experience widespread prejudice and discrimination and experience higher rates of mental disorders and suicide. With a case study as illustration, the value of social justice in transgender therapy is explored. At-tention is paid to how social justice practices support therapists in being mindful of the intersection of identities and to why such practices are critical in supporting the mental health of transgender clients in northern Canada. Recommendations for social-justice-informed transgender therapy are discussed. résumé Le genre (sexe) demeure l’un des systèmes binaires les plus persistants et les plus globali-sants utilisés pour la classification des personnes. Il en résulte que les personnes transgenres sont très largement l’objet de préjugés et de discrimination et présentent des taux plus éle-vés de troubles mentaux et de suicide. Illustrant son propos par une étude de cas, l’auteure explore la valeur de la justice sociale dans la thérapie auprès des transgenres. Elle s’attache
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".