Bibliographic record
Abstract
In this two-part paper, the author explores the significance of identity in mental health law and policy In this as in other socio-legal domains, identity functions to consolidate dissent as well as to effect social control. The author asks: where do legal experts stand in relation to the identity categories that run so deep in this area of law and policy? More broadly, she asks: is "mental health" working on us on the mental health disabled, legal scholars, all of us-in ways that are impairing our capacity for social justice? In the first part of the paper, the author considers the Foucauldian exhortation to undertake a "critical ontology of ourselves" and asks what it would mean to take this curious exhortation personally, with regard to one's mental health. In the second part, which will appear in the next issue of the Dalhousie Law Journal, she builds out from these insights toward a political taxonomy of mental health identities.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.072 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".