Organizing for Accountability: Community Legal Clinics and Police Complaints
Bibliographic record
Abstract
Cet article donne un bref aperqu des debuts et de l'6volution des m6canismes ontariens de traitement des plaintes contre la police et d6crit sommairement la proc6dure actuelle, pour s'6tendre ensuite sur ses lacunes.L'auteur y traite du r6le d'une clinique juridique communautaire dans la promotion des droits et d'une r6forme h cet 6gard.Elle examine les nouvelles strat6gies de droit en mati~re de mauvaise conduite policiire, de meme que les anciennes, et explique comment les cliniques pourraient contribuer A une r6forme de la police et A l'ducation juridique de la population en vue d'am6liorer la proc6dure de traitement des plaintes. I.4.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".