Policy Legitimacy, Rhetorical Politics, and the Evaluation of City‐Street Video Surveillance Monitoring Programs in Canada
Bibliographic record
Abstract
Cet article examine l'évaluation et la légitimation de la vidéosurveillance en milieu urbain en Ontario, Canada. Nous démontrons comment sont promus, conçus et justifiés les programmes de surveillance sur la base des revendications de leur efficacité émises de manière rhétorique. Bien que les données de l'évaluation du programme ne corroborent généralement pas ses objectifs, pas plus qu'elles ne les supportent, nous montrerons de quelle manière les politiques langagières de la recherche en évaluation de la vidéosurveillance trouvent leur légitimité en adhérant aux pratiques exemplaires telles qu'elles sont stipulées par le Bureau du commissaire à la protection de la vie privée de l'Ontario – pratiques qui sont formulées pour minimiser la rhétorique au sein‐même de la conception du système. Ce que nous avons trouvé soulève des interrogations sur la viabilité de la vidéosurveillance en milieu urbain en tant qu'option d'une politique viable, étant donné le manque de preuves relatives à son utilité.
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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 | 0.026 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".