Policing “the Risky”: Technology and Surveillance in Everyday Patrol Work
Bibliographic record
Abstract
Alors que de nombreux chercheurs universitaires du domaine de la surveillance et de la police affirment que l'émergence d'une société de la surveillance normalise l'utilisation des technologies de surveillance par les services policiers, nous constatons qu'à cause d'un manque de données empiriques il est difficile de déterminer l'impact réel de la gestion des risques, et de la sécurité et de la surveillance dans le travail de la police. Cette étude s'appuie sur des entrevues approfondies et sur l'observation participative de deux services de police canadiens dans le but d'explorer l'impact que les technologies policières peuvent avoir sur les interactions entre la police et le public. À partir de cette analyse, nous soutenons que le changement organisationnel des activités de police axé sur le risque et sur le renseignement ne se manifeste pas sur le terrain. Au contraire, les patrouilleurs utilisent plutôt les technologies pour légitimer l'action policière envers “les suspects habituels”.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".