Cartographies policières : la dimension vernaculaire du contrôle territorial
Bibliographic record
Abstract
Le « crime mapping » (ou cartographie de la criminalité), très développé dans les polices métropolitaines ou régionales de pays anglophones, fait l’objet de controverses intenses. Celles-ci sous-estiment cependant deux éléments : premièrement, l’antériorité de pratiques cartographiques dans la police à l’acquisition des outils de cartographie numérique ; deuxièmement, des pratiques cartographiques sur le terrain caractérisées par l’autodidactisme. Les pratiques policières de cartographie relèvent ainsi d’une culture professionnelle particulière distincte de l’expertise des cartographes professionnels : cet article met en évidence la dimension vernaculaire du travail cartographique policier et montre en quoi les multiples cartographies policières sont malgré tout au service d’un projet territorial de contrôle. Grâce à une enquête sur la cartographie dans la gendarmerie nationale française, l’article contribue à une approche géographique de la police ancrée dans la cartographie critique et la géographie francophone.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".