La prise de décision d’urgence chez les pompiers premiers répondants : une illustration de la pertinence d’une approche empirique en éthique professionnelle
Bibliographic record
Abstract
Lors d’une urgence médicale, l’intervention se doit d’être immédiate. Le temps de délibération est court, voire inexistant. Pourtant, l’intervenant portera la responsabilité de ses décisions et de ses actions. Cette complexité de la décision d’urgence demeure peu étudiée en éthique. Pour contribuer à combler cette lacune, cet article portera sur la prise de décision chez les pompiers premiers répondants. Il présente les données issues de focus groups réalisés auprès de pompiers du Service de Sécurité Incendie de la Ville de Montréal. Dans un premier temps, cet article illustrera la compréhension de la prise de décision d’urgence de ces pompiers premiers répondants. Dans un deuxième temps, il montrera qu’une approche empirique est indispensable à l’éthicien qui s’aventure en caserne : cette approche empirique est révélatrice des confrontations éthiques des pompiers et des moyens mis en place pour neutraliser ces confrontations.
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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 | 0.023 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 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".