Gestion de crise : le déraillement de train de MMA à Lac-Mégantic
Bibliographic record
Abstract
Dans ce mémoire, nous nous sommes penchés sur la gestion de crise du déraillement de train à Lac-Mégantic le 5 juillet 2013. Plus précisément, il s’agit d’une étude de cas de nature qualitative sur cette tragédie dans laquelle nous décodons la stratégie de gestion de crise utilisée par la compagnie Montreal, Maine and Atlantic Railway (MMA). Pour ce faire, nous analysons la couverture de deux quotidiens, soit un francophone (La Presse) et un anglophone (The Gazette) sur une période déterminée de trente et un jours. La recherche est basée sur le modèle de l’« Image Repair Theory » de Benoit (1997) ainsi que sur des éléments complémentaires de Rogers (1993). Les résultats de notre analyse démontrent que la gestion de crise de MMA comportait plusieurs lacunes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".