La perception et l’évaluation des risques d’un point de vue psychologique
Bibliographic record
Abstract
Toute modélisation du risque et de l’incertitude nous donne l’illusion d’une certaine maîtrise de ceux-ci. Tentant de saisir la complexité des aléas de notre environnement, les gestionnaires du risque (chercheurs, ingénieurs, techniciens, opérateurs, cadres, concepteurs, responsables politiques, experts, assureurs) ont mis en place des modèles formels de l’évaluation du risque. Ces modèles considèrent que l’individu évalue le risque de manière rationnelle et objective. Or, les travaux de psychologie cognitive ont montré que nos décisions sont souvent illogiques, voire irrationnelles, alors qu’on est persuadé qu’elles le sont. Afin d’élaborer des outils à penser le risque, nous devons dorénavant inclure les facteurs psychologiques dans les modélisations du risque et de l’incertitude pour que celles-ci soient adaptées à la complexité des aléas de l’environnement naturel ou artificiel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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; both teacher heads agree on what is shown here.
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".