Biais Cognitifs et Prise de Risque Managériale : Validation Empirique dans le Contexte Tunisien
Bibliographic record
Abstract
Le contexte de prise de décision est entaché par des biais cognitifs. Se basant sur un échantillon de 46 entreprises tunisiennes cotées durant 1997-2006, nous avons d’abord observé l’influence de trois biais (sur-confiance, mimétisme et illusion de contrôle) sur la perception du risque et ensuite, nous avons analysé la relation entre cette perception et la prise de risque effective. Nos résultats concluent à l’existence d’une relation positive entre le biais de sur-confiance et de mimétisme et la prise de risque et à une relation négative entre le biais de l’illusion de contrôle et la prise de risque managériale.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".