Bibliographic record
Abstract
Ce texte se propose d’examiner quelques-unes des plus importantes contributions de Jean-Jacques Laffont au versant appliqué de la science économique. Dès le début de sa carrière, Laffont a considéré la théorie économique comme un outil tourné vers l’action. Après l’étude de certaines méthodes économétriques suscitées par d’importantes questions économiques, Laffont s’est lancé le défide confronter la nouvelle économie industrielle au réel. Théorie de la concurrence imparfaite, enchères, théorie des contrats et de la régulation ont successivement subi l’épreuve des tests de Laffont sur leurs pouvoirs explicatifs et prédictifs. Nous présentons ici quelques uns des épisodes marquants de cette grande aventure qu’a eu Jean-Jacques Laffont avec l’économie appliquée.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".