Les modèles non unitaires de comportement du ménage : un survol de la littérature
Bibliographic record
Abstract
Cet article s’intéresse aux modèles non unitaires de comportement du ménage. Ces modèles supposent explicitement que le ménage est composé de plusieurs personnes ayant des préférences distinctes. Ils se classent alors en deux catégories principales : d’une part, les modèles coopératifs (ou collectifs), dans lesquels les allocations sont supposées efficaces au sens de Pareto, et d’autre part, les modèles non coopératifs (ou stratégiques) qui s’appuient sur la notion d’équilibre de Cournot-Nash. Dans ces modèles, les fonctions qui caractérisent le comportement du ménage doivent satisfaire des contraintes différentes des traditionnelles conditions de Slutsky. De plus, dans certains cas particuliers, les préférences des membres du ménage peuvent être identifiées à partir du comportement observable.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 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".