Bibliographic record
Abstract
Dans cet article, nous présentons un modèle collectif avec consommation publique. Ce modèle est basé sur celui, plus général, de Browning, Chiappori et Lewbel (2004). Au lieu d’estimer une technologie de consommation, qui capte toutes les économies d’échelle liées à la vie en couple, nous déterminons a priori les biens qui sont consommés de façon privée et ceux qui le sont de façon publique. Le modèle collectif en question est complètement identifié si l’on suppose que les préférences relatives aux biens privés et publics sont les mêmes pour qui vit en couple que pour qui vit seul. Le modèle nous permet de calculer des échelles d’équivalence applicables au sein du ménage. Ainsi, on échappe aux critiques formulées à l’encontre des échelles d’équivalence traditionnelles. Le modèle est appliqué aux données sur la consommation tirées de trois enquêtes de budget belges récentes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 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; 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".