Mesurer l'efficacité des députés au sein du parlement français
Bibliographic record
Abstract
Résumé L’adoption d’un nouveau règlement par l’Assemblée nationale en 2009, consécutive à la révision constitutionnelle de 2008, a attiré l’attention sur le problème de l’absentéisme et sur la question de l’efficacité des députés dans l’exercice de leur mandat parlementaire. Cet article se propose d’analyser cette question en mobilisant des techniques de frontières non paramétriques qui permettent de ne pas s’en tenir à la seule mesure du taux de présence, mais de mettre en valeur l’activité effective des parlementaires dans les commissions et dans l’hémicycle à niveau d’assiduité donné. Le recours à l’analyse économétrique permet ensuite de préciser le rôle des caractéristiques personnelles et politiques des députés sur leur performance relative. Nos résultats mettent en lumière l’impact du cumul des mandats et du clivage entre la majorité et l’opposition.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".