Bibliographic record
Abstract
Cet article analyse un moment de l’élaboration de la Loi de programmation de la recherche (LPR), le processus législatif. Il s’intéresse aux modalités de participation des professionnel·le·s de la recherche à l’élaboration des réformes de leur secteur dans l’espace parlementaire. À l’aide de méthodes qualitatives et quantitatives, nous montrons une homologie entre la structuration des prises de position des parlementaires académiques dans le champ parlementaire et la structuration des prises de position des chercheur·euse·s et enseignant·e·s-chercheur·euse·s dans le champ académique. Nous examinons ses effets. Plus que la seule présence de cet espace dans les discussions, nous montrons une opposition entre une fraction de l’élite scientifique qui pousse à des réformes inégalitaires et le reste de la communauté universitaire. Les positions en dehors du Parlement structurent le jeu parlementaire, et se jouent dans cet espace une lutte pour la définition des conditions d’exercice du métier de professionnel·le de la recherche, de la façon de faire de la recherche et de la financer.
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 | 0.054 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 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".