Pascal PANSU, Nicole DUBOIS et Jean-Léon BEAUVOIS (2013), Dis-moi qui te cite, et je saurai ce que tu vaux. Que mesure vraiment la bibliométrie ?
Bibliographic record
Abstract
Dans cet opuscule, Pascal Pansu, Nicole Dubois et Jean-Léon Beauvois présentent un regard critique sur l’évaluation de la recherche scientifique et notamment sur son socle méthodologique : la bibliométrie d’impact. Structuré en cinq parties, l’ouvrage, tout en étant critique, n’est pas exempt de pragmatisme ni d’originalité, tout en étant à la fois didactique et politique. Le titre, agrémenté d’un sous-titre, contraste avec la taille du texte, mais, ensemble, ils en annoncent assez fidèlemen...
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".