Bibliographic record
Abstract
Sur la scène statistique, les indicateurs occupent désormais une place de choix, et lorsque leur ambition est de mesurer des aspects par nature intangibles, ils font souvent l’objet d’âpres discussions. L’histoire et les déboires de l’élaboration, sur le plan européen, d’un indicateur de sécurité dans un domaine à risque (le contrôle de la navigation aérienne) montrent les difficultés épistémiques (que peut-on mesurer ou quantifier ?) et politiques (à quelles conditions peut-on rendre des chiffres publics ?) liées à un objectif (la sécurité aérienne) qui est la raison d’être des organismes de contrôle de la navigation aérienne. Dans la lignée de la sociologie de la statistique d’Alain Desrosières, nous analysons cette histoire de recherche d’accord sur les conventions, qui devient celle d’une renonciation à quantifier (tout ce qui compte ne peut être compté…) et nous proposons ainsi d’ouvrir une histoire des échecs, du renoncement, et de la résistance à la quantification.
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 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".