Bibliographic record
Abstract
La restitution de récits d’enquête reste vécue comme une forme de « mise en danger » vis-à-vis de la crédibilité des recherches menées empruntant principalement aux méthodes de types qualitatives, sans qu’il existe de réelle cumulativité relative aux enjeux et questionnements issus de ces restitutions. Une telle situation laisse transparaître un besoin en termes d’outillage analytique auquel cet article se propose d’apporter un début de proposition. En effet, à partir du postulat de départ que tout chercheur fait partie de son cadre de travail, qu’il influence mais qui l’influence également en retour, l’article propose de considérer tout déroulé de recherche sous l’angle de la systémique, et donc d’envisager les glissements réalisés comme étant des transformations issues de boucles de rétroactions positives. En ce sens, cet article souhaite, partant d’une expérience effective de recherche, tendre vers une possible généralisation analytique.
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 | 0.046 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.049 |
| Scholarly communication | 0.024 | 0.029 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.006 |
| 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".