Production de connaissances et processus de planification
Bibliographic record
Abstract
S’il peut sembler difficile de citer des cas où les planificateurs ont utilisé l’information à des fins de prise de décision, c’est que l’on définit l’information de façon trop étroite. Trois exemples illustrent ici le pouvoir de l’information, entendue comme un savoir subjectif et socialement construit dont l’influence se manifeste à travers les mythes qui structurent implicitement les politiques, à travers les négociations entre experts, décideurs et citoyens sur les concepts et les méthodes qui alimentent les décisions publiques, et à travers les modes de fonctionnement des organisations publiques et privées. Cette information, souvent implicite, sert à définir les problèmes et non pas à les résoudre. Elle n’exerce son influence que si elle se construit au cours d’un processus social auquel participent ses utilisateurs. Pour éviter les risques d’institutionnalisation et d’erreur qu’elle comporte, il faut la soumettre à la méthode critique et livrer ses postulats à un débat ouvert.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".