L’instrumentalisation du savoir économique en milieu universitaire québécois : Controverses autour de l’utilité d’une discipline (1950-1975)
Bibliographic record
Abstract
L’article présente quelques-unes des querelles survenues chez les économistes québécois francophones. Bien avant leur uniformisation, les sciences économiques ont longtemps été tiraillées entre leurs volets théorique et appliqué. Comme plusieurs autres sciences sociales tant au Québec qu’ailleurs dans le monde, la discipline s’est d’abord institutionnalisée dans un cadre pragmatique pour ensuite évoluer vers un contenu nettement plus théorique. C’est à cette transition que nous nous intéressons ici. Loin d’être simplement un débat épistémologique entre partisans d’une économie appliquée et d’une économie théorique, le parcours de cette discipline comporte également des enjeux administratifs et idéologiques qu’il est nécessaire de prendre en considération.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".