Méthodologies en Administration publique : analyse comparative de la recherche au Canada et en Australie
Bibliographic record
Abstract
Plusieurs études relèvent une diversification des méthodes en Administration publique contemporaine. Cette étude fait un état des lieux systématique et comparé, sur une décennie, des méthodes de recherche publiées dans deux revues nationales en administration publique. Les recherches publiées en Administration publique au Canada, ainsi qu’en Australie, semblent en décalage sur la communauté mondiale en Administration publique au plan méthodologique. Notre revue systématique révèle toutefois peu de différences entre les deux revues : les entrevues et analyses qualitatives de contenu sont courantes dans les deux échantillons, mais les techniques quantitatives utilisées demeurent élémentaires. Il s’agit d’une particularité qui n’est pas partagée avec la recherche en science politique canadienne.
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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 | 0.068 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.021 | 0.046 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".