Bibliographic record
Abstract
Résumé Depuis quelque temps, la thématique de la gouvernance occupe le centre de nombreux débats. Dans ce contexte, le but de cet article est de livrer une partie de mes réflexions sur la gouvernance au Canada. Pour ce faire, je me suis fortement inspiré du modèle de Charreaux (1997), qui propose de réfléchir aux organisations en fonction de mécanismes externes et internes de gouvernance. En vertu de cette approche, l’ensemble des mécanismes qui assurent aux investisseurs que ceux à qui ils confient leurs ressources les utiliseront aux fins promises et non pas à des fins personnelles constituent des mécanismes de gouvernance pertinents. En appliquant mon analyse des mécanismes externes et internes de gouvernance au contexte canadien, j’ai considéré deux types d’entreprises assez courants au Canada : les entreprises à structure d’actionnariat minoritaire et les sociétés d’État. Je conclus mon analyse en précisant les nombreuses avenues de recherche qu’il reste à explorer si on veut mieux comprendre la gouvernance dans le contexte canadien.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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".