La gouvernance des entreprises publiques : analyse comparative à l'échelle internationale
Bibliographic record
Abstract
Ce papier s'intéresse à réaliser une analyse comparative de la gouvernance des entreprises publiques. Cet exercice de comparaison permet de mettre l'accent sur les avantages et les inconvénients de chaque expérience en soulignant les points communs et de différence de chaque pays afin de déduire les perspectives futurs de la gouvernance publique. La réalisation de ce travail a nécessité la collecte, le traitement, l'analyse et la synthèse des différents documents, en particulier des articles scientifiques, des rapports officiels et des études professionnelles. Nous avons également eu l'opportunité de faire vingt entretiens avec les administrateurs et les dirigeants des entreprises publiques. Nous avons utilisé la technique des entretiens en profondeur afin d'explorer l'avancement des pratiques de la gouvernance tout en notant les remarques, les contraintes et leurs propositions pour renforcer le système de la gouvernance et les points de différence avec les autres entreprises publiques à l'international en étudiant trois cas : la SNCF en France, la STM au Canada et la NIW au Royaume Uni. Pour cela, nous commençons par le cadre général de la gouvernance des entreprises publiques, ensuite nous mettons une comparaison de la gouvernance des entreprises publiques entre la France, l'Espagne, l'Allemagne, le Canada et le Royaume Uni avec des illustrations pratiques afin de tirer les enseignements et les perspectives futures de recherche. Abstract : This paper is interested in carrying out a comparative analysis of state owned enterprise governance. This comparative exercise emphasizes the advantages and disadvantages of each experience by highlighting the commonalities and differences of each country in order to deduce the future perspectives in public governance. This work required the collection, processing, analysis and synthesis of the various documents, in particular scientific papers, official reports and professional studies. We also had the opportunity to do twenty interviews with directors and managers of state owned enterprise. We used the in-depth interview
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.032 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".