PRINCIPLES OF PUBLIC AND PRIVATE-BASED UNIVERSITY GOVERNANCE IN THE CONTEXT OF ENSURING THE EFFICIENCY OF EDUCATIONAL ACTIVITIES
Notice bibliographique
Résumé
The article analyzes the principles of good corporate governance; good university governance (in particular, those developed by the Committee of University Chairs of Great Britain, Goldsmith University of London, University of Toronto, Association of Universities of the Netherlands, Universities and Colleges in England, Wales and Northern Ireland; principles that were identified at the intersection of the phenomena of good university governance and good corporate governance; principles of state and public governance in education. Besides best practices in good university governance in the countries of the Organization for Economic Cooperation and Development (OECD) are analyzed. On the basis of the presented analysis, the principles of public and private-based university governance in the context of ensuring the efficiency of educational activities are theoretically substantiated. Such principles are: the principle of engagement (ensuring the appropriate and meaningful engagement of all stakeholders in the governance process and the implementation of such a model of university governance that involves joint activities and cooperative relationships between various governance structures); the principle of consensus collaboration (ensuring the common interests' fullfilment of all stakeholders, ensuring transparent and democratic procedures of self-governance and co-governance); the principle of efficiency (focusing on the most efficient use of resources in order to ensure sustainability and environmental protection; ensuring reliability, efficiency and flexibility of all governance processes and structures; orientation towards achieving optimal results; ensuring accountability, transfer of powers, consultative nature of activities, balance of open/confidential discussions, provision of necessary and timely information); the principle of optimality and relevant model (the most optimal use of resources and the creation of such a governance infrastructure that: is guided by the rule of law, provides for the implementation of decisions and supervision of activities, focused on increasing efficiency, effectiveness, creating comparative advantages for the university; developing such processes and structures of public- private governance, which correspond to the nature, scale and structure of the university); the principle of ensuring sustainability (focus on long-term strategic development, alignment of strategic priorities and vision with the interests of all stakeholders, effective control and risk management, increasing the level of capacity and viability of universities, their adaptation to changing environmental conditions); the principle of leadership (sensitive to the context, honest, interactive, aimed at realizing the mission and vision of the university, ensuring the engagement of stakeholders in the educational process in order to improve the quality of human capital, develop the potential of universities, produce and disseminate innovations, develop the economic capacity of regions and create regional innovation ecosystems).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,032 |
| Communication savante | 0,019 | 0,007 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,006 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».