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Enregistrement W4380894310 · doi:10.30525/2500-946x/2023-1-12

WORLD EXPERIENCE OF UNIVERSITY SUSTAINABLE DEVELOPMENT

2023· article· en· W4380894310 sur OpenAlexaboutno aff
Наталія Холявко, Iryna Didenko

Notice bibliographique

RevueEconomics & Education · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSustainability in Higher Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSustainable developmentHigher educationEconomic growthPolitical scienceOrder (exchange)BusinessEconomics

Résumé

récupéré en direct d'OpenAlex

Introduction. A typical practice of the world's leading countries is the transformation of higher education institutions into agents of change in society. In the XXI century, these changes are primarily focused on various aspects of sustainable development of the country and its regions. Currently, it is the universities, together with NGOs, that have the greatest impact on the achievement of the Sustainable Development Goals proclaimed by the UN for 2015. The purpose of the research is to analyse the global experience of sustainable development in higher education institutions (HEIs). Methodology. This study used the cognitive method of analysis. In order to obtain the most objective research results, the authors studied the universities included in the international Times Higher Education Impact Rankings. The study covered universities from all over the world that were included in the top 50 of the rating. The results of the analysis are systematised according to geography (the article includes several sections characterising the sustainable development of universities in Europe, the United States, Canada and Australia). Results. Higher education institutions are now expected to become leaders in sustainable change in the country, economy and society. The world's leading universities are demonstrating how to progressively transform their activities in line with sustainable principles. They are investing heavily in the implementation of the latest technologies for energy saving, water conservation, campus landscaping and waste recycling. Since they have access to areas where the natural complex is preserved, universities are trying to support these areas and create favourable conditions for using them as living laboratories in educational and research processes. Universities offer sustainable development and lifestyles as part of their educational activities (public lectures, expert workshops, specialised short-term online training, etc.). Universities influence the achievement of the Sustainable Development Goals through their educational and research (inventive) activities. The world's leading universities are keen to promote the concept of sustainable development: they share events held, projects and initiatives undertaken and goals achieved widely on their official websites and social networks. Conclusion. The main directions of sustainable development in higher education institutions are 1) sustainable development of the campus (carbon neutrality, rational consumption, energy efficiency, waste recycling, optimisation of drinking water consumption, green transport, food safety for students); 2) sustainable educational programmes and courses (a sustainable component in students' bachelor and master theses); 3) sustainable research (innovative technologies against climate change, water conservation, energy saving, etc.); 4) management (internal regulatory documents on sustainable development, specialised sustainability centres to promote and support sustainable initiatives). Long-term partnership with stakeholders (entrepreneurs, local authorities and students as agents of future sustainable change) plays an important role in ensuring sustainability. The sustainable development strategy of a modern higher education institution should be based on the principles of complexity and coherence, which will not allow sustainability measures and initiatives to be fragmented and asynchronous. Areas for further research include building a theoretical and methodological framework for the development of an integrated ecosystem of sustainable development of universities.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,577
Score d'incertitude au seuil0,785

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,303
Écart entre enseignants0,285 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2023
Routes d'admission1
Résumé présentoui

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