Research Hotspots of Regional Resilience and the Visualization of Research Frontiers
Notice bibliographique
Résumé
As a hot regional research realm, regional resilience provides a new research perspective toward regional sustainable development. At the same time, regional resilience is also an important research paradigm of sustainability science. Based on literature from a core database (Web of Science) launched between 1991 and 2019 on the topic of "regional resilience," this study presents a knowledge graph analysis of regional resilience research. The citation visualization analysis software (CiteSpace5.0) was applied. Keywords co-occurrence network analysis, co-citation clustering analysis, social network co-occurrence analysis, and other analytical methods were adopted. This research drew the following three conclusions: 1) The quantity of regional resilience research shows an upward trend, and it mainly focuses on ecosystem, regional economy, social ecosystem, and social well-being. Five countries—including the U.S., Australia, Britain, Canada, China—and research institutes such as the University of Stockholm, University of Queensland, James Cook University, Chinese Academy of Sciences, U.S. Geological Survey, and University of Cambridge are strongly competitive in terms of research on resilience. 2) The representative works of scholars such as Ron Martin, Carl Folke, Angeler D. G., Craig R. Allen, and Gillian Bristow laid a solid knowledge foundation for regional resilience studies. Furthermore, their collaboration deepened the research on regional resilience. Ron Martin is a significant scholar in the field of the theory of regional resilience evolution, and his research reflects how regional resilience evolves from equilibrium theory to evolution theory. 3) Regional economy, social ecosystem, social well-being, and method exploration are hot topics in regional resilience research. According to keyword classification and citation clustering analysis, the research hotspots of regional resilience are mainly concentrated in the following four categories: 1) Due to global warming and increases in human activities, ecosystem disturbances have increased, and the protection of ecosystem diversity has become a long-term research topic. In addition, biodiversity and ecosystem services and management have become new growth points and strategic development directions of geography. 2) Recently, the world economy has been gloomy; global climate is continuously deteriorating, while regional unrest and frictional issues are increasing. At present, with increasing uncertainties in the global economy, how regions maintain long-term development under external strikes has become the core focus of regional resilience research. Not only should the economic structure be adjusted and optimized, but the stable supply of regional food and energy as well as a stable political and social environment should also be emphasized in regional resilience research. 3) Methodological breakthroughs are key points in regional resilience research. Regional resilience is an interdisciplinary concept that requires comprehensive interdisciplinary research, social-economic scenario analysis, and the construction of multilevel models. Exploration of interdisciplinary and multi-level methods is conducive to promoting the standardization and rationalization of regional resilience research. 4) Empirical research is the trend of regional resilience research. Combining resilience research with specific situations is beneficial in solving scientific problems, providing scientific guidance in relevant policies, and boosting the significance of regional resilience in the process of policymaking. With the deepening of the internationalization process, combining specific problems of certain regions and conducting theoretical and empirical research on regional resilience have become an inevitable path for researchers.
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 | 0,004 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,026 | 0,027 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».