Exploring the Main Determinants of National Park Community Management: Evidence from Bibliometric Analysis
Notice bibliographique
Résumé
The establishment of protected areas such as national parks (NPs) is a key policy in response to numerous challenges such as biodiversity loss, overexploitation of natural resources, climate change, and environmental education. Globally, the number and area of NPs have steadily increased over the years, although the management models of NPs vary across different countries and regions. However, the sustainability of NPs necessitates not only effective national policy systems but also the active involvement and support of the local community and indigenous people, presenting a complex, multifaceted challenge. Although the availability of literature on community-based conservation and NPs has increased over the years, there is a lack of research analyzing trends, existing and emerging research themes, and impacts. Hence, in this study, we employed bibliometric methods to conduct a quantitative review of the scientific literature concerning community management of NPs on a global scale. By analyzing data from published articles, we identified research hotspots and trends as well as the quantity, time, and country distribution of relevant research. We developed a framework to illustrate the main research hotspot relationships relevant to NPs and community management, then summarized these findings. Based on the literature from 1989 to 2022, utilizing 2156 research papers from the Web of Science Core Collection database as the data source, visualizations were conducted using the VOSviewer software (1.6.18). Based on the results of network co-occurrence analysis, the initial focus of this field was on aspects of resource conservation. However, with the convergence of interdisciplinary approaches, attention has gradually shifted towards human societal well-being, emphasizing the “social-ecological” system. Furthermore, the current research hotspots in this field mainly revolve around issues such as “natural resources, sustainable development, stakeholder involvement, community management, sustainable tourism, and residents’ livelihoods”. Effectively addressing the interplay of interests among these research hotspot issues has become an urgent topic for current and future research efforts. This exploration necessitates finding an appropriate balance between environmental conservation, economic development, and human welfare to promote the realization of long-term goals for sustainable development in NPs.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,056 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».