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Record W4411151507 · doi:10.3390/f16060970

Tourism Management in National Parks: Development, Aspects, and Conceptual Framework

2025· article· en· W4411151507 on OpenAlexaff
Dehui Christina Geng, Howard W. Harshaw, Christopher Gaston, Wanli Wu, Guangyu Wang

Bibliographic record

VenueForests · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersAsia-Pacific Network for Sustainable Forest Management and Rehabilitation
KeywordsTourismEnvironmental resource managementConceptual frameworkEnvironmental planningProcess managementBusinessEnvironmental scienceGeographySociology

Abstract

fetched live from OpenAlex

Outdoor recreation in national parks has significantly driven the growth of tourism globally. Research on tourism management in national parks has grown due to increasing scholarly interest in the field. This paper presents a bibliometric review of the development, aspects, and applications of national park tourism management. Data were collected from the Web of Science core collection database, and a total of 3438 research articles from 1980 to 2022 were selected and analyzed using VOSViewer (Version 1.6.19). We here analyze and visualize the co-occurrence of research keywords with temporal overlay and cluster analysis. We also present a content analysis and conceptual and management frameworks by examining multiple aspects of tourism management to offer detail aspect-based management implications. These can assist various park stakeholders, scholars, and associated collaborative efforts with the issue of how to best manage national park tourism in the context of an uncertain future and increasing conflicts of interests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.351
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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