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Record W4402956565 · doi:10.18280/ijsdp.190938

Sustainable Tourism Development: A Model of Adaptive Destination Management in Lampung Province, Indonesia

2024· article· en· W4402956565 on OpenAlexvenueno aff
Dedy Hermawan, Simon Sumanjoyo Hutagalung

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsnot available
FundersKementerian Pendidikan, Kebudayaan, Riset, dan TeknologiUniversitas LampungBureau of Planning and International Cooperation, Ministry of National Education
KeywordsTourismSustainable tourismBusinessSustainable developmentEnvironmental planningGeographyPolitical science

Abstract

fetched live from OpenAlex

This study explores the development of a sustainable tourism management model in Lampung Province, Indonesia, emphasizing stakeholder participation, particularly during and after the COVID-19 pandemic.The research utilizes an exploratory qualitative approach to identify and reconstruct an adaptive co-management model that enables stakeholders to share responsibilities and learn collaboratively within the tourism sector.The study's findings offer insights into the importance of adaptive participation and provide a foundation for future policy and practice in sustainable tourism management.The outcome involves redesigning adaptive co-management models, emphasizing a continuous process that allows stakeholders to collaboratively assume responsibilities within a framework where they can pursue their objectives, identify shared interests, gain insights from their institutions and methods, and adjust them for future iterations.At the same time, similar to adaptive management, the emphasis remains on experiential learning, recognizing the variety of knowledge systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

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