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Record W4414999905 · doi:10.32832/abdidos.v9i3.2838

INSTITUTIONAL STRENGTHENING FOR COMMUNITY-BASED AGROTOURISM DEVELOPMENT AND ENVIRONMENTAL CONSERVATION IN JAYAWIJAYA REGENCY

2025· article· en· W4414999905 on OpenAlexaff
Sumiyati Tuhuteru, Naftali Frans Rumbiak, Benediktus Efer Alfaris Rumbiak

Bibliographic record

VenueAbdi Dosen Jurnal Pengabdian Pada Masyarakat · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsTourismCitizen journalismSustainable developmentSustainable tourismParticipatory action researchService (business)Developing countryCommunity participationCapacity building

Abstract

fetched live from OpenAlex

Jayawijaya Regency holds significant potential for developing agro-tourism villages based on local wisdom and environmental conservation. However, underdeveloped community institutions remain a key barrier. This community service project aimed to strengthen village institutions through agro-tourism management training, participatory planning facilitation, and digital promotion. The participatory method was implemented over three days at Yudha Hall and organized by the Department of Culture and Tourism of Jayawijaya Regency, involving approximately 45 local tourism actors. Results indicated a significant improvement in participants' understanding of agro-tourism concepts, institutional strengthening (BUMDes and Pokdarwis), and the emergence of participatory village tourism action plans. Before the training, only 27% of participants understood basic agro-tourism concepts; this increased to 81% post-training. These achievements demonstrate that thematic training integrated with field practice is effective in building institutional capacity and advancing sustainable agro-tourism development in Jayawijaya.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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