MétaCan
Menu
Back to cohort
Record W4220993416 · doi:10.1080/13549839.2022.2048812

Increasing community environmental awareness, participation in conservation, and livelihood enhancement through tourism

2022· article· en· W4220993416 on OpenAlexaff
Zahed Ghaderi, Elham Shahabi, David A. Fennell, Mana Khoshkam

Bibliographic record

VenueLocal Environment · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsBrock University
Fundersnot available
KeywordsLivelihoodTourismGovernment (linguistics)Local governmentCultural heritageLocal communityCommunity participationPolitical scienceSocial exchange theorySociologyEconomic growthSocioeconomicsEconomicsGeographySocial sciencePublic administrationAgriculture

Abstract

fetched live from OpenAlex

In line with social exchange theory, this case study explores how a previously indifferent and unsympathetic local community participates in the conservation of Touran National Park through community-based tourism. An in-depth analysis of local community members, local authorities, and NGOs revealed that due to changes in society's socio-cultural structure, the community’s awareness of conservation has significantly increased and resulted in active participation in natural and cultural heritage. The findings provide an alternative to social exchange theory, suggesting that benefits should generally outweigh human social interaction and behaviour calculus costs. Furthermore, rural youth and women have become much more prominent despite many public participation dilemmas and rigid government structures. Finally, theoretical and practical implications for future research are discussed.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0010.005
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 head0.035
GPT teacher head0.313
Teacher spread0.278 · 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 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

Citations19
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueLocal EnvironmentSame topicDiverse Aspects of Tourism ResearchFrench-language works237,207