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Using tourism to conserve the mist forests and mysterious cultural heritage of the Blue and John Crow Mountains National Park, Jamaica

2012· article· en· W2019610499 on OpenAlex
Susan Otuokon, Shauna‐Lee Chai, Marlon Beale

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePARKS · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSocioeconomics of Resources and Conservation
Canadian institutionsAlberta Innovates
Fundersnot available
KeywordsNational parkTourismCultural heritageGeographyArchaeologyEnvironmental ethicsForestry

Abstract

fetched live from OpenAlex

The Blue and John Crow Mountains National Park protects internationally significant biodiversity components and rich cultural heritage. Inside the park, two recreation areas are managed, and outside, sustainable community tourism is being developed. Tourism contributes to Aichi Targets by: (1) raising public awareness of the values of biodiversity, (2) engaging local communities in biodiversity awarenessraising and skills training, and (3) facilitating ecologically sustainable, income-generating activities for poverty reduction. Tourism and community engagement activities are part of the effort to reduce threats to forests through unsustainable livelihoods such as slash and burn, shifting agriculture. Community tourism activities have been established in a few communities while others are at various stages of planning. Several community members are now employed as National Park Rangers or otherwise assist in park management. Benefits to biodiversity conservation have been realised through local capacity building for sustainable tourism.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.048
GPT teacher head0.257
Teacher spread0.209 · 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