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Record W2915849183 · doi:10.1080/13504509.2019.1580628

Conservation, development and stakeholder relations in Bhutanese protected area management

2019· article· en· W2915849183 on OpenAlexaff
Heidi Karst, Sanjay K. Nepal

Bibliographic record

VenueInternational Journal of Sustainable Development & World Ecology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Waterloo
FundersRoyal Government of Bhutan
KeywordsStakeholderBusinessNegotiationAccountabilityEnvironmental resource managementPovertyCorporate governancePoliticsStakeholder engagementEnvironmental planningPolitical scienceEconomic growthPublic relationsEconomicsGeography

Abstract

fetched live from OpenAlex

Conservation and development initiatives have been widely promoted in protected areas (PAs) in developing countries despite ongoing challenges inherent in their capacity to protected biodiversity and alleviate poverty. Bhutan’s vast PA network is becoming increasingly affected by the rapid expansion of conservation and development activities. This paper examines important challenges that PA stakeholders face during socio-political change, and assess how these challenges might impact stakeholder relations in a remote Asian PA. Multiple methods were used to explore the gap between expectations and delivery of two development projects and provide insights through issues of local capacity, indigenous culture and incompatible priorities. Perceived impacts indicated flaws in project design, strong local cultural norms yet weak local ownership, trust and accountability concerns, tensions between modernization and traditional lifestyles, and prospective trade-offs. Suggestions for stronger projects and PA management include having greater internal leadership, adopting realistic timelines, and openly negotiating trade-offs and hard choices.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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