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Record W2065752419 · doi:10.5539/sar.v4n1p41

Accommodating the Interest of Local Community in Resolving Conflicts: A Case in Bentayan’s Wildlife Area, South Sumatra, Indonesia

2014· article· en· W2065752419 on OpenAlexvenueno aff
Didi Tahyudin, Ridha Taqwa, H. P. Dadang, Alfitri Alfitri

Bibliographic record

VenueSustainable Agriculture Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeNegotiationNatural resourceAgency (philosophy)Government (linguistics)Wildlife conservationEnvironmental resource managementGeographyNatural (archaeology)Environmental planningWildlife managementPolitical scienceEcologySociologySocial scienceEconomics

Abstract

fetched live from OpenAlex

<p>The developments of forest conservation Wildlife (SM) in Bentayan as flora and fauna ecology has created a conflict within the society and has negatively affected the wellbeing of the community in the area. The communities have used a lot of natural resources for their life. A development of Bentayan’s Wildlife Centre has been opposed by the community as the usage of various natural resources have been restricted after the development of the wildlife centre started. In order to solve the conflicts, many strategies have been employed. However, the expected outcome has not yet been achieved. Therefore, the current study provides a conflict resolution model approach to accommodate the interests of all parties, both society and government through the Natural Resources Conservation Center. The model was developed from narrative data that was collected through series of dialogues and negotiation process with both parties (community and agency/Centre) involving stakeholders and community members. This proposed model can be used as a framework for managing forestry and wildlife centre.</p>

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.563
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.310
Teacher spread0.262 · 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.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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