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Record W4378836402 · doi:10.18280/ijsdp.180525

Sustaining Mangrove and Rainforests: Land Rights and Collective Action in Indonesia

2023· article· en· W4378836402 on OpenAlexvenueno aff
Asihing Kustanti, Mangku Purnomo, Dodik Ridho Nurrochmat, Yulia Rahma Fitriana

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersUniversitas Brawijaya
KeywordsRainforestMangroveCollective actionAction (physics)AgroforestryEnvironmental resource managementGeographyBusinessEnvironmental planningEnvironmental scienceEcologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

This study explores land right transfer and collective action as strategies for sustaining mangrove and rainforests in Indonesia.Qualitative methods were employed, and 45 informants were interviewed in purposively selected locations.Historical analysis was used to examine forest management, while an Institutional Analysis Development framework was used to assess sustainability.The study found that the land rights regime for mangrove and rainforests has different mechanisms for sustainability.The legal aspects of mangrove forests rely on community awareness and proper management, while rainforest land rights are granted by the government for educational and research purposes.Collective action was identified as a suitable management strategy.Effective control of the situation requires stakeholder cooperation, and effective regulation implementation is necessary for managing the unique forest.Future research should focus on understanding the community's capacity to understand forest characteristics, mapping the interests and powers of forest managers, and applying forest sustainability principles.

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)0.000
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 score0.063
Threshold uncertainty score0.201

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 head0.018
GPT teacher head0.247
Teacher spread0.228 · 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
Published2023
Admission routes1
Has abstractyes

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