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Record W4386250707 · doi:10.18280/ijsdp.180818

Community-Based Mangrove Protection to Mitigate Climate Change: A Socio-Ecological Approach

2023· article· en· W4386250707 on OpenAlexvenueno aff
Andry Sukarmen, Mubarak Mubarak, Daviq Chairilsyah, Dessy Yoswaty, Rasoel Hamidy

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsMangroveClimate changeEnvironmental resource managementGeographyEnvironmental planningEnvironmental scienceEnvironmental protectionEcology

Abstract

fetched live from OpenAlex

Protection of the mangrove ecosystem in the Climate Village Program (ProKlim) is a government effort to reduce climate change and reduce Greenhouse Gas (GHG) emissions from an ecological perspective.This study aims to analyze the protection of mangrove ecosystems based on community empowerment in the climate village program (ProKlim) in Pangkalan Jambi Village, Bengkalis Regency.The method used in this research is mixed method by combining quantitative and qualitative technique through observation and in-depth interviews.From the observation results, it was found that the condition of the mangroves in Pangkalan Jambi Village had been damaged.Based on interviews, it was found that community involvement was carried out with the concept of empowerment accompanied by PT.Pertamina Indonesia Refinery (KPI) Sungai Pakning, Bengkalis Regency Government and Riau Provincial Government so that the mindset of the people in Pangkalan Jambi Village, Bukit Batu District, increases positively in protecting the mangrove ecosystem.In protecting the mangrove ecosystem, real action is carried out through planning, implementing nurseries, planting and using technology by involving the community.The novelty of the paper lies in its novel combination of socio-ecological and mixed method approaches to highlight the importance of community-based conservation efforts in mitigating climate change impacts in a mangrove ecosystem protection.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.176
GPT teacher head0.350
Teacher spread0.174 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Sustainable Development and PlanningSame topicClimate Change, Adaptation, MigrationFrench-language works237,207