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Record W3014566725 · doi:10.31294/swabumi.v8i1.7543

Implementation of the Resilient Village at Gunung Geulis Village, Sukaraja Sub-regency, Bogor, West Java

2020· article· en· W3014566725 on OpenAlexaff
Admiral Musa Julius, Nrangwesthi Widyaningrum, Ainun Najib, Andi Ahmad Aminullah, Hani Syarifah, Hendro Pratikno, Ifad Fadlurrahman, Khairunnisa Adri, Tego Suroso, Rizkia Mutiara Ramadhani, I Dewa Ketut Kerta Widana

Bibliographic record

VenueSwabumi · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsDisaster risk reductionEmergency managementEnvironmental planningCapacity buildingBusinessGeographyDisaster areaEnvironmental resource managementRisk managementSocioeconomicsPolitical scienceSociologyFinanceEnvironmental science

Abstract

fetched live from OpenAlex

This study aims to analyze (1) the participation of the community of Gunung Geulis Village, particularly vulnerable groups, in managing resources in order to reduce disaster risk; (2) increasing the capacity of citizens and officials on disaster management and (3) the performance of the Village DRR forum. This study uses a qualitative method. The subjects of this study were Gunung Geulis village secretaries using the interview method. The results showed (1) personnel from the disaster management forum planted trees on landslides prone area and made archery embankments, (2) Gunung Geulis Village as a program implementer of Disaster Resilient Village had been actively conducting routine and ongoing training every once a month in an effort capacity development on disaster management, (3) the Disaster Risk Reduction (DRR) forum of Gunung Geulis village has carried out passive mitigation efforts such as making mapping and analysis of disaster risk, even though there is no document compiled. DRR personnel also carry out mitigation and early warning efforts through information through pamphlets, brochures, and other village meetings. In addition, active mitigation efforts have been made by the DRR team.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

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)0.0030.001

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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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