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Record W3192765305 · doi:10.4102/jamba.v13i1.943

The role of community protection institution in disaster management at West Java, Indonesia

2021· article· en· W3192765305 on OpenAlexaff
Etin Indrayani, Sadu Wasistiono

Bibliographic record

VenueJàmbá Journal of Disaster Risk Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsInstitute on GovernanceGovernment of Canada
Fundersnot available
KeywordsUnit (ring theory)Government (linguistics)Work (physics)Focus groupPublic relationsBusinessIndependence (probability theory)Qualitative researchEmergency managementEnvironmental planningPolitical scienceKnowledge managementEnvironmental resource managementEngineeringPsychologySociologyGeographyMarketingComputer science

Abstract

fetched live from OpenAlex

This research aimed to establish a mechanism of evolution of community protection, identify the support of facilities and infrastructure needed in facilitating the implementation of the tasks and functions of Linmas, especially in disaster management and formulate community protection institutions that are appropriate to the needs and capacities of the regions. The research method is carried out by a qualitative approach that is using focus group discussion (FGD) based on experience and perceptions of the benefits and impacts of the community protection unit's guidance in West Java province. The results show that the community protection institutions are needed in improving the independence of the community in tackling any disaster that is faced by an organization in which at least have the ability and skills in the field: early prevention, peace and orderly of safety fibre, health and psychologist and public and social work. The practical implication of this research is that the local government should empower the community protection unit through the regional work unit or related stakeholders in conducting training and facilitation of training and improving skills so that they can carry out their duties better.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.030
GPT teacher head0.309
Teacher spread0.280 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

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