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Record W2757440642 · doi:10.5539/ass.v13n10p55

The Effect of Rubbish Management Socialization Based on Indonesian Ulama Council’S Fatwa Number 47 of 2014 on Community Behavior in Dealing with Rubbish Problem

2017· article· en· W2757440642 on OpenAlexvenueno aff
Azis Muslim

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsnot available
Fundersnot available
KeywordsSocializationIndonesianRepresentativeness heuristicDocumentationGovernment (linguistics)Indonesian governmentValue (mathematics)PsychologyPublic relationsSociologySocial psychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Rubbish has been an acute and less resolvable problem, because the volume of rubbish produced by human being increases over years. Many attempts have been taken to solve this problem, one of which is through the economic value-based socialization of rubbish management. However, the result has not been able to generate consciousness and to change the community behavior collectively in dealing with rubbish problem. This research studied another attempt taken to deal with rubbish problem, the socialization of rubbish management using economic and religion value combination. This research was conducted in Sleman Regency. Data was collected through interview, observation, and documentation. Analysis was conducted interactively. The result of research showed that the socialization of rubbish management based on the Indonesian Ulama Council’s Fatwa Number 47 of 2014 could build consciousness and change the community behavior collectively in dealing with rubbish problem, when the participants selected reflected on the representativeness of all community elements, the presence of volunteers from the community who were willing to organize, the participants were given information completely about the objective of socialization, government’s support to the community conducting rubbish management activity, and the material of socialization was taken for granted by the participants of socialization.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.541
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.306
Teacher spread0.282 · 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.

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
Published2017
Admission routes1
Has abstractyes

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