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Record W1591082930 · doi:10.5539/ass.v11n18p279

Policy Implementation of Local Communities Development-Based Waste Management in Banjarbaru, South Kalimantan, Indonesia

2015· article· en· W1591082930 on OpenAlexvenueno aff
Ogi Fajar Nuzuli, Yuli Andi Gani, Ratih Nur Pratiwi, Imam Hanafi, Anwar Fitrianto

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessGovernment (linguistics)EmpowermentLocal governmentCommunity participationProcess (computing)Order (exchange)Environmental economicsEnvironmental planningEnvironmental scienceEconomic growthComputer scienceEconomicsPolitical scienceFinanceSocioeconomicsPublic administration

Abstract

fetched live from OpenAlex

This study aims to describe and analyze the facts that occurred in Banjarbaru, related to the implementation of community development-based government policy in addressing the issue of spike volume of waste. We found that waste management system in the landfill Hutan Panjang, Banjarbaru is currently still using open dumping system, so that improvements must be focused in order to become controller landfill management. Due to that fact, the implementation of government policies based on local community development in waste management has been focused for improvements of final landfills (TPA) Hutan Panjang with high hope to process all the waste in Banjarbaru. Moreover, local government of Banjarbaru should further improve the model to go green and clean which can strongly encourages the empowerment of people. Thus it is a form of implementation of good waste management through coaching stage.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.286
Teacher spread0.262 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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