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Record W4380049115 · doi:10.52364/zona.v6i2.60

Partisipasi masyarakat dalam pengelolaan sampah pemukiman di Kecamatan Senapelan Kota Pekanbaru

2022· article· en· W4380049115 on OpenAlexaff
Febriana Zulmi, Yusni Ikhwan Siregar, Thamrin Thamrin

Bibliographic record

VenueJurnal Zona · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsGarbageNonprobability samplingPopulationSocioeconomicsHuman settlementSample (material)GeographyBusinessEnvironmental planningEnvironmental healthEngineeringWaste managementSociologyMedicine

Abstract

fetched live from OpenAlex

The problem of waste management which is still a city problem, if the waste is not done properly it will cause problems. Uncontrolled piles of garbage due to human activities will have an impact on environmental problems such as decreasing the beauty of the city, the emergence of odors from waste decomposition, the occurrence of air pollution due to burning waste that interferes with public health and a source of disease for human health. This research was conducted in Senapelan District, Pekanbaru City from February to April 2022. The type of research is quantitative analytic with cross sectional. The population is all heads of families with a sample of 94 people with purposive sampling. The results showed that there was no influence of age, education, occupation, on community participation in residential waste management in Senapelan District, Pekanbaru City and there was an influence on infrastructure, knowledge, perception, on community participation in residential waste management in Senapelan District, Pekanbaru City. It takes a conducive environment and good infrastructure in waste management in settlements in Senapelan District, Pekanbaru City

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.010
GPT teacher head0.208
Teacher spread0.199 · 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
Published2022
Admission routes1
Has abstractyes

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