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Record W4306925892 · doi:10.18280/ijsdp.170623

An Exploration and Comparison of Attitudes Towards the Participatory Solid Waste Management for Sustainable Development of Communities in Khaoroopchang Municipality, Songkhla Province, Thailand

2022· article· en· W4306925892 on OpenAlexvenueno aff
Wassawadee Kaewprapun, Ampai Muensit, Ekarach Maliwan, Patcharin Kangkha, Onuma Suphattanakul

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
FundersRajamangala University of Technology SrivijayaThailand Science Research and Innovation
KeywordsSolid waste managementMunicipal solid wasteCommunity participationCitizen journalismPairwise comparisonParticipatory action researchScale (ratio)SocioeconomicsPsychologyBusinessEnvironmental planningSociologyEconomic growthGeographyPolitical scienceEngineeringEconomicsWaste management

Abstract

fetched live from OpenAlex

The purpose of this study is to explore and compare the community members’ attitudes towards community participation in solid waste management. The participants in this research were 400 people in 3 communities in Khaoroopchang Municipality. The research instrument was a set of 5-point rating scale questionnaires, enquiring about the community members’ attitudes towards the community’s solid waste management. The statistics used for data analysis were mean, standard deviation, t-test, analysis of variance (ANOVA), and LSD pairwise comparison. The results revealed that the community members’ attitudes towards the participatory solid waste management were at a high level. The results also showed that people who had different ages, education, occupations, residences, and family incomes had different attitudes towards waste management. This research outcome serves as a guideline for community leaders in changing the behavior of each household in the community in terms of waste sorting, career enhancement, and increasing income in the community in order to be good role models and local philosophers for sustainable development.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.085
GPT teacher head0.339
Teacher spread0.254 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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