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Record W2789536649 · doi:10.1017/s1355770x17000432

Public preferences for improved urban waste management: a choice experiment

2018· article· en· W2789536649 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Development Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWillingness to payMixed logitPreferenceSocioeconomic statusInvestment (military)BusinessEconomicsDiscrete choiceWaste collectionMunicipal solid wastePublic economicsLogistic regressionPopulationMicroeconomicsEngineeringWaste managementEnvironmental health

Abstract

fetched live from OpenAlex

Abstract A discrete choice experiment, aiming to elicit public preferences for improvements in solid waste services, is carefully administered across socioeconomic zones in the city of Hawassa, Ethiopia. Observed and unobserved preference heterogeneity are analyzed using mixed logit choice models. The results show that there exists substantial willingness to pay to increase collection frequency and separate recyclable waste. A new issue is the focus on child labor in the waste management sector. Significant gender effects are found: women are more interested than men in increasing waste collection frequency and value the abolishment of child labor more highly, as do higher income households. As expected, respondents living in wealthier neighborhoods are more likely to pay higher service charges. Education indirectly influences preferences for waste separation. The study provides important insight into the social benefits of public investment decisions to improve the quality of solid waste management services in large cities in Ethiopia.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.112
GPT teacher head0.201
Teacher spread0.089 · 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