MétaCan
Menu
Back to cohort
Record W2113261107 · doi:10.1177/0956247808096122

Budget sheets and buy-in: financing community-based waste management in Siem Reap, Cambodia

2008· article· en· W2113261107 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 Urbanization · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHydropower, Displacement, Environmental Impact
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinanceChampionBusinessData collectionFinancial managementWaste collectionOperating budgetPoliticsMunicipal solid wasteWaste managementEngineering

Abstract

fetched live from OpenAlex

This paper details some of the difficulties in financing a community-based waste management (CBWM) project for the collection of waste in Siem Reap, Cambodia. It presents a series of financing scenarios based on several potential logistical arrangements. The financial variables investigated include labour costs and honorariums, collection fees, charges for secondary collection, land and equipment costs, and educational programmes. The case study illustrates how the loss of a political champion and a lack of cooperation by a private waste collection company derailed the financing of a CBWM project despite the presence of other favourable conditions for its success. The waste collection company's participation was fundamental to ensuring the affordability of secondary waste collection, and this one financial element greatly affected the feasibility of the entire system. The paper concludes that without buy-in and financial cooperation from all stakeholders, the best laid plans for CBWM (and the accompanying budget sheets) are rendered irrelevant.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.632

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)0.0000.000

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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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