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Record W2890736291

A social business model for the provision of household ecological sanitation services in urban Haiti

2016· article· en· W2890736291 on OpenAlexfundno aff
Claire Remington, Marion Cherrak, Nick Preneta, Sasha Kramer, Borja Royuela Mesa

Bibliographic record

VenueLoughborough University Institutional Repository (Loughborough University) · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersEidgenössische Anstalt für Wasserversorgung Abwasserreinigung und GewässerschutzGrand Challenges Canada
KeywordsSanitationToiletSeweragePit latrineLatrineBusinessPopulationService (business)Port (circuit theory)Environmental planningOpen defecationAgricultural economicsGeographyEnvironmental engineeringEnvironmental scienceEngineeringEnvironmental healthEconomics
DOInot available

Abstract

fetched live from OpenAlex

Traditional sanitation alternatives like pit latrines or sewerage systems are often unsafe, economically infeasible or inappropriate for low-income populations living in urban areas characterized by lack of infrastructure, high population density, a high groundwater table, and a subsequent lack of waste treatment.Since 2012, SOIL has launched a household ecological sanitation service, called EkoLakay, in several urban areas in Haiti.This program is showing promising results in providing a sustainable, attractive, and affordable sanitation solution for urban households.Customers pay a monthly fee of $4-$5 that covers the installation of the toilet and the weekly waste collection.Waste containers are brought to a SOIL composting waste treatment facility where the wastes are safely treated and transformed into a nutrient-rich compost.As of March 2016, Ekolakay serves 721 households, or 4000 users, in Port-au-Prince and Cap-Haïtien, and demand for the service continues to grow.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0240.002

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 head0.222
Teacher spread0.198 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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Same venueLoughborough University Institutional Repository (Loughborough University)Same topicChild Nutrition and Water AccessFrench-language works237,207