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Record W3103496828 · doi:10.1111/coep.12512

DO BETTER INSTITUTIONS BROADEN ACCESS TO SANITATION IN <scp>SUB‐SAHARA</scp> AFRICA?

2020· article· en· W3103496828 on OpenAlexaff
John Nana Francois, Johnson Kakeu, Cristelle Kouame

Bibliographic record

VenueContemporary Economic Policy · 2020
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsSanitationLanguage changeAccountabilityUniversal designGovernment (linguistics)Quality (philosophy)BusinessRural areaImproved sanitationAccess to financeEconomic growthDevelopment economicsEconomicsPublic economicsPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

Inadequate access to sanitation remains a persistent issue in sub‐Saharan African countries, affecting children, women, and workers. We employ dynamic panel estimation to uncover the empirical relationship between institutions and access to sanitation in sub‐Sahara Africa. We find that control of corruption, regulatory quality, and voice and accountability increase access to sanitation. Moreover, a dichotomy exists between rural and urban areas in that efficient corruption control, rule of law, and government effectiveness facilitate access to sanitation in rural areas. However, only voice and accountability matter in urban areas. These findings generate important policy implications in achieving universal access to sanitation. (JEL D72, O55, O180, P16)

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.100
GPT teacher head0.294
Teacher spread0.194 · 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 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

Citations10
Published2020
Admission routes1
Has abstractyes

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