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Record W2957853220 · doi:10.1177/2399654419859365

Assessing states: Water service delivery and evolving state–society relations in Accra, Ghana and Cape Town, South Africa

2019· article· en· W2957853220 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCapeGovernment (linguistics)Context (archaeology)State (computer science)Work (physics)Economic growthService delivery frameworkGeographyPolitical scienceQuality (philosophy)SocioeconomicsService (business)BusinessSociologyEngineeringMarketingArchaeology

Abstract

fetched live from OpenAlex

This paper analyzes water services in relation to trust in government, with insights for broader state–society relations. The work is based on a multi-year and multi-sited case study of underserved areas of Cape Town, South Africa and Accra, Ghana. The analysis reveals that water quality and satisfaction are statistically linked to trust in government in South Africa, but not in Ghana. As well, while indicators of water access and quality appear to be very good in South Africa, there is nonetheless deep contestation and ongoing dis-enfranchisement. For Ghana, water access and quality are important for people’s daily lives, but are less strongly connected to senses of governmental responsibility—although for both countries there is a strong sense that government should be “doing more.” Features of history and context are emphasized in the Discussion and Conclusion sections to understand key differences between the sites and other results.

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 score0.125
Threshold uncertainty score0.368

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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