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Record W4409726145 · doi:10.1080/19376812.2025.2494010

One Village, One Dam and development politics in northern Ghana

2025· article· en· W4409726145 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

VenueAfrican Geographical Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHydropower, Displacement, Environmental Impact
Canadian institutionsRed River College
Fundersnot available
KeywordsPoliticsPolitical scienceGeographyDevelopment economicsEconomics

Abstract

fetched live from OpenAlex

To increase water access in Ghana’s arid, northern agricultural communities, the Ghanaian government initiated the One Village, One Dam (1V1D) project in 2017. Under 1V1D, the government planned to construct or repair over 570 small-scale dams across northern regions, where water scarcity and social-ecological vulnerabilities are particularly high. This research examines implications of 1V1D in one rural agricultural community. We interviewed 29 community members and state officials in the Upper East Region to understand how 1V1D was rolled out, and implications for farmers. Our findings reveal that while state officials asked for community input and participation, community knowledge was ultimately sidelined for outside ‘experts.’ Furthermore, the dam has not met community members’ expectations and is not used for dry season farming. We situate these findings in a long history of water and development in northern Ghana and argue that development projects must move beyond recent party politics to truly incorporate local people’s insights and experiences in participatory development projects.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.367
Teacher spread0.344 · 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