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Record W3207570729 · doi:10.1080/07900627.2021.1969223

Scenarios for public systems transition using learning alliances: the case of water supply in Uganda

2021· article· en· W3207570729 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

VenueInternational Journal of Water Resources Development · 2021
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsAllianceBusinessWater supplyRobustness (evolution)Environmental resource managementEnvironmental planningEconomicsGeographyEngineering

Abstract

fetched live from OpenAlex

Uganda’s Vision 2040 aims to modernize rural water supply through a transition from community-managed point sources to professionally managed piped water services. At the start of the transition period, a learning alliance established in Kabarole District participated in action research to develop scenarios predicting possible future development trajectories. The diversity of its membership, whose formal institutional roles spanned national, district and niche levels, increased the robustness of the strategies proposed for the adaptively managed transition of the public water service. The learning alliance has been facilitated by a non-governmental organization providing funding and expert advice; the effectiveness of this approach is demonstrated.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.225
Teacher spread0.203 · 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