MétaCan
Menu
Back to cohort
Record W2039305882 · doi:10.2166/wp.2006.047

Privatization model for water enterprise in Kenya

2006· article· en· W2039305882 on OpenAlexfundno aff
O.A. K’Akumu

Bibliographic record

VenueWater Policy · 2006
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsLegislaturePrivate sectorLegislationBusinessPublic administrationWater industryDeveloping countryWater sectorWater supplyState (computer science)Economic growthEconomicsPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

The world over, the role and eligibility of the state in the provision of water supply is increasingly coming into question. Policy makers and analysts are advocating the abdication of the state in favour of private participation. This is expected to bring with it a host of benefits to all the stakeholders concerned. Kenya is one of the developing countries that have endeavoured to privatize their water sectors. Kenya has done this by enactment and implementation of the Water Act of 2002. The paper carries out an analysis of the water institutions being created under the new legislation. This has been done against conventional policy and conceptual frameworks. Overall, the institutional set-up is found to be public sector-oriented rather than private sector-oriented. Recommendations are made for legislative review for mainstreaming private sector participation.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0260.001

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 head0.006
GPT teacher head0.196
Teacher spread0.189 · 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 designTheoretical or conceptual
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

Citations35
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueWater PolicySame topicWater resources management and optimizationFrench-language works237,207