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Decentralisation in Africa: A critical review of Uganda's experience

2017· review· en· W2113237779 on OpenAlexaff
Henry Ojambo

Bibliographic record

VenuePotchefstroom Electronic Law Journal/Potchefstroomse Elektroniese Regsblad · 2017
Typereview
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDecentralizationAccountabilityPublic administrationService delivery frameworkGovernment (linguistics)DemocracyLocal governmentConstitutionPromotion (chess)Corporate governancePolitical scienceCentral governmentService (business)Economic growthLawEconomicsPoliticsEconomyManagement

Abstract

fetched live from OpenAlex

Since the rise to power of the Movement government under the leadership of Yoweri Museveni in 1986, Uganda has largely been show-cased as an emerging democracy on the continent. Among other things, Museveni's regime has been acclaimed for the restoration of periodic national elections, the making of the Constitution and the overall promotion of democratic governance, most especially through the adoption of a decentralised system with a commendable institutional and legal framework. Decentralisation is believed to promote service delivery at the local level, accountability for government resources by local leaders, and the involvement of the masses in local planning and the implementation of government programmes. It is now over twenty years since decentralisation was adopted as a system of government but the quality of service delivery and the accountability for government resources at the local level remains just as deplorable as the extent to which the masses are involved in the planning and implementation of government programmes in their localities. This paper examines the challenges that inhibit the realisation of the noble objectives of decentralisation, notwithstanding the apparently impressive institutional and legal framework. 

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0070.012
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.110
GPT teacher head0.415
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2017
Admission routes1
Has abstractyes

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