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Record W4389568452 · doi:10.1177/00020397231211935

State Capacity and Elite Enrichment in Uganda's Northeastern Periphery

2023· article· en· W4389568452 on OpenAlexfundno aff
Karol Czuba

Bibliographic record

VenueAfrica Spectrum · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsEliteAuthoritarianismState (computer science)PoliticsPopulationGovernment (linguistics)Natural resourceInvestment (military)Political scienceEconomic growthDevelopment economicsPolitical economyEconomicsSociologyDemocracyLaw

Abstract

fetched live from OpenAlex

In the mid-2000s, Uganda's authoritarian National Resistance Movement (NRM) regime set out to extend state control over Karamoja, a long-neglected region in the northeast of the country. This effort has involved large-scale deployment of security personnel, investment in an expansive administrative system used to subdue the local population, and construction of physical infrastructure that connects Karamoja with the rest of Uganda and facilitates the exploitation of the region's natural resources by members of the political elite. Government bodies in Karamoja capably perform functions that benefit the NRM elite and regime; other government responsibilities, notably for public service provision, have been assumed by non-state organisations. This article shows that the unevenness of state capacity in the region is the result of a coherent strategy that the regime has implemented across Uganda; developments in Karamoja illuminate this strategy and, thereby, help to account for the apparent incongruity of the country's political system.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0040.002
Open science0.0000.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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 designObservational
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

Citations3
Published2023
Admission routes1
Has abstractyes

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