Decentralization is Dead, Long Live Decentralization! Capital City Reform and Political Rights in <scp>K</scp>ampala, <scp>U</scp>ganda
Bibliographic record
Abstract
Abstract African cities are currently experiencing some of the highest population growth rates in the world. Accompanying this growth is constant and continuing pressure on national and local governments to develop political and institutional structures that respond to the multiple demands this demographic change provokes in relation to service delivery, economic development and social wellbeing. In response to these challenges, national governments are reviewing the political and administrative structures of their capital cities, sometimes recentralizing authority. This article examines the reforms to Kampala, capital city of Uganda. The article explains how the national government gradually created the legal conditions necessary to take over the capital city directly, and the political rhetoric and conflict that ensued. We argue that while Kampala had deep internal problems and fared poorly in service delivery, matters were exacerbated by the national government's historical indifference to the city. Moreover, past service delivery failures offered an easy rationale for recentralizing authority. We demonstrate that this recentralization was a well‐planned effort by the central government to regain political control of the capital city. This article illustrates how the national government's recentralization of authority in Kampala is a significant departure from its longstanding policy of democratic decentralization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".