Controlling consent, dealing with dissent, and planting misinformation: how the Museveni regime stifled Bobi Wine's youth movement in Uganda
Bibliographic record
Abstract
After Uganda embraced electoral democracy in 1996, a trend emerged where Ugandans between 18 and 35 do not turn out to vote in large numbers. Although the country is astonishingly young, Ugandan youth had long shown little interest in politics and were less likely to run for public positions compared to older Ugandans. However, the meteoric rise of Bobi Wine has inspired many young Ugandans to engage in local and national politics as first-time voters, party members, cash contributors, protesters and foot soldiers. This article explains how the rise of Robert Kyagulanyi, also known as Bobi Wine, a popular singer turned opponent of President Museveni, has inspired an upsurge in youth political participation in Uganda. The article posits that, to contain a growing youth-led movement, the Museveni regime largely relied on coercion, which has thus far proved counterproductive. The more coercion is employed the more it aggravates the backlash from and determination of young Ugandans to mobilise against Museveni’s rule. The response from the regime has been a mixture of repression, disinformation and disenfranchisement of young voters.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.028 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".