Uganda's 2016 elections: Not even faking it anymore
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Uganda's 2016 elections may have been the most competitive in the country's long struggle for democracy, but almost everything about this election was a foregone conclusion: nobody expected a free and fair ballot. Nobody expected President Museveni to lose. And nobody was surprised when ‘the Old Man’, Uganda's ruler for the last 30 years, was declared the undisputed winner with 60.6 percent of the vote. Even the post-election condemnations by the donors that have so generously funded Uganda to the tune of US$1,658 million annually were predictable;1 the European Union's election monitors described ‘an atmosphere of intimidation’, while the United States noted ‘irregularities and official conduct that are deeply inconsistent with international standards’.2 While voters turned out in great numbers, they, like the donors, have become sceptical about elections and doubt that Museveni could ever be declared a loser in a contest where he appoints the referees (electoral commissioners) and commands the security apparatus.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it