The Limits of Igbt Rights in Rwanda: International Action and Domestic Erasure
Bibliographic record
Abstract
Abstract When African countries and lgbt people are written about, a lot of the focus is on elites’ use of politicized homophobias to target lgbt people. However, there has been significantly less attention paid to countries where governments do not politicize homophobia, but also do not legislate for Igbt people’s human rights. Rwanda is one such country where senior government officials, including the President, have declined to politicize homophobia, even whilst many of their neighbours were doing so. However, lgbt activists report that discrimination remains widespread in the country, including from state actors. Therefore, it is surprising that at the United Nations Rwanda has increasingly although not universally moved to supporting Igbt rights positions. Rather than assuming Rwanda has adopted these differing positions for coercive reasons due to donor pressure or because of officials’ personal beliefs, I argue the Rwandan government’s approach is a strategic recognition of the importance of Global South actors supporting lgbt rights. Rwanda’s government does more internationally than domestically, but this is still enough to differentiate the country from its neighbours, and this gives it power in the international system as a Global South government that is willing to support lgbt rights internationally.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".