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Record W4281615721 · doi:10.1080/07393148.2022.2079319

The Limits of Igbt Rights in Rwanda: International Action and Domestic Erasure

2022· article· en· W4281615721 on OpenAlexaff
Emma Paszat

Bibliographic record

VenueNew Political Science · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman rightsGovernment (linguistics)Political scienceState (computer science)Power (physics)Gender studiesSociologyPolitical economyLaw

Abstract

fetched live from OpenAlex

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.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.044
GPT teacher head0.365
Teacher spread0.321 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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