Police violence targeting LGBTIQ+ people in Nigeria: Advancing solutions for a 21st century challenge
Bibliographic record
Abstract
The Government of Nigeria passed the Same-Sex Marriage Prohibition Act (SSMPA) in 2014, emboldening the human rights violations of LGBT Nigerians by state and nonstate actors. Nigerian police enforce morality laws that criminalize same-sex relations, but their role as perpetrators of violence has not been well studied. Using six-year (2014 to 2019) administrative data, this article investigates the severity, prevalence, and typology of police violence and abuse of LGBT Nigerians. Since SSMPA, violence against LGBT Nigerians has risen by 214 percent. Survivors frequently report arbitrary arrest and unlawful detention, invasion of privacy, physical assault and battery, and blackmail/extortion. This study is the first to present serial, cross-sectional findings of LGBT Nigerians’ experience with the police. Available administrative reports and data were synthesized to produce a general picture of the situation on the ground. Findings point to actionable social and policy recommendations that can be taken to promote police accountability and improve police-LGBT community relations.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".