A comparative legal analysis of human rights norms and institutions in Nigeria and Canada, with a particular focus on the issue of unlawful arrest and detention
Bibliographic record
Abstract
Since the establishment of the National Human Rights Commission (“NHRC”) of Nigeria, high expectations that the commission will ensure effective protection of human rights have dwindled due to pervasive human rights violations. Of great concern is that the security agencies in Nigeria, particularly the police who are empowered under the law to ensure obedience to law and order, often engage in unlawful arrest and detention. This thesis offers a comparative legal analysis of human rights norms and institutions in Nigeria and Canada, with a particular focus on the issue of unlawful arrest and detention. It argues that NHRCs have been unable to effectively address unlawful arrests and detentions by the Nigeria police, and that Nigeria can borrow from Canada’s human rights system to improve her human rights institutions and practices, especially with regard to arrest and detention. It also offers recommendations from the lessons drawn from Canada’s human rights system.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".