Explaining the Comparatively Less Robust Human Rights Impact of the ECOWAS Court on Legislative and Judicial Decision-making, Process, and Action in Nigeria
Bibliographic record
Abstract
Abstract This article outlines and tackles two inter-related puzzles regarding the comparatively much less robust human rights impact that the ECOWAS Court (in effect, West Africa’s international human rights court) has had on the generally more democratic legislative/judicial branch of decision-making and action in Nigeria vis-à-vis the generally more authoritarian executive branch within Nigeria, the country that is the source of most of the cases filed before the court. The article then discusses and analyzes the examples and extent of the court’s human rights impact on legislative/judicial branch decision-making and action in that key country. This is followed by the development of a set of analytical, multi-factorial, explanations for the two inter-connected puzzles that animate the enquiry in this article. In the end, the article argues that several factors have combined to produce the comparatively much less robust human rights impact that the ECOWAS Court has had on domestic legislative and judicial decision-making, process, and action in Nigeria, through restricting the extent to which the latter could mobilize more robustly the court’s human rights-relevant processes and rulings.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".