Extra-judicial killings in democratic Nigeria vis-à-vis the rule of law: an overview
Bibliographic record
Abstract
Generally, extra-judicial killings, summary and arbitrary executions in Nigeria were considered as part of the necessary evil of military dictatorship that dominated the polity of the country from independence to 1999. This is principally because once the military takes over the governance of the country they immediately suspend the Constitution (the supreme law of the land, which, amongst other things, guarantees and safeguards the fundamental human rights of the citizens) from operation. In the absence of the Constitution, the legal protection afforded individuals ceases to exist paving the way for arbitrary rule. However, the perpetration of extra-judicial killings under democratic administration, which is bound to protect and enforce the Constitution, raises a number of questions particularly as to whether the nation's democratic rule is in some way a mere extension of its military style leadership. This paper considers the reason-d'être of the continuation of the involvement of security forces, especially the police, in extra-judicial killings in spite of the existence of democracy in Nigeria; what is the implication of this trend on the rule of law and what measures ought to be taken to reverse it? In this analysis, the paper adopts the doctrinal methodology.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".