The Relationship between the Constitutional Right to Silence and Confessions in Nigeria
Bibliographic record
Abstract
Abstract The extraction of confessions from suspects under torture by security agents is a notorious fact in Nigeria. Ironically, the Constitution of the country guarantees a right to silence, but courts in Nigeria predicate the admissibility of confessions on the common law-based Judges Rules and Evidence Act 2011 without linking it to the constitutionally guaranteed right to silence. This article reviews the legal rules on the admissibility of confessions in Nigeria and contends that without attaching constitutional flavour to the admissibility of confessions, the legislature and the courts in Nigeria unwittingly water the ground for the systemic extraction of confession from suspects in custody in Nigeria. The article suggests that the courts in the country consider the implication of the guarantee of the right to silence in the country’s constitution in the determination of the admissibility of confessions to promote fair trial in criminal cases in the country.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".