Special Courts as Nigerian Criminal Justice Response to the Plight of Awaiting Trial Inmates in Ebonyi State, Nigeria
Bibliographic record
Abstract
This study looks at how using special courts can provide succor to the plight of awaiting trial inmates in Ebonyi state, Nigeria. The study adopted quantitative and qualitative research methods, with a sample of 1,498 respondents comprising 617 police officers, 623 awaiting-trial inmates, 113 court staff, and 145 prison officers drawn from Ebonyi State. Purposive and Multi-stage sampling techniques were used to reach the respondents. The quantitative data was descriptively analyzed using percentages and charts, while a thematic method of analysis was employed in the qualitative data. The findings revealed that, while there has been an uptick in awaiting trial problems, there is no meaningful provision to address them, despite the existence of provisions within the Nigerian legal framework. The article calls for the creation of special courts that are equipped to address peculiar crime cases in a more effective and faster manner. These courts are better poised to address the peculiarities of special cases and pass better and faster judgments.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".