Prisoners’ Access to Justice: Family Support, Prison Legal Education, and Court Proceedings
Bibliographic record
Abstract
This study investigates the extent of prisoners’ legal entitlements as well as how prisoners acquire legal assistance within the prison setup. It is argued that inmates’ legal entitlements within the prison bureaucracy are devoid of the ideal of access to justice. The study used the mixed-method approach in data gathering. For the quantitative aspect, a sample of 300 inmates was used. Simple random and systematic sampling techniques were used to select the respondents. For the qualitative aspect, the following participants were purposively selected: ex-convicts, a paralegal prison officer, a court warrant officer, prison after-care officer, registrars, and relatives of inmates. The analysed data showed that most inmates did not receive family support during their trial before conviction. It was also found that inmates had no access to legal materials due to lack of law libraries, yet received some form of legal education from prison staff. Even though the court proceedings of inmates formed a critical part of their appeal process, a little above half of the inmate population had access to these documents. With the advancement in Information and Communication Technology, it is recommended that all courts should be digitized with relevant logistics and improved infrastructure to smoothen access to case files.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".