Bibliographic record
Abstract
The apparatus of cash bail is devised to balance the presumption of innocence with a guarantee of court appearance, which has gradually railed against the existence of socioeconomic and ethnic inequality. This research yields a socio-legal critique of pretrial justice in Mombasa County, Kenya, examining how systemic bail inequities weaken governance credibility and intensify social exclusion. Utilising a multimethod approach, we explored thematic analysis of policy documents, court rulings, and NGO reports; interviews with police officers; regression modelling associating pretrial detention rates (2018–2023) with crime data; GIS-based hotspot mapping; and comparative case studies of bail reform in Germany and Canada. Quantitative results demonstrate that pretrial detention rates have an inverse relationship with community trust (β = –0.45, p < 0.01) and are inseparable from minor offences (3.2 % increase per 10 % rise in detention, p < 0.05), including terrorism recruitment. Logistic decline divulges that detention beyond seventy-two hours significantly raises the probability of reoffending in organised crime (OR = 1.8, p < 0.001). Spatial data analysis reveals coastal counties as points of interest where prolonged detention occurs simultaneously with radical activity. Qualitative intuitions bring to light that ethnic and economic discrimination in police bail decisions wears away civic faith and intensifies grievances that fanatic networks exploit. Considering experiences in other countries, we assert that impartial bail practices, emphasising risk-based assessments, non-monetary release options, and strengthened legal aid, are prerequisites for reinforcing social cohesion and national security. The analysis shows that pretrial justice updates should become part of security planning so bail works as a universal defence mechanism.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".