How Far Are Kenya’s Courts? Distance as a Barrier to Justice in Kenya
Bibliographic record
Abstract
Abstract Access to justice for many Kenyans remains a challenge due to the infrastructural and geographic reach of court services throughout the country. This recent development paper presents a spatial proximity analysis that quantifies the distribution of Kenya’s population proximate to the nearest court as an illustrative indicator of access to justice. The results estimate that about 3.5 per cent (1.7 million) of Kenya’s population reside more than 100 kilometres to the nearest physical courthouse, with the average distance to the nearest court per person being 22 kilometres. These considerable travel distances create significant barriers to justice, especially for rural populations, which are further aggravated by limited access to information and low levels of legal literacy. The paper concludes by discussing the current approaches, such as leveraging information and communication technologies, to expand access to court services, improve case information availability and ultimately enhance last-mile justice delivery for Kenyans living in remote regions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".