Satellites, Plasmas and Law: The Role of TeleCourt in Changing Conceptions of Justice and Authority in Ethiopia
Bibliographic record
Abstract
An ambitious experiment in the ICT and justice sector is underway in Ethiopia. As part of an effort to improve service delivery and the responsiveness of the state, the Ethiopian government has created 'TeleCourt,' a system that allows trials to take place between remote areas and regional or federal courts through videoconferencing and a satellite Internet connection. This article is the first to analyze how TeleCourt operates, with a particular focus on the perspectives of end-users, those who have had first-hand experience of how 'justice at a distance' actually works. The findings suggest general satisfaction with the savings - both in terms of financial burden and time costs that are often incurred when travelling to trials - which TeleCourt allows. As the system improves ways to provide justice to the grassroots, in line with the government's commitment towards peasants, this must also be considered in the context of the Ethiopian government's growing efforts to use law to curb political dissent. This is indicative of a broader tendency of selectively adopting and reshaping ICTs and extending them to the poorest people in Ethiopia in order to support the functioning of the state, while other uses of ICTs that are seen as potentially destabilizing are discouraged or forbidden.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".