The Accused Privacy Rights in the Sudanese Legal System
Bibliographic record
Abstract
The purpose of this article is to discuss the rights of the accused person in the Sudanese legal system. Similar with other criminal justice systems, the Sudanese law do provide rights for the accused person to enable him or her to defend him or herself. These rights are considered as the core idea behind the thinking of human rights in the criminal proceedings. However the problematic issue here is to what extent does Sudanese law provide and protect the accused right especially the privacy right. It is also pertinent to balance the law enforcement interest in evidence collection in criminal proceedings with the privacy right of the accused in the Sudanese legal system. We found that there are evidence of privacy right protection on the accused within the Sudanese legal system. The result of this research shows that in Sudan, the privacy right was provided for the first time at the constitutional level in the T1973 Constitution (Articles 42 and 43). It has later received recognition in the 1985 Transitional Constitution (Articles 24 and 30), the 1998 Constitution (Article 29) and the 2005 Interim National Constitution (Article 37). At the statutory level, legislative protection is given to this right in the Penal Code 1991 (Section 166), the Code of Criminal Procedure 1991 (Sections 86 through 95) and the Informatic Offences (Combating) Act 2007 (Sections 16 and 6). The method adopted in this article is a qualitative content legal analysis of primary and secondary data obtained from legislation, case-law and various literature.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".