State Responsibility and the Right to Personal Security in the drc: A Human Rights Law Perspective
Bibliographic record
Abstract
The right to personal security has been grossly violated in eastern Democratic Republic of Congo for nearly two decades by persistent armed conflicts. Ensuring this right through justice in such a complex context is particularly challenging but feasible. This paper examines whether the drc should be judicially held accountable for violations of the right to personal security. Drawing on case-law, international practice and literature in the field of human rights, the paper demonstrates that under the doctrine of State responsibility the drc has the duty to exercise due diligence in protecting its inhabitants through legislation, precautionary measures and prosecution. It also explains, however, that the drc’s responsibility may not be established under certain mitigating circumstances and factors, such as loss of part of territorial control, the necessity of granting amnesty to some perpetrators of human rights violations and the difficulty of judicially determining the minimum core of the right to personal security. The paper concludes that the possibility of judicially holding the drc accountable for failure to respect its international human rights obligations has been demonstrated and recommends that to be capitalised by competent jurisdictions in order to improve the situation of the right to personal security on the ground.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".