Beyond the state of play: Establishing a duty of non-State armed groups to provide reparations
Bibliographic record
Abstract
Abstract This article examines whether and how non-State armed groups, as distinct entities, might be required to provide reparations for their violations of international humanitarian law. It shows that the possibility of holding armed groups to reparations is marked by uncertainty in international law. This complex question calls for clarification. In building on these observations, the article explores how the duty to provide reparations by armed groups could be operationalized as a matter of lex ferenda. This exercise involves examining how such a duty could be conceptualized and put into practice. From this discussion, a multi-faceted proposal emerges, which draws upon existing approaches in international law and responds to the particular challenges presented by armed groups. The article ends by considering the implications of the proposal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.060 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".