Detention by Non-State Armed Groups under International Law By Ezequiel Heffes *
Bibliographic record
Abstract
In this iteration of the Review 's “Beyond the Literature” series, we have invited Ezequiel Heffes to introduce his recent book Detention by Non-State Armed Groups under International Law , before then posing a series of questions to Tilman Rodenhäuser, René Provost, Mariana Chacón Lozano and Katharine Fortin, who have agreed to serve as discussants of the book. Tilman Rodenhäuser is a Legal Adviser at the International Committee of the Red Cross (ICRC), with particular expertise in non-State armed groups (NSAGs) and detention. René Provost is the James McGill Professor of Law at McGill University and has written extensively on public international law, including his recent monograph Rebel Courts: The Administration of Justice by Armed Insurgents. 1 Mariana Chacón Lozano has served as the Operational Legal Coordinator for the ICRC in Colombia since October 2020 and has worked for the ICRC since 2011. Katharine Fortin is Associate Professor at the Netherlands Institute of Human Rights within the Faculty of Law, Economics and Governance of Utrecht University. The Review team is grateful to all four discussants, and to Ezequiel, for taking part in this engaging conversation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".