Illegal: The Recourse to Force to Recover Occupied Territory and the Second Nagorno-Karabakh War
Bibliographic record
Abstract
Abstract The Second Nagorno-Karabakh War, and its lingering aftermath, have put the fundamental and largely unsettled question of the jus ad bellum in the spotlight: when part of one state’s territory is occupied by another state for a prolonged duration, can the former state have lawful recourse to military force to recover its land? Prior to the 2020 conflict, the Nagorno-Karabakh region was widely regarded as belonging de jure to Azerbaijan, but as being unlawfully occupied – for more than 25 years – by Armenia. Accordingly, was Azerbaijan entitled to claim self-defence to lawfully recover it, even though the pre-2020 territorial status quo in the region had existed for more than a quarter of a century? In addition, could Azerbaijan invoke self-defence again in the near or distant future to recover those remaining parts of territory that continue to be outside of its control now that a new ceasefire is being enforced in the region? The answers to these questions have ramifications that extend far beyond the Caucasus, being of relevance for a wide range of pending conflicts around the globe. Upon closer scrutiny, the present authors believe that a negative answer is in order.
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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 | 0.001 | 0.002 |
| 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 | 0.016 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".