The Failure of the European Union to Address the Threat of Ethnic Cleansing of Armenians in Nagorno-Karabakh
Bibliographic record
Abstract
The ceasefire that ended the 2020 Nagorno-Karabakh War paused the fighting but also precipitated major challenges to human rights and humanitarian issues. Nagorno-Karabakh's status remained unresolved, even as Azerbaijan gained control of large parts of the region. Since then, Azerbaijan’s impunity and ethnic animus against Armenians has created fears of ethnic cleansing. Azerbaijan's 2022-2023 blockade of Nagorno-Karabakh in particular which has deprived the Armenian population of food and medicine, directly contravenes its obligations under the ceasefire. The European Union is striving to negotiate a settlement between Armenia and Azerbaijan but has faced criticism for not substantively addressing these human rights and humanitarian issues. Despite having the political and legal tools, the EU's lack of engagement on these concerns threatens regional stability and undermines its credibility as an ethical international actor. If a mass atrocity occurs while the EU actively seeks a settlement but fails to intervene, it would bear responsibility for the outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".