A conceptual limbo of genocide: Russian rhetoric, mass atrocities in Ukraine, and the current definition’s limits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The presence of multiple, semantically opposed usages of the term “genocide” not only poses a challenge for legally defining Russia’s atrocities in Ukraine, but also exemplifies the constraints of international law in dealing with mass civilian destruction in the twenty-first century. Indeed, despite widespread evidence of Russia’s genocidal behaviour, few scholars and lawyers believe it would be legally possible to prove Russia’s genocide in Ukraine. Nonetheless, given the powerful public image of genocide as the “crime of crimes,” political usage of the term by politicians, activists, and the general public has intensified since the beginning of Russia’s 2022 invasion with the hope of attracting global attention to (and ceasing) Russia’s atrocities. This paper provides some preliminary observations on how and why the concept of genocide has proven to be effective in fuelling civilian destruction rather than preventing it during the invasion. It first traces how Russia’s controversial, two-pronged rhetoric of genocide has evolved over the initial months of the invasion. It then examines Russia’s atrocities and the difficulties of classifying them as genocide.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it