Bibliographic record
Abstract
The term “genocide” derives from the Greek word genos (“race”) and cide (from the Latin occidere, meaning “to kill”). It was introduced in 1944 by the jurist Raphael Lemkin and refers to a type of mass killing widely regarded as the most egregious of crimes. Lemkin identified the phenomenon itself decades earlier, in the massacre of the Armenians in Turkey. In 1921 he insisted that the doctrine of state sovereignty was not a license to kill millions of innocent people, and he agitated in the 1930s for international support from criminal lawyers to address the question of what to do about murderous regimes. Finally, in the 1940s, in the aftermath of war and Nazi atrocities, he and other jurists successfully pressed to get genocide recognized as a crime in international law. The definition provided by the 1948 Genocide Convention registered the considerable anxiety Lemkin felt about planned and systematic state persecution and destruction of racial and religious groups. Although he had also voiced concerns about criminal mistreatment of “social” groups, the General Assembly of the United Nations, under pressure from the Soviet Union, retreated from what looked like a possibility of including “political and other groups” in the list of potential victims.
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 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".