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
Abstract The Oxford Handbook on Atrocity Crimes consolidates and further develops the evolving field of atrocity studies by combining major mono-, inter-, and multidisciplinary research on atrocity crimes in one volume encompassing contributions of leading scholars. Atrocity crimes—war crimes, crimes against humanity, and genocide—are manifestations of large-scale and systematic criminality committed within specific political, ideological, and societal contexts. These crimes are typically committed by multiple actors against a large number of victims who suffer far-reaching consequences. Scholars studying mass atrocities are scattered not only across disciplines—such as international (criminal) law, international relations, criminology, political science, psychology, sociology, history, anthropology, and demography—but also across the topic-related fields, which are by definition multi- and interdisciplinary but are typically limited to a particular category or aspect of atrocity crimes. This Handbook brings together these strands of scholarship and interrogates atrocity crimes as an overarching category of criminality, while simultaneously recognizing and theorizing differences among the individual constitutive categories. The Handbook covers topics related to the etiology and causes of atrocities, the actors involved, the victims of atrocity crimes and related harms, the reactions to atrocity crimes, and in-depth case studies of understudied situations of war crimes, crimes against humanity, and genocide.
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.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it