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 Scholars from different disciplinary backgrounds have studied why perpetrators of international crimes commit these horrendous acts. Initially, historians and psychologists focused on this debate, which was heavily centred on the Second World War. Over the years, scholars with more diverse disciplinary backgrounds, studying a wide array of cases, using both qualitative and quantitative research methods, began to investigate perpetrators of international crimes and terrorism. Recently, this multi- and interdisciplinary debate has become known as perpetrator studies. This is the first book to take stock of the state of the art of this new field of study. It analyses the most prominent theories, methods, and evidence to determine what we know and what we think we know about perpetrators, as well as the ethical implications of gathering this knowledge. It traces the development of perpetrator studies while pushing the boundaries of the field by including contributions from authors from a wide array of disciplines, including criminology, history, law, sociology, psychology, political science, religious studies, and anthropology. Authors cover numerous case studies, including prominent ones such as Nazi Germany, Rwanda, and the former Yugoslavia, but also those that are relatively under-researched and more recent, such as Sri Lanka and the Islamic State, and use various research methods, including but not limited to, trial observations and interviews.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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