“A Disturbing Portent of Future Harm”? Attacks on Cultural Heritage, Atrocity Crimes, and the Problem of Prevention
Bibliographic record
Abstract
Preventing atrocities has garnered significant scholarly and practitioner attention. In 2014, the UN Office of Genocide Prevention issued a Framework of Analysis of Atrocity Crimes listing 14 risk factors and 143 indicators to support risk analysis and early action. Cognizant that conflicts regularly include deliberate attacks on cultural heritage, the Framework identifies fourteen indicators that pertain to culture and cultural heritage. Five years after the Framework’s release, Simon Adams decried the international community’s ineffectiveness at translating early warning into practical action with respect to cultural heritage. Instead of focusing on lack of political will or obstructionism—an obstructionism that led to a certain blindness in the international legal framework of the intimate relationship between cultural and human destruction—this article observes that definitional, temporal, and scalar ambiguities in the Framework likewise contribute to translation problems. The essay adopts a human rights framing of cultural heritage to help mitigate some of those problems, especially as it broadens the array of relevant agents to work proactively to avert and prevent tensions from erupting into violence, and sometimes reactively when situations devolve.
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".