Property Loss and Cultural Heritage Restoration in the Aftermath of Genocide: Understanding Harm and Conceptualising Repair
Bibliographic record
Abstract
Abstract This article seeks to contribute a ‘thicker’ understanding of the harm caused by the destruction of cultural heritage and the means through which that harm can be redressed. It analyses attacks on property of local significance to the Cham, an Islamic group subjected to religious persecution and genocide during the Khmer Rouge regime in Cambodia. Using Bernadette Atuahene’s property-loss concepts of ‘dignity takings’ and ‘dignity restoration,’ the article links the loss of property associated with the group’s cultural heritage to experiences of dehumanization, infantilization and community destruction. The article explores how responses to the Cham’s loss of cultural heritage have been iterative, at times unintentional and ultimately unsuccessful in redressing the full impacts of the loss. It stresses the importance of moving beyond a focus on specific restitution to develop a spectrum of interventions which reaffirm victims’ humanity, reinforce their agency and allow them to reconnect meaningfully with their heritage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.074 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".