Culture of violence or violent Orientalism? Neoliberalisation and imagining the ‘savage other’ in post‐transitional Cambodia
Bibliographic record
Abstract
Violence and authoritarianism continue to resonate in Cambodia’s post‐transitional landscape, leading many scholars, journalists, international donors and non‐governmental organisations alike to posit a ‘culture of violence’ as responsible for the country’s democratic deficit and enduring violence. In contrast, this paper interprets the culture of violence thesis as a sweeping caricature shot through with Orientalist imaginaries, and a problematic discourse that underwrites the process of neoliberalisation. The culture of violence argument is considered to invoke particular imaginative geographies that problematically erase the contingency, fluidity and interconnectedness of the places in which violence occurs. While violence is certainly mediated through both culture and place, following Doreen Massey’s re‐conceptualisation of space and place, this paper understands place not as a confined and isolated unit, but as a relational constellation within the wider experiences of space. This reflection allows us to recognise that any seemingly local, direct or cultural expression of violence is necessarily imbricated in the wider, structural patterns of violence, which in the current moment of political economic orthodoxy increasingly suggests a relationship to neoliberalism. Through the adoption of the culture of violence discourse, neoliberalisation is argued to proceed in the Cambodian context as a ‘civilising’ enterprise, where Cambodians are subsequently imagined as ‘savage others’.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.046 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".