Perspectives on the ‘Collapse’ of Angkor and the Khmer Empire
Bibliographic record
Abstract
The apparent decline of Angkor and the Khmer Empire between the 13th to 15th centuries has long been the focus of discussion and debate. Most explanations have focused on warfare, in particular a 1431 invasion by neighbouring Ayutthaya, as the ultimate cause of Angkor’s demise. In this chapter, we offer a critical review of the literature. Drawing on new perspectives arising from the last 20 years of archaeological research, we argue that depopulation of the Angkor region was likely a slow and gradual process and not a sudden or violent event as implied by conventional notions of ‘collapse’. Recent research instead points to a constellation of social, cultural, and environmental factors that contributed to varying degrees to a shift in political power away from the Angkor region in the mid-first millennium CE, accompanied by broad demographic changes that unfolded over centuries.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".