Bibliographic record
Abstract
The nation-states that make up the Association of Southeast Asian Nations are widely described to be peaceful in their relations with each other, so much so that scholars have referred to the Association of Southeast Asian Nations’ “long peace.” While it is true that war eludes the region, interstate militarized disputes remain a persistent feature. How can we account for the absence of war between Association of Southeast Asian Nations members in light of persistent militarized disputes? To address this question, this article builds on the emerging International Relations literature on habits and practice in interstate relations. I develop a framework centred on the habitual dispositions of communities of practitioners that focuses on the unreflexive cognitive and behavioural qualities of regional relations. These “habits of peace” circumscribe thinking and behaviour among the Association of Southeast Asian Nations’ state practitioners. Specifically, they have led to a toleration of limited violence among Association of Southeast Asian Nations member states. After tracing the existence of these habitual qualities of relations, I demonstrate their effects on regional crisis response, which makes possible community building and maintenance alongside considerable levels of interstate violence. I explore this through an in-depth analysis of the regional response to the 2011 Preah Vihear crisis between Cambodia and Thailand.
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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 | 0.002 | 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 | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".