Practicing peace: conflict management in southeast Asia and South America
Bibliographic record
Abstract
Norms and practices have been staples of the constructivist approach to International Relations (IR) since the 1980s. In comparison, little attention has been paid to habits, the relatively thoughtless ways of understanding and structuring relations. Building on the work of scholars such as Emanuel Adler, Vincent Pouliot and Ted Hopf, Practicing peace unearths the dynamics that link norms, habits and practices in shaping the behaviour of actors. Aarie Glas synthesizes them through a new framework of ‘habitual dispositions’ that he deploys to shed light on the decades-long peace that has characterized south-east Asian and south American intraregional relations. The book interrogates why this largely peaceful but conflictual dynamic has taken hold in those regions, where Glas observes that war between illiberal states is an aberration, but ‘violence is not’ (p. 97). The author reasons that their interstate relations are ‘circumscribed by particular and largely given habits and practices of cooperation’, which ‘generate both cooperative relations and a tolerance of limited violence between states’ (p. 3). These contradictory tendencies explain why south American and south-east Asian states engage in community-building despite their protracted disagreements. Thus, regional peace emerges as the result of ‘communities of diplomatic practice’ whose behaviours and conflict management are shaped by their habitual dispositions (p. 21). Habitual dispositions are defined as the ontologically prior predispositions of a bounded group, they are ‘proclivities to see and engage the world in particular ways’ (p. 41). Given that actors are socialized within an institutionalized setting, Glas claims that these habitual dispositions limit their very agency. Moreover, since these dispositions are ‘acquired in and through interaction … within organizational settings’, they are also unnatural and sometimes even bizarre to non-members (p. 49).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.008 |
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".