Changing Norms in Practice: Noninterference in the UN and ASEAN
Bibliographic record
Abstract
Abstract Noninterference is a foundational governance norm for international and regional organizations. In the United Nations and the Association of Southeast Asian Nations, the norm has long undergirded the practice of interstate governance in fundamental ways. However, the noninterference norm has been understood and enacted in disparate ways between these organizations and over time within them. While theories of norm diffusion and contestation have long examined the variable understanding of norms within different contexts, we argue that they are inadequate to analyze cases—like those we examine in this article—where divergent practices do not spring from a conscious desire to contest a norm's relevance, meaning, or requirements. To understand dynamics of norm change, we argue that the growing literature on international practices should be placed in dialogue with both traditional accounts of norm diffusion and existing scholarship on norm contestation. We build on these literatures to offer a novel and productive framework to explore shifting beliefs about the competent enactment of norms within disparate communities over time. Empirically, we center attention on the recent United Nations (UN) peace operation in Côte d'Ivoire and the Association of Southeast Asian Nations (ASEAN) response to the ongoing Rohingya crisis. In each case, we show that divergent interpretations of the noninterference norm are embedded in seemingly mundane practices that have the potential to transform that norm over the long term. We draw on detailed empirical evidence to illustrate the changing practice of the noninterference norm in each case, relying on seventy-six interviews with officials from both organizations.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".