Hierarchy in practice: Multilateral diplomacy and the governance of international security
Bibliographic record
Abstract
Abstract In today’s world, a significant portion of international security politics is conducted through multilateral channels, often from the halls of international organisations such as the United Nations or NATO. This article theorises and empirically documents the production, reproduction, and contestation of local diplomatic hierarchies that practitioners often call ‘international pecking orders’. According to conventional wisdom in IR, the sources of international hierarchies are primarily structural, stemming from the interstate distribution of (material) capabilities. Yet the growing prevalence of multilateral diplomacy in the governance of international security generates distinctive forms of social stratification organised around a struggle for diplomatic competence. As they pursue their instructions and manage security politics, state representatives posted to international organisations make use of the opportunities and constraints of a given situation and compete for rank through the display of practical know-how. The article illustrates this process by looking at how a key set of multilateral practices lend themselves to pecking order dynamics, fromesprit de corpsto reporting through brokering. By taking the multilateralisation of security politics seriously, the article shows that international hierarchy, far from an unobservable reality, is actually part of parcel of each and every practice that makes the world go round.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.075 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".