When security community meets balance of power: overlapping regional mechanisms of security governance
Bibliographic record
Abstract
. By now arguments about the varieties of international order abound in International Relations. These disputes include arguments about the security mechanisms, institutions, and practices that sustain international orders, including balance of power and alliances, hegemony, security regimes based on regional or global institutions, public, private, and hybrid security networks, as well as different kinds of security communities. The way these orders coexist across time and space, however, has not been adequately theorised. In this article we seek to show (A) that, while analytically and normatively distinct, radically different orders, and in particular the security systems of governance on which they are based (such as balance of power and security community), often coexist or overlap in political discourse and practice. (B) We will attempt to demonstrate that the overlap of security governance systems may have important theoretical and empirical consequences: First, theoretically our argument sees ‘balance of power’ and ‘security community’ not only as analytically distinct structures of security orders, but focuses on them specifically as mechanisms based on a distinct mixture of practices. Second, this move opens up the possibility of a complex (perhaps, as John Ruggie called it, a ‘multiperspectival’) vision of regional security governance. Third, our argument may be able to inform new empirical research on the overlap of several security governance systems and the practices on which they are based. […]
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.043 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".