Rethinking ‘middle powers’ as a category of practice: stratification, ambiguity, and power
Bibliographic record
Abstract
Abstract Scholars have attempted to theorise the social structure of the international system from the perspective of the ‘middle powers’ for decades. However, scholars have struggled to agree on the essential dispositional characteristics of this category of actors, stunting theoretical progress. Drawing on sociological and literary approaches to the rhetoric of the ‘middle class’ in domestic societies, this article shifts the terms of this debate away from asking who the ‘middle powers’ are or what their ‘essence’ is , to ask what actors do with the term in practice. Combining this with and contributing to scholarship on hierarchy in international relations, I recast ‘middle powers’ as a category of practice and argue that one of the term's main uses is to differentiate certain status-anxious states – that hold no real prospect of achieving great power status – from ‘small states’ that occupy the lowest stratum of stratification within the ‘grading of powers’. Following an illustrative case study of Australian and Canadian attempts to establish the ‘middle power’ category in the 1940s, the article then outlines the contributions of the argument for the study of status and hierarchy in world politics.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.141 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".