Why Middle Power Coalition Strategies Fail Against Great Powers
Bibliographic record
Abstract
This article critically examines the limitations of middle power coalition strategies in countering great power influence, particularly in the context of U.S. economic nationalism and China’s strategic assertiveness. Drawing on historical and contemporary examples—including the Cairns Group, MIKTA, and the proposed JACK coalition (Japan, Australia, Canada, South Korea)—the authors argue that structural asymmetries, economic dependencies, and strategic defection undermine the viability of sustained middle power cooperation. The failure of coordinated responses to U.S. tariff threats illustrates the prisoner’s dilemma dynamics that incentivize individual accommodation over collective resistance. The article contends that middle powers must abandon idealistic coalition-building in favor of pragmatic, issue-specific cooperation and deeper integration within existing alliance structures. By aligning with hegemonic frameworks while negotiating implementation details, middle powers can preserve strategic relevance without directly challenging dominant powers. This approach offers a more realistic pathway for maintaining liberal international order and managing great power competition.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".