Middle-power internationalism in-between European ‘paradise’ and American ‘power’? Canada’s political role in an age of Trumpism and Brexit
Bibliographic record
Abstract
Hyper forms of globalization have contributed to the diffusion and de-institutionalization of state power (Chin and Mittelman, 1997) and to growing populism, nationalism, and authoritarianism in Europe thathave questioned the liberal international order’s effectiveness, legitimacy and authority. What has come under threat is not only the order itself, but the economic prosperity, security, peace, and normative foundations that has nurtured it. In this context of a emerging world order we examine what function so-called middle powers on both sides of the Atlantic could play?While often overseen in recent years, middle powers are important units of analysis to study because during the times of the ‘old’ order in the aftermath of WWII they had benefitted most of the stable liberal international order, and as a result they have the most to lose today in case that order changes dramatically or even disappears. In looking back at middle power’s presence at creation of the liberal international world order in the aftermath of WWII, we suggest, helps us to comprehend what function middle powers could play in this current wave of changing transatlantic orders. Especially their intraalliance bridgebuilding function is important in this regard that in the past helped to balance the interests of the major powers. Canada is discussed as a case study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".