From Counterterrorism to Deterrence: The Evolution of Canada’s and Italy’s Defense Postures
Bibliographic record
Abstract
How do US democratic allies perceive and adapt to the multiple challenges associated with the rise of multipolarity and the return of major war in Europe? This article examines how two US allies—Canada and Italy—have adapted their defense postures from the professed beginning of the shift in the balance of power in 2008 to Russia’s full-scale invasion of Ukraine in 2022. More specifically, it provides a comparison of three major dimensions of defense postures: threat perceptions, patterns of foreign military deployments, and military expenditures. This article argues that both allies have undertaken a shift from liberal interventionism towards a defense posture increasingly geared towards deterrence vis-à-vis Russia. However, the shift did not occur analogously and simultaneously, as the two allies’ adjustment was shaped by differing levels of domestic inter-party contestation. This article highlights the extent to which US allies’ international security adaptation follows political-party threat perceptions more than the traditional left-right dichotomy. Shared inter-party threat perceptions of great power revisionism are found to shape the degree of defense policy adaptation toward 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".