Book Review: Canada Among Nations 2023: Twenty-First Century National Security HillmerNormanLagasséPhilippeRigbyVincent, eds.Canada Among Nations 2023: Twenty-First Century National SecurityPalgrave Macmillan, 2024, US$109.99
Bibliographic record
Abstract
DonaldTrump's recent assertion that Canada should be absorbed into the United States (US) as its "fifty-first state" has reignited discussions on Canadian sovereignty and Canada's security policy. 1 The outright dismissal of Trump's bold proposal by former prime minister Justin Trudeau, alongside strong rejections from government officials and others across party lines, reflects Canada's firm commitment to its sovereignty.2 However, this episode points to a broader reality: Canada's security environment has become increasingly uncertain, and the country must therefore reassess its strategic priorities.In this context, Canada Among Nations 2023: Twenty-First Century National Security, edited by Norman Hillmer, Philippe Lagassé, and Vincent Rigby, is a timely contribution that offers a critical examination of Canada's security challenges, including the Canada-US relationship, defence spending, cybersecurity, Arctic sovereignty, economic and human security, and democratic resilience.While the book provides valuable scholarship on these issues, it also prompts questions on how Canada should recalibrate its security approach in light of evolving global threats.A hallmark of the Canada Among Nations series, this edition effectively blends academic scholarship with policy analysis.The book's thematic breadth allows it to engage with diverse security concerns, making it an informative resource for policymakers, scholars, and the broader public.At its core, the book warns against
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.061 | 0.031 |
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".