Provide for the Common Defense: Updating the Canada-United States Security Relationship
Bibliographic record
Abstract
Time to revisit and upgrade the Canada-United States defense relationship. New threats: the Homeland Defense paradigm The Homeland Defense concept is that the United States needs to develop new defenses against threats to its own people and economy, in contradistinction to the need for force projection and pre-emptive strikes that placed the most likely conflicts and uses of U.S. military power outside our borders for most of the 20th century. In the post Cold War, the U.S. military’s advanced weaponry, tactics and sheer size are unmatched, and there are therefore few scenarios in which the United States is likely to face a large-scale attack or invasion. This has led U.S. defense planners to consider the greater likelihood of asymmetrical warfare – that is, an attack from a smaller force designed to hit at weak points in U.S. defenses and undermine American resolve. Such a “David against Goliath ” situation could take the shape of a terrorist attack on civilians or infrastructure within the United States, or against a symbolic target linked to the United States. This kind of strike, as witnessed recently in Aden against the U.S.S. Cole, can have a psychological impact on Americans that goes far beyond its military value and can be
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.028 | 0.012 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 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".