Bibliographic record
Abstract
Canada went through the last great power shift with some soul-searching but little harm. From Confederation to the Second World War, Canada was a British country at heart. 1 Although the presence of a significant French-Canadian minority weakened ties to Britain in the francophone parts of the country, Canada&s;s loyalty to the British Empire was unmistakable. Nowhere was this devotion more evident than in Canada&s;s military affairs. When Britain went to war in 1914, Canada obediently followed. Nor, notwithstanding the increasing influence of a Canadian independence movement in the 1920s and 1930s, did the country&s;s political leaders hesitate to join the United Kingdom&s;s struggle against Nazi Germany in 1939. 2 As Britain&s;s global economic and political importance declined at war&s;s end, however, Canadian decision-makers quickly recognized that their country&s;s fate lay with the new hegemonic power, the United States. Although a few members of the Canadian political elite clung to the British connection for decades after the war, there was no turning back, and especially not in matters of national security. Shared geography, values, and interests ensured that Canada was destined to go through the Cold War, post-Cold War, and post-9/11 eras as one of the United States&s; closest military allies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.006 |
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".