Bibliographic record
Abstract
O ne of the Canadian government's political and economic priorities has always been its bilateral relations with the United States.In the last decade, however, it has incorporated another issue regarding its biggest trade partner: security, specifically in the framework of the Security and Prosperity Partnership of North America (SPP).Undoubtedly, this alliance reaffirms Canada's political and economic relationship with the U.S. government, which is alive and well despite being quite asymmetrical.1 Both political and economic forces have managed to remain stable, not only because they share one of the longest borders in the world, where 80 percent of the Canadian population lives and which includes the Great Lakes, one of the world's biggest reserves of fresh water (18 percent), but also because of the dynamism of trade.The proximity, the language, growing investments, Canada's natural resources, etc., have fostered among other things very dynamic trade along the world's longest non-militarized border.2 Naturally, it has also forged ample cooperation with Canada's southern neighbor through different accords like the 2001 intelligent border agreement, the establishment of the Binational Planning Group in 2002 and the 2005 joint declaration about common security and prosperity, among others.3 The main points on the bilateral agenda cluster around three key issues for the two economies: defense, trade and development.This ensures that efforts are not diluted in too 97
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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 | 0.003 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.001 |
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".