Bibliographic record
Abstract
September 11, 2001 marked the beginning of a new era of security imperatives for many countries. The border between Canada and the United States suddenly emerged from relative obscurity to become a focus of constant attention by media, federal and state/provincial governments on both sides of the boundary, and the public at large. This book provides a comprehensive examination of the Canada-USA border in its 21st century form, placing it within the context of border and borderlands theory, globalization and the changing geopolitical dialogue. It argues that this border has been reinvented as a 'state of the art', technology-steeped crossing system, while the image of the border has been engineered to appear consistent with the 'friendly' border of the past. It shows how a border can evolve to a heightened level of security and yet continue to function well, sustaining the massive flow of trade. It argues whether, in doing so, the US-Canada border offers a model for future borderlands. Although this model is still evolving and still aspires toward better management practices, the template may prove useful, not only for North America, but also in conflict border zones as well as the meshed border regions of the EU, Africa's artificial line boundaries and other global situations.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".