Building Fences Together: The EU's Lessons for the U.S.-Canada Perimeter Security Plan
Bibliographic record
Abstract
After the events of September 11, 2001, the United States and Canada enacted policies aimed at increasing the effectiveness of joint measures between the two countries. The latest joint policy, calling for unprecedented integration of U.S. and Canadian apparatuses, is known as the security plan. On December 7, 2011, the U.S. and Canadian governments released a Joint Action Plan plotting a path toward this further integration of the two countries' national policies. However, there are a number of concerns regarding the various facets of the plan. Is it advisable to integrate national functions? What do the countries stand to gain by integrating? Most importantly, can integration work? The example of the European Union's common foreign and policy indicates that regional partnerships can indeed work. Analysis of the development of the European Union's policy identifies the crucial areas where partners must collaborate. Application of the lessons learned from the European Union's experience will enable the United States and Canada to adroitly navigate the complications of integrating their policies. The analysis and application of these lessons should lead to a strong and stable perimeter that will serve the interests of both countries. Love your neighbor as yourself; but don't take down the fence. Carl Sandburg' Matthew K. Grashoff anticipates receiving his J.D. from Case Western Reserve University School of Law in May 2013. 1. Carl Sandburg Quotes, THINK ExIsT.coM, http://thinkexist.com/ quotation/love-your neighbor as-yourself-but donttake/175650.html (last visited Oct. 7, 2012). 1 Grashoff: Building Fences Together: The EU's Lessons for the U.S.-Canada Pe Published by Case Western Reserve University School of Law Scholarly Commons, 2012 CANADA-UNITED STATES LAW JOURNAL VOLUME 37 ISSUE 2 -2012 Building Fences Together
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.031 | 0.013 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 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".