‘Routinizing’ cooperation and changing narratives: The security and prosperity partnership of North America
Bibliographic record
Abstract
March 2005 witnessed the heads of state of Canada, Mexico, and the United States signing the Security and Prosperity Partnership of North America (SPP), a new international framework for cross‐border cooperation in North America. The SPP features two important agendas relevant for the post‐September 11th era: one revolving around national security and the other around economic prosperity. In this paper, we explore how the SPP impacts the dominant narrative of the U.S.‐Canada border. After tracing the historical trajectory of the border, we suggest the emergent narrative eschews the notion that security and trade at the frontier are incompatible and instead maintains that regulatory policies can achieve both through bilateral and trilateral cooperation. The SPP agreement, and related accords such as ‘Smart Borders,’ signals, at least for a time, a new way of perceiving and managing the border. That vision has been recently set back for reasons discussed in this article. This paper analyzes the SPP in several ways based on historical research and interviews conducted with policymakers in Ottawa and Washington, D.C., during 2005. First, we look at the SPP in terms of Milner's International Political Economy framework for international cooperation, arguing for the primacy of national domestic interests. Second, we examine the dynamics of cross‐border bilateral cooperation, focusing on ‘routinization’ and bureaucratic policymaking. Finally, we explore how multidisciplinary scholarship may assist us in determining whether the SPP is a model for other border regions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.050 | 0.052 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".