Bibliographic record
Abstract
This chapter explores the concept of North America through various indigenous, literary, political, cultural, environmental, economic, and historical perspectives. It also focuses on North America as a region, with different borderlands separating Canada, the United States and Mexico, and shifting attitudes towards sovereignty, fluctuating between continental integration post-North American Free Trade Agreement (NAFTA), and the hardened borders and securitization after the 2001 terrorist attacks on the United States. Asymmetries of power related to culture, security, and economics also shape institutions and ideas of a potential “project North America.” Perhaps most importantly, however, the introduction highlights an “epistemic desert” regarding the study of North America, tied to a lack of funding and limited trilateral intellectual engagement, especially in contrast to Europe. This volume is an attempt to bring North American scholars and practitioners together to partially address these shortcomings. What it identifies are market realities and incremental institutional changes that promote closer ties, but also many social, political, economic, environmental, cultural, and nationalist boundaries that continue to serve as barriers to cooperation and integration. To explore these challenges, the introduction and volume focus on comparisons with other regional experiments, the impact of NAFTA, and the relationship between trade and security, both in terms of cooperation and in a normative context.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".