North American Borders in Comparative Perspective during COVID Times
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After the partial closure of the Canada-U.S. and Mexico-U.S. borders due to the COVID-19 pandemic in 2020, and considering a new vision of border management that has been evolving since 1994, the face of North American borders is changing today. The future of the Canada-U.S. border will essentially differ from that of the Mexico-U.S. border. The first one might become more tenuous, while the border that divides Mexico and the United States will be probably fortified. Such a divergence is directly connected to the structural inequalities that characterize this region magnified by the pandemic. The present article examines North American borders in comparative perspective during COVID times. This comparative exercise focuses on four main thematic areas: trade, human mobility/migration, security and public health.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it