Caught in the middle : border communities in an era of globalization
Bibliographic record
Abstract
In a world with tremendous growth of goods and people flowing across borders, little attention has been paid to the communities through which these goods and people pass and in which people live. Caught in the Middle provides a fascinating look into the inner workings and realities of border communities along five international borders --United States-Canada, United States-Mexico, Germany-Poland, Russia-China, and Russia-Kazakhstan. The volume focuses on innovative cross-border initiatives that contribute unique insights into the daily lives and local perspectives of border communities. Also, it presents a better understanding of the border management issues faced by countries worldwide, as well as of the nature of relationships between federal and local governments, community leaders, government officials, and local communities. By shedding light on existing best practices and providing comparative analyses of the challenges and opportunities faced by communities, Caught in the Middle provides valuable lessons for policy makers, governments, and researchers alike.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".