Caught in the middle : border communities in an era of globalization
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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