ISSUES ACROSS THE INTERNATIONAL
Bibliographic record
Abstract
Integration of disease surveillance efforts across the international borders of the United States presents complex challenges and significant implications for national security against both natural epidemics and biological attack. To explore these issues, we conducted qualitative studies of surveillance of communicable diseases across the Mexico /Texas border and the Michigan/Canada border. We conducted a series of semi-structured interviews with public health officials and physicians responsible for surveillance along these borders. The interviews were audio- taped, transcribed, and then coded for themes that emerged from these data. The findings for the Mexico border indicate that the most important issues are differences in standards of health care (including diagnostic tests and treatment protocols), communication pathways, and information technology between the two countries. Accurate communication about diseases cannot take place while standards are different. Another key finding was the importance of bi-national organizations in coordinating a variety of health issues across these complex borders. Although bi-national organizations have functioned for a number
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".