Is a new definition required for travelers who visit friends and relatives?
Bibliographic record
Abstract
We appreciate the Editorial by Dr Paul Arguin and its contribution to the discussion of the proposed definition of Visiting Friends and Relatives (VFR) traveler 1 following publication of the two articles summarizing the deliberations of an expert committee. 2,3 Nevertheless, we continue to consider a new definition for the VFR traveler necessary. We have found no common definition for VFR; the editorial lists three distinct definitions from three authorities [ie, Centers for Disease Control and Prevention (CDC), the World Health Organization, and the “major textbook” on travel medicine] which all differ. The common thread included in these definitions is use of immigrant status, race and/or ethnicity to classify individuals because the frequent view is that these factors predict a “complex set of behaviours.” Race and ethnicity, however, are poor predictors for behaviors and/or health beliefs of individuals. In this increasingly mobile and culturally, ethnically, and racially intertwined world, a large number, perhaps a majority, of travelers cannot be classified on the basis of their immigrant status and ethnicity. It is rather essential that each individual's preexisting health knowledge and beliefs be assessed during a travel visit.
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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 | 0.011 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.046 | 0.054 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".