Bibliographic record
Abstract
Organization (WHO) declared Zika a "Public Health Emergency of International Concern," based on growing evidence that women who have the Zika virus during pregnancy are at increased risk of having their children born with microcephaly. 1 On November 20, 2016, while this letter was in press, WHO declared that Zika was no longer a Public Health Emergency of International Concern because the link between Zika and microcephaly has been found to be robust and in need of a longer-term global strategy.2,3 To stem the spread of Zika, travel-related policies have been issued by federal public health agencies and are still in place, advising in particular pregnant women or women trying to become pregnant not to travel to areas with ongoing Zika virus outbreaks.4 These policies may have the unintended result of decreasing women's input on the planning, implementation, and evaluation of global health projects.This is important to the field as a whole, because gender-balanced teams are crucial for implementing effective global health programs and projects.As a woman global health scholar and practitioner, I reflect on potential negative impacts of these Zika travel policies and recommend actions. ZIKA TRAVEL POLICY AND GLOBAL HEALTHIn the United States, the Centers for Disease Control and Prevention (CDC) announced, on January 15, 2016, a travel alert for 14 Zika-affected countries in Latin America, the most economically unequal region in the world 5 with considerable and persistent global health challenges.This region continues to be a high priority for health donors such as the U.S. Agency for International Development.6 The travel policy recommends special precautions for women who are pregnant or trying to become pregnant, including considering postponing travel to these destinations.7 The Zika travel policy is unusual in its sex specificity: It recommends that women, and not men, should potentially avoid travel to Latin America.In fact, men can also become infected with Zika, which is sexually transmissible to their partners, but this scenario has not been addressed in the travel policies directly.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.023 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".