The contribution of a gender perspective to the understanding of migrants’ health: Table 1
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 2005 women represented approximately half of all 190 million international migrants worldwide. This paper addresses the need to integrate a gender perspective into epidemiological studies on migration and health, outlines conceptual gaps and discusses some methodological problems. We mainly consider the international voluntary migrant. Women may emigrate as wives or as workers in a labour market in which they face double segregation, both as migrants and as women. We highlight migrant women's heightened vulnerability to situations of violence, as well as important gaps in our knowledge of the possible differential health effects of factors such as poverty, unemployment, social networks and support, discrimination, health behaviours and use of services. We provide an overview of the problems of characterising migrant populations in the health information systems, and of possible biases in the health effects caused by failure to take the triple dimension of gender, social class and ethnicity into account.
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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 | 0.073 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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