Taking action to rebuild: violence experienced by migrants consulting Doctors of the World in Europe
Bibliographic record
Abstract
Background Since 2006, the Doctors of the World (DOW) International Network Observatory has been conducting multicenter surveys in Europe among vulnerable people – the vast majority of whom are immigrants – who make use of of its national programs, in order to describe their social and health-related characteristics and access to care, with the goal of informing the public authorities and European institutions and bringing about positive changes. Materials and Methods A cross-sectional analysis of routine data collected from 23,341 patients who availed themselves of the MdM clinics in 26 cities in 11 countries in 2014 (Belgium, Canada, France, Germany Greece, the Netherlands, Spain, Sweden, Switzerland, Turkey and United Kingdom), 1809 of whom were interviewed about the violence they may have experienced in their lives. For foreign citizens, note was taken of when the violence occurred: in their country of origin, during migration journey, or in the host country. Results 84.4% of the interviewees had experienced one or more episodes of violence. 52.1% had lived in a country at war, 43.3% had been threatened physically or imprisoned for their ideas, 39.1% had suffered violence at the hands of the police or armed forces, 42.1% had been subjected to psychological violence, and 14.9% had been victims of rape (24.1% of the women and 5.4% of the men). 35.7% had suffered from hunger. It was also found that 9.8% had experienced violence after arriving in Europe, in particular, hunger (40.8%) or confiscation of their identity papers and money (37.1%). One in 5 rapes was committed after they had arrived in Europe. Discussion The high rate of experiences of violence confirms the importance in primary care to systematically ask patients, especially migrants, about violence, given its consequences, including its long-term consequences. In the vast majority of cases, their management is a primary health care concern. Key messages Violence experiences are very frequent among vulnerable migrants They should be systematicaly screened in primary care
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".