Gender-based violence among refugee women referred to a Cultural Consultation Service in Montreal
Bibliographic record
Abstract
Gender-based violence (GBV) among female refugees/asylum seekers is a major underreported/understudied psychosocial issue. The aims of this study were: to describe the proportion of GBV-related experiences among female refugees/asylum seekers referred to a Cultural Consultation Service (CCS) in Montreal; to describe their sociodemographic and clinical characteristics; and to compare these characteristics among women who make GBV their principal refugee claim (Group A), those who did not but had suffered GBV (Group B1), and those who had never reported GBV (Group B2). Data on sociodemographic and clinical variables and GBV were gathered by chart review. Data were analyzed using chi-square for categorical and ANOVA for continuous comparisons. A total of 91 female refugees/asylum seekers were evaluated from 2000 to 2013; 80% (73/91) having reported GBV, with 38.5% (35/91) using GBV as the principal reason for seeking asylum in Canada (Group A), mainly due to intimate partner violence (IPV). Fully 66.6% (38/56) of women who sought asylum for reasons other than GBV reported having experienced GBV (Group B1). When compared to the other groups, Group A women exhibited a number of statistically significant differences: they tended to migrate alone ( p < .001), be divorced/single ( p = .02), have more suicidal thoughts/behaviors ( p < .001), and report a history of IPV ( p < .001). Women from Group B1 were more likely to be diagnosed with Affective Disorders ( p = .045), and to have suffered sexual violence ( p < .001). Results suggest that GBV is frequently experienced by refugee/asylum seeker women in this small, tertiary care clinical sample. When assessing refugee women such as these, differences in the kind of violence suffered, migration process, family/social support, and clinical related features should be taken into account and explored by clinicians in a culturally appropriate and safe manner.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".