Health outcomes and female genital mutilation/cutting: how much is due to the cutting itself?
Bibliographic record
Abstract
While Female Genital Mutilation/Cutting (FGM/C) continues to garner global attention, FGM/C-affected migrant communities, who are often racialized minorities in the U.S., face additional challenges which may impact their physical and mental health and well-being. It has been proposed that an overly narrow focus on the female genitalia or FGM/C status alone, while ignoring the wider social experiences and perceptions of affected migrant women, will result in incomplete or misleading conclusions about the relationship between FGM/C and migrant women's health. A cross-sectional study was conducted across two waves of Somali and Somali Bantu women living in the United States, (n = 879 [wave 1], n = 654 [wave 2]). Socio-demographics, self-reported FGM/C status, perceived psychological distress, and self-reported FGM/C-related health morbidity was examined against self-reported experiences of everyday discrimination and perceived psychosocial support. In statistical models including age and educational attainment as potentially confounding socio-demographic variables, as well as self-reported FGM/C status, self-reported discrimination, and perceived psychosocial support, self-reported discrimination was the variable most strongly associated with poor physical health and psychological distress (i.e., FGM/C-related health morbidity and psychological distress), with greater perceived psychosocial support negatively associated with psychological distress, when controlling for all the other variables in the model. FGM/C status was not significantly associated with either outcome. Discrimination, more frequently reported among 'No FGM/C' (i.e., genitally intact or unmodified) women, was most frequently perceived as linked to religion and ethnicity. Our findings are consistent with views that discrimination drives negative outcomes. In this population, discrimination may include the 'quadruple jeopardy' of intersecting relationships among gender, race, religion, and migration status. We find that self-reported experiences of discrimination-and not FGM/C status per se-is associated with adverse physical and mental health consequences in our sample drawn from Somali migrant communities living in the United States, and that social support may help to mitigate these consequences. Our findings thus reinforce calls to better contextualize the relationship between FGM/C and measures of health and well-being among Somali women in the United States (regardless of their FGM/C status), taking psychosocial factors more centrally into account.Clinical Trials.Gov ID no. NCT03249649, Study ID no. 5252. Public website: https://clinicaltrials.gov/ct2/show/NCT03249649.
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How this classification was reachedexpand
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".