432 Somali Women's Birth Experiences in Canada after Earlier Female Genital Mutilation
Bibliographic record
Abstract
BACKGROUND: Women with previous female genital mutilation (sometimes referred to as circumcision) are migrating, with increasing frequency, to countries where this practice is uncommon. Many health care professionals in these countries lack experience in assisting women with female genital mutilation during pregnancy and birth, and they are usually untrained in this aspect of care. Somali women who customarily practice the most extensive form of female mutilation, who were resident in Ontario and had recently given birth to a baby in Canada, were surveyed to explore their perceptions of perinatal care and their earlier genital mutilation experiences. METHOD: Interviews of 432 Somali women with previous female genital mutilation, who had given birth to a baby in Canada in the past five years, were conducted at their homes by a Somali woman interviewer. RESULTS: Findings suggested that women's needs are not always adequately met during their pregnancy and birth care. Women reported unhappiness with both clinical practice and quality of care. CONCLUSIONS: Changes in clinical obstetric practice are necessary to incorporate women's perceptions and needs, to use fewer interventions, and to demonstrate greater sensitivity for cross-cultural practices and more respectful treatment than is currently available in the present system of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".