Do No Harm? Discrepancies across Canadian Healthcare Policy and Obstetrics and Gynaecology Training for Treating Women affected by Female Genital Cutting
Bibliographic record
Abstract
Female genital cutting (FGC) is a flashpoint feminist issue.It is a deeply stigmatized and controversial cultural practice that affects millions of women and girls internationally and is criminalized in Canada.My research set out to answer the questions: To what extent is obstetrics and gynaecology training in Canada structured to provide adequate, effective, and culturally sensitive care for women who have undergone FGC?Does this training reflect the broader framing of FGC as a "barbaric" practice?Through my research into medical education, I find that Canadian healthcare reflects norms and values of nationalism when considering whose bodies represent these standards.With the methodology of transnational feminism, these covert issues of structural violence that mark certain bodies as Other become more clearly recognizable.I challenge predominant knowledge, attitudes, and skills of healthcare practitioners to ultimately recommend four steps toward creating a new benchmark for culturally sensitive training and care.Dr. Valerie Percival.Val -thank you for your hard work and commitment, especially in the final weeks of my writing process.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.025 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".