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Record W4387317756 · doi:10.4103/efh.efh_18_22

Canadian medical student knowledge and attitudes toward female genital mutilation

2023· article· en· W4387317756 on OpenAlexaffabout
Marisa Market, Mélanie Grondin, D. BOUCHER, Claudia Malic

Bibliographic record

VenueEducation for Health · 2023
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of OttawaWestern University
Fundersnot available
KeywordsCurriculumLikert scaleFemale circumcisionLegislationFamily medicineScale (ratio)Health careMedicineMedical educationPsychologyGynecologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

Background: Despite female genital mutilation/cutting (FGM/C) practices being an illegal form of gender-based violence in Canada, this practice impacts many Canadians. Lack of education and training among Canadian health-care providers has resulted in systematic barriers to care. Awareness and FGM/C-related education among Canadian health-care providers must be urgently assessed. Methods: Canadian medical students were recruited to complete an anonymous survey via E-mails distributed through their schools' student organization between January and March 2021. We evaluated student understanding of FGM/C, attitudes toward medicalization and legislation, and prior clinical experience using multiple choice, Likert scale, and open-response questions. Results: Respondents (n = 135) performed poorly on knowledge assessment questions (mean percent correct <50%). Only 10.4% of respondents indicated knowing how to involve appropriate authorities when necessary, and most never evaluate FGM/C in patient history (86.7%) or clinical examination (57.1%). Subgroup analysis revealed that prior education significantly improved knowledge scores and influenced students' behaviors and attitudes. About 92.2% of respondents supported the integration of FGM/C curricula in undergraduate medical education. Discussion: This study reveals that Canadian medical students have a poor understanding of FGM/C and are not prepared to identify affected patients or intervene when necessary. These results provide rationale for the implementation of FGM/C-learning modules in undergraduate medicine.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.444
Teacher spread0.391 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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