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Record W4400413854 · doi:10.36834/cmej.78134

The conditional inclusion of Muslims in medicine: intersectional experiences of Muslim medical students at the University of Toronto’s Faculty of Medicine from 1887-1964

2024· article· en· W4400413854 on OpenAlexaffvenueabout
Roshan Arah Jahangeer, Cynthia Whitehead, Umberin Najeeb

Bibliographic record

VenueCanadian Medical Education Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsThe Wilson CentreWomen's and Gender Studies et Recherches FéministesUniversity of Toronto
Fundersnot available
KeywordsInclusion (mineral)Medical educationMedicineTraditional medicineSociologyGender studies

Abstract

fetched live from OpenAlex

Background: Archival research has unearthed processes of exclusion impacting the experiences of Black, female, and Jewish communities at Canadian medical schools. However, the history of Muslim medical students is little known. Our research is the first known study to examine when Muslim medical students with varying identities were first admitted to the University of Toronto's (UofT) Faculty of Medicine (FoM) and their experiences. Knowing this history can contribute to ongoing equity, diversity, and inclusion efforts in medical school admissions and curriculum development. Methods: This is an exploratory case study with no clear, single set of expected outcomes. We consulted the UofT's Archive & Record Management Services and looked for students who self-identified as Muslim in primary documents from the FoM between 1887-1964, including admissions applications, correspondences from the Dean's Office, photographs, and yearbooks. We analysed the archival data for emerging themes. Results: = 4) postgraduates from one South Asian country who may have been Muslim, and who were granted fellowships from the Canadian government. Conclusions: Self-identified Muslim students were first admitted to the UofT's FoM in 1945 and continued to be admitted infrequently until 1964. These early students' experiences included financial hardships despite having privileged backgrounds; discrimination due to being foreign; and conditional inclusion while in medical school. We discuss the study's continuing contemporary relevance, limitations, and directions for future research.

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)0.003
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2240.000

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 head0.019
GPT teacher head0.364
Teacher spread0.345 · 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.

Study designQualitative
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

Citations2
Published2024
Admission routes3
Has abstractyes

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