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Occupational segregation by gender in veterinary specialties: Who we are choosing, or who is choosing us
Samantha L Morello1, Jordan Genovese1, Anne Pankowski1
1Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Objective:
Gender demographics vary across specialties including surgery, internal medicine, cardiology, neurology, and oncology. Our objective was to determine whether residency selection or the decision to apply for training drives these differences.
Study Design:
Retrospective cohort study.
Sample Population:
Matched and unmatched residents lists from Veterinary Internship and Residency Matching Program (VIRMP) from 2011 to 2020. Comparative Data Reports from the American Association of Veterinary Medical Colleges from 2010 to 2019.
Methods:
Names for matched and unmatched residents with addresses in the United States or Canada were coded for gender for seven programs: large and small animal surgery, large and small animal medicine, cardiology, neurology, and oncology. Match rate by gender was compared using chi-square tests. Gender demographics of applicants were compared to demographics of graduates using tests of two proportions.
Results:
No differences were observed between genders for the likelihood of successfully matching into each residency program evaluated except in large animal internal medicine. Women (44.2%) were slightly more likely to match, overall, than men (39.0%, p = .003). The proportions of women applying for residencies overall (70.7%), in large and small animal surgery (66.1%, 62.2%), cardiology (70.2%), and neurology (70.7%) were lower than the proportion of female graduates (79%; p's < .001).
Conclusion:
No evidence for gender bias was detected in the VIRMP resident selection process. Female veterinary graduates seemed less likely to apply for residencies than their male counterparts.
Impact:
Occupational segregation seems to stem from the decision to apply for residency. Interventions aimed at altering gender demographics in specialized medicine should target potential applicants.
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Semantic barriers:
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