Gender differences in academic rank among faculty surgeons at US veterinary schools in 2019

Vet Surg. 2020 Jul;49(5):852-859. doi: 10.1111/vsu.13440. Epub 2020 May 6.

Abstract

Objective: To describe academic rank, gender, surgical career length, and publication record of academic veterinary surgeons and to estimate the association between gender and higher academic rank.

Study design: Cross-sectional study.

Sample: Residency-trained surgeons at US veterinary schools in 2019.

Methods: Surgeons were identified via institutional websites. Data including surgeon gender, academic title, and year of board certification were collected from public resources. Publication record was measured by using author h-indices obtained from Scopus. Data were analyzed with descriptive and inferential statistics.

Results: Three hundred eighteen surgeons were identified from 30 institutions, including 162 (51%) women and 156 (49%) men. Women represented 66% of instructors and assistant professors, and men represented 60% of associate and full professors. This distribution differed significantly (P < .001). Author h-index was associated with career length but not gender. Men were 2.5 times more likely than women to be associate or full professors (odds ratio 2.52, 95% CI 1.03-6.14, P = .042) after adjustment for career length and h-index.

Conclusion: Female surgery faculty at US veterinary schools in 2019 were concentrated in lower academic ranks and were less likely than male surgery faculty to be associate or full professors after adjustment for career length and publication record.

Impact: A gender gap exists in academic veterinary surgery in the United States. It is critical to recognize that women's increasing participation in veterinary medicine has not been matched by equal representation in all areas. Additional efforts are warranted to identify contributing factors and implement strategies to improve gender inclusion.

MeSH terms

  • Academic Performance*
  • Cross-Sectional Studies
  • Faculty, Medical / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Schools, Veterinary / statistics & numerical data*
  • Sex Factors*
  • Surgeons / statistics & numerical data*
  • United States