THE IDEAL GRADUATE STUDENT: HOW GENDERED DISCOURSES SHAPE THE EXPERIENCES OF WOMEN DOCTORAL STUDENTS IN BIOLOGY.

  • Published In: Journal of Ethnographic & Qualitative Research, 2025, v. 18, n. 1. P. 46 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Steele, Ariel; Parson, Laura 3 of 3

Abstract

Despite the increasing numbers of women pursuing graduate degrees in the biological sciences, women remain underrepresented in senior faculty positions, suggesting gendered experiences in graduate education may be contributing. Graduate education is a site for students to learn the expected norms and values of their field, which include discourses that coordinate how scientists behave and perform. We used institutional ethnography framed through gendered organization theory to explore the discourses and practices that organized the experiences of women doctoral students in biology, focusing on how those discourses constructed an ideal graduate student and what challenges were associated with meeting the standards of the ideal graduate student for women. Our findings suggest the characteristics of the ideal graduate student, which include an adequate scientific background, prioritization of research, willing to ask good questions, time management skills, and self-motivation, contributed to fear of failure and imposter phenomenon for the women participants in this study. The findings of this research highlight the importance of critically reviewing how discourses and subsequent practices can perpetuate inequality within biology graduate education. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Ethnographic & Qualitative Research. 2025/09, Vol. 18, Issue 1, p46
  • Document Type:Article
  • Subject Area:Biology
  • Publication Date:2025
  • ISSN:1935-3308
  • DOI:10.5281/zenodo.17972447
  • Accession Number:190314512
  • Copyright Statement:Copyright of Journal of Ethnographic & Qualitative Research is the property of Ethnographic & Qualitative Research, LLC and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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