DEI Event Recordings

Anti-Racism is Never Not Intersectional

Co-sponsored by: The Institute for Research on Women and Gender, the Women’s & Gender Studies Department, and the National Center for Institutional Diversity’s Anti-Racism Collaborative.

DECEMBER 9, 2021

The racial reckoning during 2020 sparked renewed energy to address pervasive structural racism and the resulting disparate inequities and injustices impacting minoritized communities and communities of color in the US. Institutions of higher education across the nation have expressed commitments to address racism in their organizations. Similarly, many institutions across the country have sought to focus new efforts to end harassment based on sex, sexuality, and gender, yet these efforts have often operated separately from the fight to address systemic racism.

At the College of Literature, Science & the Arts (LSA) at the University of Michigan working groups have produced both an LSA Task Force on Anti-Racism and Racial Equality report and a Preventing Sexual Harassment report in recent months. Additionally, the university commissioned reports on high-profile cases of sexual misconduct (Philbert and Anderson) and created campus initiatives in response to national conversations around anti-racism.

This expert panel will help us to understand how systems of racism and sexism support and maintain each other, discuss recent efforts to grapple with these issues at Michigan, frame them within a broader theoretical and political context and then provide suggestions on how to move from intention to action and how to enact structural change that is transformational and sustainable.


  • Elizabeth Cole, Faculty Associate Director, National Center for Institutional Diversity; Professor of Women's and Gender Studies, Psychology, and Afroamerican and African Studies
  • Elizabeth González, Education & Training Program Manager, Spectrum Center
  • SaraEllen Strongman, Assistant Professor, Afroamerican and African Studies
  • Ruby C. Tapia, Chair, Department of Women's and Gender Studies; Associate Professor, English Language & Literature and Women's and Gender Studies

Moderator: Anna Kirkland, Director, Institute for Research on Women and Gender; Arthur F. Thurnau Professor, Women's and Gender Studies; Political Science, Sociology, and Health Management & Policy (by courtesy)

Tracking Health Disparities Using Multiple Data Sources with varying Measurement and Response Properties

Biostatistics DEI Research Seminar

December 3, 2021

Measuring and tracking health disparities among various subgroups in the population may be useful in assessing a nation's health. Such ability to track crucially depends upon suitable data measuring various diseases and outcomes. This talk will focus on three measures of quantifying health disparity and multiple data sources with different measurement and response properties to track race/ethnic disparity in diabetes over a ten year period. Treating one of these data sources as preferred, methods to calibrate other data sources to reduce bias and improve statistical efficiency will be explored.


Co-Sponsored by faculty, staff and students of the School of Public Health community, including members of multiple departmental DEI committees, as well as the OVPR Institute for Research on Women & Gender.

September 24, 2021

Picture a Scientist is a groundbreaking documentary that chronicles the lives of three women scientists, who share their own experiences overcoming harassment and discrimination in order to create a more equitable and welcoming field. In this recording, distinguished panel members, Patricia Coleman-Burns, Heather Colohan, Reshma Jagsi and Anna Kirkland discuss the film.


Examining Algorithmic Fairness and Why It's Important

Biostatistics DEI Research Seminar 

February 22, 2021

Algorithmic bias is increasingly becoming a major issue in today’s modern world. As use of big data increases, so does the potential for harmful consequences by perpetuating bias through unchecked algorithms. In this talk, I will go through several examples of algorithmic bias and the lasting impacts on inequities in our society. Then, I will describe several statistical definitions of algorithmic fairness. Lastly, I will highlight several methods that are being developed to examine, test, and correct algorithmic bias.


October 23, 2020

The ongoing pandemic has affected the world in numerous ways, but it has also underscored societal issues where we can contribute as biostatisticians and perhaps ignited our desire to do so. We met as a department to discuss how we can engage with the community around us as statisticians and contribute meaningfully as socially responsible citizens.

We were joined by outside guests Jeff Leek, PhD Johns Hopkins School of Public Health and Luke Shaefer, PhD Gerald R. Ford of Public Policy. Jeff's work with training underprivileged students in data science and employing them, Luke's work on poverty solutions in Detroit has been inspirational to many. In addition, we had had a presentation from STATCOM leadership showcasing some of their recent work.