QSIDE Colloquium

The QSIDE Colloquium series is pleased to announce our spring 2021 speakers! Please register for your events as soon as possible; attendance is limited and is on a first-come, first-served basis.

All talks will be held virtually via a Zoom webinar. Zoom details will be sent prior to each event.

Aruna D’Souza, Writer, Art Critic, and Curator

Naming Institutional Whiteness in the Cultural Realm

Speaker: Aruna D’Souza, Writer, Art Critic, and Curator
Date and Time: January 14, 2021 4:00p.m. Eastern
Abstract: This talk will address some of the ways in which museums, universities and colleges, and other sites of cultural production reify and protect whiteness at all costs- even, or especially, in the guise of diversity. 

Dr. Candice Price, Assistant Professor of Mathematics at Smith College

Using Social Network Theory to Support Women in Conflict Zones

Speaker: Dr. Candice Price, Assistant Professor of Mathematics, Smith College
Date and Time: January 21, 2021 4:00p.m. Eastern
Abstract: In 2016, James Gatewood and I started working on a model to study the plight of women in conflict zones through the lens of social network analysis. This novel idea was to build a social network within troubled regions to assist in understanding the structure of women’s communities and identifying key individuals and groups that will help in rebuilding and empowering the lives of women. Our first contribution to this idea was a paper titled “Utilizing Social Network Analysis to Study Communities of Women in Conflict Zones”. We believe this article can be used as the foundation for a model that will represent the connections between women in these communities. In this presentation, we will explore the ideas in the article as well as the next steps, including some cautionary advice

Gaelan Smith, Data Visualization Engineer and Knowledge Manager

Labels Matter: Methodology and Data Visualization

Speaker: Gaelan Smith, Data Visualization Engineer and Knowledge Manager
Date and Time: February 4, 2021 4:00p.m. Eastern
Abstract: Our language drives what we choose to measure, and what we
choose to measure drives our conversations. The visual and textual language we use to present our research, especially about underrepresented and marginalized communities, fundamentally
shapes the perception of and future course for not only our own work, but for everyone who
encounters it. We’ll explore how labels, colors, placement, flow, and accompanying text in data
visualization are as critically important to the intended message as the data itself.

Russell Skiba, Ph.D, Ph.D ,Professor Emeritus Department of Counseling and Educational Psychology Former Director, the Equity Project Indiana University

Giving our Data Legs: Lessons from Research on Racial Disparities in Discipline

Speaker: Russell Skiba, Ph.D ,Professor Emeritus Department of Counseling and Educational Psychology Former Director, The Equity Project Indiana University
Date and Time: February 18, 2021, 4:00 p.m. Eastern
Abstract: Research for over 40 years has found deep inequity in the use of school suspension and expulsion for students of color, especially African Americans.  Yet for many years, those disparities were virtually ignored by policymakers and educators.  This presentation will describe the nature of those disparities, and how research in recent years has begun to highlight the issue and contribute to changes in policy and practice.  In the process, the presentation will focus on framing and disseminating research in a way that addresses questions of equity.  How do we design our research so that it addresses key questions in the larger discourse concerning racial/ethnic inequity?  As the research reaches fruition, how can we disseminate it in a way to maximize its outreach to policymakers and advocates?

Shilad Sen, Professor of Mathematics, Statistics and Computer Science at Macalaster College and Research Fellow at Target Corporation

Embracing Discomfort: Bridging the Human Gap in Data Science

Speaker: Shilad Sen, Professor, Mathematics, Statistics, and Computer Science Department, Macalester College Data Science Research Fellow, Target Corporation
Date and Time: March 4, 2021 4:00 p.m. Eastern
Abstract: Data science has been lifted up as a way for quantitative experts to address societal problems. But “data science for good’s” failure to regularly create “good” often stems from an embrace of comfort by data scientists themselves. Data scientists choose problems and approaches they can easily understand and control. In contrast, they do not typically enter into meaningful dialog with the individuals and communities most reflected, affected, and oppressed by the data they study.
I will discuss two examples of failures driven by an embrace of comfort. First, I will describe a study in information geoprovenance, or where information comes from geographically.  I will describe how we hit a wall in this line of research until we moved forward in partnership with media experts and data producers.

Second, I will talk about the recent rise in “data science for good courses” in higher education. While these courses hold great promise, they typically fall short of providing students with the lasting skills needed to center historically minoritized communities when conducting data analyses. I will share a vision of how undergraduates may address this challenge by engaging in meaningful service of local organizations who have data needs. This is a work in progress, and I will share as many problems I don’t know how to solve in this new educational model as ideas and opportunities.

Andres Lopez, Ph.D.
Research Director
at Coalition for Communities of Color
Mira Mohsini, Ph.D., Senior Researcher at Coalition for Communities of Color

Community Data and Racial Equity: Strategies for Research and Data Justice

Speaker: Andres Lopez, Ph.D., Research Director at Coalition for Communities of Color and Mira Mohsini, Ph.D., Senior Researcher at Coalition for Communities of Color
Date and Time: March 18, 2021 4:00 p.m. Eastern
Abstract: For decades, if not centuries, data has been weaponized against Black, Indigenous, and People of  Color (BIPOC) communities by dominant institutions to reinforce oppressive systems that result  in divestment and often inappropriate and harmful policies. Local, regional, and state  governments rely on datasets that misrepresent BIPOC communities while dismissing the lived  experiences of community members as unreliable and untrustworthy. One strategy to address this  issue is ensuring that government datasets are more equitable through efforts such as survey  modernization and community engagement. However, these often place tremendous burden on  communities to provide input and feedback, over and over again, without seeing any tangible  outcomes from these efforts at the community level. To advance racial equity and reduce the  harms done by extractive and exploitative data practices, we propose elevating the elements,  uses, and power of community data – including stories and narratives of everyday lived  experiences – by employing strategies framed by the principles of research and data justice.  These strategies are necessary in order for community members to understand the value of their  lived experiences as community data. These strategies are also necessary in order to communicate the structure of community data to governments and other dominant institutions as  valid for equitable decision-making. In this presentation, we discuss some of these strategies for  research and data justice.