The Potential & Perils of Categorization

Presented by Phong Le, PhD
Thursday, October 31, 2019
10 – 11:30 am in Buchner Hall - Alumnae/i House (Directions / Campus Map)

Registration Fee: $18

Program Description

This program will explore three examples of the census and the potential and peril of categorization, primarily by race. Presenter and participants will compare the U.S., Mauritian, and Rwandan census, their respective histories, and how they look today. Discussion will include some of the immigration question issues. During the second half of the program there will be a more in-depth tutorial of using American Fact Finder, and the way that we, as the public, engage with U.S. census data.

Program Objective

Participants will learn:

• how race and identity are captured in official census documents.
• the intended and unintended consequences of emphasizing category.
• how the census becomes politicized.

Program Format

• Power Point presentation
• Demonstration of American Fact Finder
• Question and answer

Suggested Supplementary Reading

• Podcasts: https://www.npr.org/sections/codeswitch/2017/08/03/541142339/heres-why-the-census-started-counting-latinos-and-how-that-could-change-in-2020
• Podcast: https://www.npr.org/templates/transcript/transcript.php?storyId=721190520 – It is a little long but I often use that as an example of unintended consequences.
• Website: American Fact Finder -I will do a demonstration of this in class.

About Phong Le, PhD

Phong Le is an Associate Professor of Mathematics in the Center for Data, Mathematical and Computational Sciences at Goucher College. He also attended Goucher as an undergraduate, studying mathematics and minoring in music. He received his MA and PhD from the University of California, Irvine. His professional interests range widely from algebraic number theory, cryptography, error-correcting codes, statistics and data science. He serves as the Community-Based Learning coordinator, fostering partnerships with Goucher and the surrounding community. In Baltimore, he engages in a wide variety of data-driven community projects ranging from health access, fair housing, and food accessibility. As often as is possible, he brings these experiences into his classroom as stories and daily lessons on how data can empower and transform existing narratives within a community.