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A woman with glasses and long hair smiles. Text reads "Big IDEAs about health data. Developing guidance on using race and ethnicity data. Tatiana Kim. September 28, 10 - 11AM PT|1-2PM ET" HDRN Canada logo at bottom.

Hello!

Please join us for the launch of HDRN Canada's Big IDEAs About Health Data Speaker Series THURSDAY, SEPTEMBER 28 from 10:00 - 11:00 a.m. PT | 1:00 - 2:00 p.m. ET. The first talk in our new series features Tatiana Kim, Manager of Anti-Racism Data Projects for BC Stats, who will disuss the BC government's new Guide on Categorial Race & Ethnicity Variables

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About the presentation:

In June 2023, BC Stats released a Guide on Using Categorical Race and Ethnicity Variables to support anti-racism research in British Columbia. This tool will help users of administrative and survey data to appropriately and consistently incorporate race and ethnicity variables into their projects. In this talk, Tatiana Kim discusses the challenges and lessons learned in the process of developing it as well as implications for research in British Columbia.

About the speaker:

Tatiana Kim is an applied social researcher and a program evaluator with a Master of Arts in Applied Social Psychology and a Professional Specialization Certificate in Population Health Data Analysis. In her role as a Manager of Anti-Racism Data Projects at BC Stats, she is part of the team supporting research that aims to understand and address systemic racism in government programs and services. Through this work, she hopes to make a difference in the lives of British Columbians and help build a community where researchers can exchange knowledge and ideas. Tatiana is grateful to live on the traditional territory of the Snuneymuxw First Nation, which is known today as Nanaimo, British Columbia.

About the Big Ideas About Health Data Speaker Series:

HDRN Canada’s Big IDEAs about Health Data speaker series features a variety of experts discussing how data can be used to advance health equity in Canada, specific uses of disaggregated data (sex and gender, race and ethnicity, disability) and advancements in data research methods that embed inclusion, diversity, equity and accessibility.