Difference between revisions of "CSPS Digital Academy Events/Recognizing Data Bias - Event Program"
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* '''Rachel Zellars (Dr)''', Assistant Professor, Department of Social Justice and Community Studies, St. Mary’s University | * '''Rachel Zellars (Dr)''', Assistant Professor, Department of Social Justice and Community Studies, St. Mary’s University | ||
* '''John Cheney-Lippold''',Associate Professor, Associate Chair, Director of the Undergraduate Studies Program, University of Michigan | * '''John Cheney-Lippold''',Associate Professor, Associate Chair, Director of the Undergraduate Studies Program, University of Michigan | ||
| + | <br> | ||
| + | * '''Robyn Rowe (Dr)''', Staff scientist at ICES in Ontario and Chair of the Indigenous Data Team at Health Data Research Network Canada | ||
<br> | <br> | ||
'''Moderator:''' <br> | '''Moderator:''' <br> | ||
* '''Ima Okonny''', Chief Data Officer, Employment and Social Development Canada | * '''Ima Okonny''', Chief Data Officer, Employment and Social Development Canada | ||
<br> | <br> | ||
| + | |||
== '''2:55 PM - 3:00 PM''' == | == '''2:55 PM - 3:00 PM''' == | ||
=== Closing Remarks === | === Closing Remarks === | ||
Revision as of 12:57, 29 March 2022
Event Page
Speaker Biographies
Event Program - March 30, 2022 | 1:30 PM – 3:00 PM
1:30 PM - 1:35 PM
Welcome and Introductions
- Ima Okonny, Chief Data Officer, Employment and Social Development Canada
1:35 PM - 2:55 PM
Panel Discussion
Speakers:
- Rachel Zellars (Dr), Assistant Professor, Department of Social Justice and Community Studies, St. Mary’s University
- John Cheney-Lippold,Associate Professor, Associate Chair, Director of the Undergraduate Studies Program, University of Michigan
- Robyn Rowe (Dr), Staff scientist at ICES in Ontario and Chair of the Indigenous Data Team at Health Data Research Network Canada
Moderator:
- Ima Okonny, Chief Data Officer, Employment and Social Development Canada
2:55 PM - 3:00 PM
Closing Remarks
Moderator:
- Ima Okonny, Chief Data Officer, Employment and Social Development Canada
