LEARNER: Designing Proof and Evidence with Minorities and Outlier Data

Inclusive Design Research Centre

wecount@inclusivedesign.ca

The Inclusive Design Research Centre is an international community of open source developers, designers, researchers, educators and co-designers who work together to proactively ensure that emerging technology and practices are designed inclusively. Learn more at idrc.ocadu.ca

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accessibility, Bill-c7, Learning, MAiD, MedicalAssistanceInDying, quantification, Social-Hierarchy, Statistics

The earner of this badge has learned about how evidence-based decisions fall short of meeting the needs of marginalized, highly diverse communities. In addition, the earner has contributed their perspective on the challenges of proof for small and diverse groups. The learner viewed a webinar on designing proof and evidence with minorities and outlier data delivered by Catherine Frazee, Officer of the Order of Canada and Professor Emerita at Ryerson University in the School of Disability Studies, and Jutta Treviranus, the Director of the Inclusive Design Research Centre (IDRC) and Professor in the Faculty of Design at OCAD University. A summative assessment, in the form of a knowledge recall quiz, including distinguishing terminology, frameworks, and relevant use, was completed, and then evaluated by a qualified We Count assessor. Estimated learning time including assessment: 2-4 hours.

For more information, please visit We Count’s Home Page

This Learner assessment consists of four short-answer questions based on the content of We Count’s “Designing Proof and Evidence with Minorities and Outlier Data” webinar. The reflection questions will allow you to connect what you have learned to your own experience and We Count initiatives.

This assessment is not time-restricted, featuring an option at the bottom of the form for it to be saved and continued later. Remember to read through all of the questions carefully and to take your time. Please share your ideas by writing in the boxes below. A We Count assessor will verify your contribution to grant you the Brainstormer badge.

The average learning time for this badge is 2-4 hours.

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Question 1: The conception of scientific evidence tends to be reduced to the conception of statistical probability reached through quantitative measures. To your understanding, explain why the scientifically valid decisions in practice could not meet the critical needs of marginalized, disadvantaged communities, such as people with disabilities? *

Hint: Review 05:04 in the recorded webinar.

Question 2: On the “starburst” visualization diagram, which area is described or predicted with the highest statistical accuracy? And which with the lowest accuracy? What, in practice, does this statistical theory imply for meeting the needs of the majority versus the needs of marginalized communities, such as people with disabilities? Furthermore, why do the needs of the majority often trump the needs of the few? And how do automated decision systems and AI data analytics add to this burden on marginalized communities? *

Hint: Review 06:57 in the recorded webinar.

Question 3: What impacts does the passage of Bill C7 policy changes to MAiD have on people with disabilities? *

Hint: Review 16:45 in the recorded webinar.

Question 4: Catherine Frazee made eight observations about the data, MAiD and disability justice in her framing of the Challenge. Please name and describe two of the eight observations in more detail. *

Hint: Review 22:12-35:11 in the recorded webinar.

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LEARNER: Designing Proof and Evidence with Minorities and Outlier Data

Inclusive Design Research Centre

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