BRAINSTORMER: 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 brainstormed 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 Brainstormer assessment asks you to share your ideas and thoughts based on 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 Brainstormer assessment asks you to share your ideas and thoughts based on your own experience and the content you learned from the We Count’s “Designing Proof and Evidence with Minorities and Outlier Data” webinar. This brainstorming activity about the challenges of proof for small and diverse groups will allow you to connect what you have learned from your own experience and from the We Count initiatives.

To qualify for this Brainstormer badge, you must have the Learner badge “Designing Proof and Evidence with Minorities and Outlier Data”.

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.

Your name *

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Step 1: To address the design challenge, reflect on what is considered valid proof and scientific evidence. Then, identify barriers and challenges that keep small and diverse group data from being considered valid proof or evidence. Lastly, explore and identify at least one strategy or approach to producing valid and acceptable proof for the diverse minorities and outliers who are marginalized. *

Step 2: Explore the data production cycle for the small and diverse groups, in terms of how data is A) generated, B) collected, C) analyzed, D) presented, and E) reviewed. In any stage of the data production cycle, choose at least one stage (from A-E) and suggest strategies or tools to improve the data production process for the diverse minorities and outliers who are marginalized, so that they could better collect and provide proof or evidence to policy makers. (Hint: Please use the bullet points under each headline as a guide to structuring your answer.) *

Please use the bullet points under each headline as a guide to structuring your answer. A. How data is generated (and by whom) · How might we support a community to generate data? · How might we support the generation of a variety of different forms of data? · What forms could the data take? · How might we reach the people we want data from? B. How data is collected · How might we support the collection of contextual/qualitative data? · How might we ensure that we’re collecting enough data? · How might we access the people we want data from? C. How data is analyzed · How might we include and analyze outlier data? · How might we change the way data is sorted? D. How data is presented/curated · How might we present the data to make it more credible to policy makers? · How does something become data? · Can data be generalized? E. How data is reviewed (and by whom) · How might we make recommendations to policy makers to change how they review/perceive the data as valid?

Step 3: Based on the approach to producing valid proof that you have explored in the previous step, map out the concrete, actionable steps and solutions. *

You can use the following elements to structure your answer: WHAT — the approach that you choose in the previous answer WHY — the goal or motivation for the approach and desired outcome HOW — the actionable steps, which could be sequences of multiple actions WHO — who is responsible for each action CHALLENGES — potential challenges that could be encountered for each action

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BRAINSTORMER: Designing Proof and Evidence with Minorities and Outlier Data

Inclusive Design Research Centre

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