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Principles for the Use of Disaggregated Data (DDN3-J04)


This job aid serves as an introduction to disaggregated data, its sources and its applications, including dos and don'ts.

Published: July 10, 2023
Type: Job aid

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Principles for the Use of Disaggregated Data

Disaggregated data can help us understand the needs of the diverse groups in Canadian population and identify the gaps and inequalities in existing policies and services.

This job aid is intended to provide an introduction to those who want to learn more about disaggregated data, its sources and applications. This is not a comprehensive guide or a substitute for expert advice. Use it as a starting point for further exploration and learning.


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1. Understand the importance of collecting, analyzing, and sharing disaggregated data. Read your department's mandate letter, the Disaggregated Data Action Plan, and refer to the GBA Plus research guide and Compendium (PDF) (GCpedia) to learn more about the importance of disaggregated data in addressing systemic inequalities in our society.
2. Seek out varied sources for disaggregated data. Combine data from various sources, such as stories from people with lived experiences, academic literature, administrative data and statistical datasets, including the Gender, Diversity and Inclusion Statistics Hub, to create a complete picture.
3. Include diverse perspectives at every stage of the process: collection, analysis, implementation and reporting. Design data collection tools that resonate with a diverse pool of respondents. Engage people with lived experiences to help understand and make sense of data. Store, analyze and disseminate data in an inclusive and culturally relevant manner.
4. Make disaggregated data collection, analysis, implementation and reporting into an iterative process. Continually seek insights to improve and enrich disaggregated data as you plan and implement your work.
5. Look for differences between various groups as well as within the groups. Ask questions and apply an intersectional lens (PDF) to help you identify groups that still need to be represented. Find differences within common groups and disaggregate them further.
6. Apply empathy and ethical best practices when working with data from different communities. In order to build trust with government, the lived experiences of different communities need to be considered and represented, and data ownership needs to be respected.
7. Ask questions and ask for help. Ask colleagues and learn from training and guides, such as Measuring Impact by Design, to improve your capacity to collect and use disaggregated data.  


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1. Don't give up on finding data. Even if not immediately available, make a wish list and seek out the data that you need for your work. Ask a colleague or experts for help finding it.
2. Don't consider Gender-based Analysis Plus (GBA+) to be a tick box. Learn about the GBA+ process and integrate it into every stage of your work to ensure inclusivity.

This infographic was created by the GC Data Community based on the tips and insights shared at a learning event on Collecting and Using Disaggregated Data in December 2022. To learn more, visit the CSPS learning path on GBA+.

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