4• 4 • How to make data justice actionable in the classroom •
"I tell my students, 'When you get these jobs that you have been so brilliantly trained for, just remember that your real job is that if you are free, you need to free somebody else. If you have some power, then your job is to empower somebody else. This is not just a grab-bag candy game."
As a way to think about data justice in more concrete and actionable ways, we have crafted together a list of heuristics that you can use to make this abstract more concrete so that it can be realised.
The seven principles of data feminism (Klein and D’Ignazio, 2019) can be helpful in raising awareness about structural problems in how data and its products are produced and used in society. The seven principles of data feminism help you to interrogate the data your students will use for different purposes but also the data they may be produced. In the open-access book (linked above) you have a wealth of resources that you can use in your activities with students or communities.
The seven inequities held in place by power, seven opportunities for change
This is a toolkit created by an organisation called Chicago and Beyond, in the US. They are a group of people that have partnered with and invested in, community organisations working towards providing more equitable access and opportunity to young people in Chicago. “Our hope is that the research will generate learnings to impact more youth in our city and nationwide, and arm our partners with ‘evidence’ they need to go after more funding for what is working” (Chicago Beyond).
The toolkit serves to enable researchers, community organisations and funders to make actionable the more conceptual ideas about data justice introduced at the beginning of the module by asking critical questions and transforming common challenges into opportunities for change.
The model illustrated in the figure above, is based on the inequities that have been experienced more often by marginalised communities, particularly people of colour in a US context. Each of the 7 points addresses a particular dimension of the problems they have been confronted with.
The guide begins by naming seven inequities standing in the way of impact, each held in place by power dynamics.
- Access: Could we be missing out on community wisdom, because conversations about research are happening without the community meaningfully present at the table?
- Information: Can we effectively partner to get to the full truth, if information about research options, methods, inputs, costs, benefits, and risks is not shared?
- Validity: Could we be accepting partial truths as the full picture, because we are not valuing community organisations and members as valid experts? What about different ways of knowing as a valid source of knowledge?
- Ownership: Are we getting incomplete answers by valuing research processes to exploit, rather than to build up community ownership?
- Value: What value is generated, for whom, and at what cost?
- Accountability: Are we holding funders and researchers accountable, if research designs create harm or do not work?
- Authorship: Whose voice is shaping the narrative and is the community fully represented?
Download the guidebook to get the full details of how to use the tool. In our project, we are working on an interactive version of this toolkit. Watch this space!
Data ethics canvas
The data ethics canvas will support you in identifying and managing ethical issues – at the start of a project that uses data, and throughout. It encourages you to ask important questions about projects that use data, and reflect on the responses. These might be:
- What is your primary purpose for using data in this project?
- Who could be negatively affected by this project?
The idea with these questions is to wrestle with personal bias and bias more generally, rethink power structures, acknowledge the work of others, and push against how we have always done things.