Research & Data Justice

Research Justice

 

This guide is for anyone who is curious about new models of conducting research, e.g., research with a community -  not just about the community - and consciously working to redress historic harms perpetuated on "the researched" by unethical / poorly designed / biased research in the past.
 

 

Research justice is a strategic framework that seeks to transform structural inequities in research. It centers community voices as experts and leverages all three types of knowledge to push their political agendas. It is research WITH the people and not ON the people. (Research Justice Fast Facts Sheet. What is Research Justice?).

 

Multiple ways of knowing
 

 

Many types of knowledge inform the human experience, but western research culture tends to define knowledge arising from research conducted by scholars at post-secondary institutions and research institutes, and published in peer-reviewed journals or scholarly monographs as the "gold-standard" of accuracy and reliability.

 

The research justice movement seeks to expand our understanding of "expertise" to welcome community members into the research process - not solely as research subjects - but as acknowledged experts in their own lived experience and in their own social and cultural traditions.

 

 

• Experiential knowledge comes from lived experience, e.g., "What we learn and know from living and dealing with issues that impact our lives" (An Introduction to Research Justice.  Data Center Research for Justice).
  
   
  • Ask yourself: in mainstream academia, whose lived experience is valued and in what context?
     
    • What distinguishes a "an oral history" from "anecdotal chatter?"
       
    • Who decides which voices are credible enough to be amplified or heeded?

 

• Traditional cultural knowledge "is often transmitted orally from generation to generation. It tends to be collectively owned and can be expressed in stories, songs, folklore, proverbs, cultural values, beliefs, rituals etc" (Backgrounder: Traditional Knowledge  The United Nations Permanent Forum on Indigenous Issues).

 

Ask yourself: 
 

• Does your proposed project reflect only one way of knowing?  On reflection, is that a concern?
   
• Would the project be strengthened by gathering more types of knowledge and/or from a wider range of sources?

Power & Privilege

 

Before starting a research project, and at all stages throughout the project lifespan take the time to consider:

 

• What is the purpose of the project?
   
• How will the research be conducted?
   
• Who will the project benefit?
   
• How will we determine if we've been successful? (Adapted from: The Data Process.  p 12.)

 

 

Additional considerations: 

 

• Are any important voices missing from the research team? Is there representation from a diverse cross-section of topic experts?
   
• Are community-members welcome to participate in the research design process or is their role limited to "test subjects?" 
   
  • If community-led research design isn't feasible, how will you determine and communicate the benefits/usefulness of your research project for the community being studied?
     
• Does the chosen research platform, e.g., online survey, in-person focus group pose unforeseen barriers to participation such as limiting to those with reliable internet access or to those who don't have mobility challenges?

 

 

Marginalized / Under-represented Groups

 

 

All research participants rely on the research team to adhere to accepted research ethics, to protect their privacy, and to safeguard their data from accidental loss or misuse, but it's important to consider the additional responsibility that comes with working with groups who've experienced historic harms from participating in research.

 

Care for research participants
 

 

• It's important for the research team to build care for the participants into the research design, e.g., offering safety and trauma-support during the active research stages - especially when topics being explored pose a risk of re-traumatizing participants.
   
• Another crucial element is ensuring that the research offers tangible, clearly conveyed benefits to the participants and their community to offer a meaningful balance to any potential risks in participating.
   

 

Safeguarding research data

 

"When you collect data from marginalized/under-represented groups, you may not have a second chance.  Losing data is always bad, but breaking trust with these communities means long-term repercussions for both you and them, particularly when it comes to trust" (University of Maryland Libraries. What is Data Equity?).

 

• It is important to set up and maintain best practices in data security, including access limitations, secure data handling and storage, and long-term preservation/destruction procedures.
   
• See the College guide to Safeguarding Research Data for more detailed guidance.

 

Access to / Governance of the data

 

For many communities, much of the scepticism associated with participating in research studies centres around historic misuse of participant data.  Examples of research "malpractice" include:

 

• biological samples taken from participants without permission, right to refuse, and/or being informed about how the samples would be used, stored, and / or displayed e.g., hair taken from Indigenous peoples 
   
• sharing / re-use of biological samples for other research projects / research teams without participant permission or notification, e.g., the Havasupai genetic study into diabetes
   
• lying to test subjects about the true nature of the research they are participating in / withholding appropriate medical care, e.g., Tuskegee Syphilis study
   

 

Due to these and other past research harms, research involving human participants is now subject to stringent ethical oversight.  At Douglas College for example, all such research must be approved by the Research Ethics Board (REB) prior to commencement.   Participant advocacy efforts have also increased internationally, as have efforts to establish principles and practices for community data governance -  including Indigenous Data Sovereignty.

 

Ask yourself:

 

• who "owns" the data and how clearly is this conveyed in your participant release form?
   
• what control do participants have over their own data? 
   
• will participants have free / easy access to the data / research results?  Or will they likely wind up behind a journal paywall?
   
• what are your long-term archiving / data-destruction plans?  Are they clearly articulated in your release forms?

The Research Team

 

 

Equity, Diversity & Inclusion

 

 

When recruiting team members consider whether a diverse research team could strengthen and improve the project, e.g.,
 

• by bringing diverse perspectives to the research question(s).
   
• by adding unique experiences and world-views to how the research data are analyzed and interpreted.
   
• by adding representation for marginalized/under-represented groups - especially if these are the communities being studied - in order to:
   
  • provide a community-centred lens, which may help to prevent perpetuating historic harms.
     
  • bring awareness of how best to reach out to community members - and awareness of which groups should be included or should be permitted to be invisible.
     
  • potentially improve the research design, rebuild trust with the community, and provide more relevant/tangible benefits for participants and the greater community.

 

 

Community-based Research

 

 

A community focussed, data-justice informed project should:   1) Represent and make visible the challenges and strengths of the community.    2) Treat data in ways that promote community self-determination, which include considerations of consent and ownership of data.    3) Pro-actively consider potential harm to the community and work to mitigate it.    4) Make critical consideration of the value of invisibility and disengagement for certain communities (What is Data Justice? [PDF]. UBC ORICE: Community-Based Research & Data Justice Resource Guide).

 

An Introduction to Research Justice.  Data Center: Research for Justice.

 

Exploring Social Justice in an Age of Datafication.  Data Justice Lab.

 

Indigenous Approaches to Evaluation and Research.  Government of Canada.

 

Research & Data Justice.  Coalition of Communities of Color.

 

Together We Achieve.  The United Nations Permanent Forum on Indigenous Issues.

 

Transformative Research Toolkit.  Community Power and Policy Partnerships Progam.

 

Ways of Knowing. Queen's University: Office of Indigenous Initiatives.