VDS Session 2

What scientific practices, assumptions and mindsets, past and present, have caused harm? How can scientists use that awareness to design and do collaborative research that seeks to avoid harm? Click to view the recording of our Q&A with Matt Houser. 

Come in with empathy, do the best you can, and acknowledge that it might not work.

Agenda

We (academics) are too often more interested in producing the impacts that matter in our careers, compared the work that produces benefits in our communities.

Can I actually explain to someone why they should participate, and believe it myself? This is a litmus test for community science.

Our goal as academics should be to understand; let someone be heard for who they are and where they are coming from.

Post-Call Q&A

Dr. Houser provided these written answers to questions from the chat. Thank you to Dr. Houser, the Community Voices, and participants!

A: If I’m understanding correctly, I think this question is about how to move from connecting with a commuting to doing co-produced research with a community?  Building the relationships and the trust with communities is hard, is my opinion. Once those networks are in place, the research is much easier. I think it is essentially a process of having an honest conversation with key people in the community about what they would like to see and if/how new research/collaboration can be a means toward helping to achieve that. To whatever extent is feasible, including members of the community in the process of project development/funding is extremely helpful as well. Biggest risk factor I see is a research team thinking that just because they have expertise in X, then the community will benefit from X. It may not always be a fit and admitting that, rather than overpromising and failing to deliver, is better. As one of my colleagues at UMCES says, trust is hard to win and easy to lose. So tread carefully and respectfully.

A: I’m reading this as being related to relying participant quotes in papers or reports, etc. If that’s the case, I do  two things: (1) I seek to streamline and find the essence of their meaning drawing on the larger context of the conversation we had and on my own personal knowledge of that community or group. I seek to amplify their message through clarifying, in short, with my edits. (2) Following, this and to whatever extent is possible, I like to present my findings back to my participants and ask what I got right and what I got wrong. I’ve never really had issues with misrepresentation being noted here. Usually it produces comments akin to “Yes AND you need to note these other things too..” It’s a great way to develop additional insight and provide assurance of the quality of your interpretations.

Lighter lifts: I send back reports and/or peer reviewed papers to the participants I worked with. Usually I ask folks if this is something they’d actually want. I mark those people down and I return the information to them.
Medium lifts: When feasible or needed given a specific project, I reconnect with as many participants and/or community “leaders” as possible. I send them the drafts of the papers or reports, etc. and I ask them to provide their thoughts/feedback on the entire thing. I use this as a means to collect additional data too (see above). Sometimes we’ll conduct additional in-place interviews or focus groups with participants following a presentation of results. We’ll discuss how they want the work to be used, what they want to see from it. These discussions may or may not be the “end” of our research collaboration. We address that directly in conversation.
Heavier lifts: This is what I’ve been striving to primarily do in the last couple of years. Here I try to produce an impact that is tangible in the sense that it directly impacts the participants and their wider community in some positive (or at least hopefully positive) way. Usually, these heavier lifts include the lighter and medium lift efforts as initial steps. I then draw on them to produce new projects that directly deliver/test desired efforts. For instance, in one project, we drew on farmer social data to inform the ecological analyses. Colleagues conducted these analyses given farmer input, and we brought the results back to the farmers who participated and got their input on what variables we might be missing, the realities or worth of the analysis, and how to make it more useful in the future. This is more of a traditional “co-produced” science model. In other work, we’ve drawn on social science efforts and collaborations with farmers and ag businesses to develop “innovative” incentive models that enable farmers to try practices they’re interested in and that produce economic/environmental benefits. Through our partnerships with farming participants as co-PIs, we’ve applied for and won large awards that bring dollars and innovation directly to our participants and their wider communities. This, to me, is a really exciting direction for action-science moving forward.

Other Links:

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It’s a very stressful time to be a farmer. They might say, “I’ll chat if I’m still around.” Does our work measure up to that reality?