Data Doesn’t Speak, People Do!

by: barbara allen

After months of collecting and analyzing data from a participatory survey on environmental health conducted in a polluted industrial region, we had arrived at the big moment: we presented it to the local community in an open public meeting in the town hall. Our epidemiological statistics revealed most of the health issues the residents had suspected, but for which they previously had no science to support their claims. At the end of the meeting, one of the residents–a shop owner and civic leader–raised his hand, then stood up and said, “We are not statistics. This data is not us!” While we were taken aback by the directness of his comment, we had planned an additional step in our participatory research process: to further interpret and analyze the data in collaborative workshops.

Unfortunately, scientists’ community engagement often ends with the presentation of data to the public and the publication of a final report. Some years ago I met with the director of an international environmental nonprofit organization. He expressed frustration that they had hired the best scientists and made sure their study had no perceived political bias… but when they gave the study to the local people, nothing happened. It was as if their work was for naught; the study was not used to promote environmental or regulatory change. What was missing from the scientists’ engagement with the public was a critical component: collaborative and deeply inclusive interpretation and analysis of the data with the community, prior to releasing the report.

Collaborative data analysis for policy impact

When those people for whom the science matters most are able to participate in the shaping of science, they are able to better contextualize that knowledge, making it more relevant to their life. The data collected can evolve from tables and statistics to meaningful knowledge that can easily be conveyed by local people to the media, regulators, and politicians.

Collaborative analysis to answer a community’s questions about environmental concerns might look something like this:

1. Scientists present the initial data they collect to local communities in a workshop. This can be data they have collected via participatory methods, and/or data they have gathered from government sources.

2.  The workshop participants are able to view the data and ask questions, suggest hypotheses and ideas for further analyses, and add their experience related to pollution or illness (or whatever the study data represents) in a collective discussion with others in their community.

3. The workshop deliberation space is a catalyst for scientists and residents thinking together towards developing science that reflects and includes local knowledge and values.

Scientific reports that emerge from such processes reflect a hybridization of quantitative and qualitative data, infusing statistics with the empirical observations of lay people. Additionally, the participatory process of workshopping data and inviting input and reflection from local people for whom the science is more relevant aligns with science communication research on attention and motivation. People have greater capacity for understanding and personally processing science if it connects to both: 1) people’s preexisting observations and beliefs, and 2) concrete events or outcomes that can impact their lives, or those that they care about. In collaboratively making and shaping science with people, it is more likely that the science will travel through the voices of the people who helped make it.

The social integration of knowledge via collaborative analysis leads to a stronger and more relevant report compared to the socially remote knowledge that is often contained in official state studies or other scientific documents. Inclusively reporting data-in-context enables laypeople to be better advocates for policy, speak to the press and agency officials, and build community capacity for further action.

Participatory science is supportive of a new kind of “scientific citizenship.” Part of the process is reframing civic institutions and institutional approaches to science to not only be more inclusive, but to also invite new kinds of “questioning communities,” a move that can strengthen not only science but also democracy. Science can also learn from other fields and social movements about how to better support communities and address inequities. We know that we need both community members and scientists to be actively involved in informing policy to have a thriving democracy. As we face multiple crises, from coronavirus to climate change to systemic racism, we would do well to remember that when we come together in discussion and deliberation, sharing what we know, we can create the best outcomes for all.

Scientists Engaging the Public: 6 Steps to Make Participatory Science More Policy Effective

by: barbara allen

Several years ago I led a team of scientists working with residents in several polluted towns in an industrial region in France to collect health and related environmental data. The participatory science project collected self-reported data by surveying door-to-door using a random sampling of addresses. The project lead led to extensive policy impacts driven by the local residents. These included stopping a local incinerator expansion and ending “excess pollution” permits given to industry. Eventually the local residents’ actions led to a much larger national impact–an unprecedented lawsuit filed by the residents against the polluting industries. While participatory science (i.e. citizen science, Community Based Participatory Research (CBPR)) is not new, there were several elements of our project that stand out for “super-charging” participatory science in the public and political realm.

There are informational resources for scientists wishing to engage with local communities as well as networks designed to facilitate those connections. There are also a few key strategies that can increase the effectiveness of scientists’ engagement with local groups.

1. Find out what local groups want to know. What are their questions that are answerable through science? Work with the group to clarify their questions.

2. Find out why groups are asking questions. What problem or concern are they trying to address? What kinds of outcomes are they hoping for? For example are community groups hoping to change permitting policies, strengthen environmental regulations, alter city refuse disposal, or shift pesticide use to greener alternatives?

3. Explain to lay people the kinds of data or science that can enable them to find an answer to their questions. Find out if this data or analysis already exists and how to access it. If the data does not exist, what kind of participatory study or citizen science project could produce an answer to the communities’ questions? This may involve consulting with other subject matter experts along the way. 

4. Investigate what kind of science is most likely to inform policy makers or to influence politicians and regulators. Research the kinds of science and data standards that inform current policy. Design the participatory science project with the local group to try and answer their questions with science that will align with what regulators and government officials currently use for decision-making.

5. Any data collected with or for local groups should be analyzed with the group in an open, deliberative fashion. Through collaborative discussion of data, new ideas on how to analyze the data can occur. The local group’s experience and personal evidence informs their understanding of the relevant science. Ideally, their empirical knowledge informs the further analysis of data done by scientists.

6. Final reports should include a robust accounting of the community’s ideas and input gained during the collaborative analysis phase. This qualitative data interpretation and analysis by regular people should be recorded alongside any quantitative data reported. This shapes a final report into a chorus of local voices, which is ideal to promote press coverage and attract political notice. At the end, scientists should get out of the way of promoting the outcomes and findings from the report and let community members do their own talking. Including local people in data analysis can lead to a powerful science-infused public voice informing media, pressuring politicians and government regulators, and potentially, leading to better policy outcomes and structural change.

When scientists work with communities to ensure that data and technical information addresses their questions in the context of their lived experiences, a more robust science can emerge. Local residents can add great value to science both in the kinds of questions they ask and their on-the-ground knowledge of the issues at hand. In the project I led in France, the health issues we were able to collaboratively document and analyze with the residents were, in part, responsible for the state taking the following actions: providing more access to health specialists; continuing operation of a local health clinic that was slated for closure; agreeing to establish a regional cancer registry; and funding medical research to understand the co-morbidities of exposure to industrial pollution in the region. Participatory science, doing science with the people, can promote scientific rigor, social relevance, and policy reach, the 3Rs of participatory research. 

We need more, and more effective, tools for science advocacy to help us achieve these outcomes.