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The citizen scientists of hidden America

Speed read
  • Big data has problems with bias, but can also be used to correct the historical record
  • Citizen science framework gives more agency to subjects in a public health study
  • Black women in Chicago direct design of study and participate in results

When you read the words ‘citizen scientist’, what do you picture? Maybe backyard astronomers helping to classify distant galaxies, or fifth graders recording soil temperatures to track climate change.

Big data is not neutralRuby Mendenhall sees citizen science as a way to address health disparities and social inequality.

But Ruby Mendenhall, assistant dean for diversity and democratization of health innovation at the Carle Illinois College of Medicine, has a different idea of what citizen science can do—and who can participate. 

Mendenhall used a 2017-2018 NCSA Faculty Fellowship to examine how exposure to nearby gun crimes impacts African-American mothers living in Englewood, Chicago. Home to about 30,000 people, Englewood has a reputation as one of the most violent neighborhoods in the city.

Beyond the physical effects of stress, Mendenhall wanted to investigate the long-term consequences experienced by women living in communities like Englewood. For example, what happens to a parent when the sound of gunshots is common during the day—and especially at night?

<strong>Exposure to gun crimes.</strong> Mendenhall wanted to investigate the long-term consequences experienced by women living in Englewood, one of the most violent neighborhoods in Chicago. Here’s where the citizen science comes in. The women of Englewood aren’t just subjects in this research, they’re active participants.

“We wanted to put more agency in their hands,” says Mendenhall. “We asked them, ‘What would you like to see solved? What’s an issue that you have? How can we study this?’”

From subjects to scientists

Mendenhall sees citizen science as a way to address health disparities and social inequality. Though many citizen science projects focus on topics like backyard biology, it’s an existing framework that can be applied to community-based participatory research in health and medicine.

“These are citizen scientists who can take knowledge of their own lived experience and create new knowledge about Black women and families,” says Mendenhall. “We hope they can help us  make medical advances around depression, PTSD, and how the body responds to stress.”

Mendenhall wanted to put more agency in the hands of the women, transforming them from study subjects into participating scientists. The researchers asked what the women wanted to see solved, what issues they were concerned about, and how it might be studied.

<strong>Active participants.</strong> Researchers asked the women what issues they were concerned about and how it might be studied. The women wore biosensors and kept diaries to collect data.Mendenhall then teamed up with computer scientist Kiel Gilleade to design a mobile health study that documented the women’s experience via wearable biosensors, phone GPS, and diary-keeping.

Given historical problems with mistrust of the medical community—and with good reason—Mendenhall was concerned that the participants wouldn’t agree to let researchers take samples of their blood (for a separate study) to see how stress affected the genes that regulate the immune system.

But, somewhat to her surprise, the women agreed. One of the reasons the women gave for their willingness to participate was that they recognized the impact stress was having on their bodies.

“They talked about having headaches, backaches, stomachaches, many things,” says Mendenhall. “They were interested in what was going on with their bodies, what was the connection.” 

Asking the right questions

Mendenhall hasn’t always engaged with computation to further her research. She started her academic career in African-American studies and sociology. But when faculty from NCSA visited her department, Mendenhall became intrigued by the possibilities of big data.

<strong>Whose voice is not represented?</strong> Mendenhall presented her keynote address, Using Advanced Computing to Recover Black Women’s Lost History, at the PEARC18 conference in Pittsburgh, in July 2018.“I didn’t change the research I was interested in, I didn’t change my focus on Black women and their agency and their lived experiences on the margins of society,” says Mendenhall. “What I did was expand my toolkit and my ability to answer questions—and even to ask different questions.”

Some of the questions she’s asking are: Whose voice may not be represented? Whose lived experience isn’t represented? If they were, how would what we see be different? Mendenhall believes that scholars of all types can benefit from putting more time and energy into asking questions like these.

“I think it’s important to understand that big data is not neutral, it is not objective,” says Mendenhall. “Data is situated within a historical and political context.”

Despite biases in existing collections of data, Mendenhall believes data can also be applied to help equalize the historical record.

“I think big data has great potential if more voices are brought in,” says Mendenhall. “If everyone’s voice can be heard and seen and studied and digitized. And if Black women can also study it themselves and develop ideas about what that data is representing.”

The study about Black women in Englewood followed only twelve women but the next step will be to expand the pool of citizen scientists to 600 or more. 

“Ideally, I’m thinking about 100,000 citizen scientists or all the women in Chicago. If they could all be citizen scientists—then what would we see?”

Mendenhall is currently at work on a funding proposal to create a Communiversity Think-and-Do Tank where researchers and citizen scientists will work together to address grand challenges (e.g., gun violence, Black infant and maternal mortality, mental health, diverse histories in the digital archives, etc.) She hopes this will be one avenue to get her closer to her goal of 100,000 citizen scientists.

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