Solidarity Moves as the “Social” in Sociocritical Data Literacies

• In Event: How Critical Literacies Are Changing in a Post-Pandemic World

Abstract

Background
In the wake of COVID-19, data has become an everyday part of our media landscape and how we make sense of the world (Tabak, 2022). But seldom do we ask students, especially nondominant students, if and how they see themselves in publicly-available data, or explicitly invite them to consider and share what data means in their sociocultural contexts. Drawn from an environmental justice-focused data science workshop for middle school students, this study brings forth humanizing dimensions that emerged during students’ critical engagements with data. Students used the Common Online Data Analysis platform (CODAP) to explore a large-scale dataset featuring categories of health, asthma, and pollution, along with demographic data (race, zip codes and socioeconomic status). This study shows how students’ interactions with data go beyond strictly technical learning to offer insight into the development of sociocritical data literacies–meaning-making practices recognizing data as socially-constructed text (Lee et al., 2021; Philip et al., 2016), challenge normative scripts about data (Van Wart et al., 2020), and leverage data to identify and address social injustices (Rubel et al., 2016).

Methods
We focus on one student, Daphne, who took the workshop as a student, then voluntarily returned as a co-instructor and second-time participant. Using interactional analysis, we examine video recordings of Daphne’s coursework and interview. In addition to the videos, study data also includes chat logs and student work (slideshows; CODAP data files). Activity logs and analytic memoing were used to identify and discuss moments of sociocritical reasoning and solidarity.

Findings & Significance
Daphne’s reasoning with data revealed how sociocritical data literacies emerge, not in isolation, but through solidarity moves across relationships, which mediate Daphne’s entire data sensemaking process: across the construction of a problem, data collection, analysis, and process of drawing conclusions & communicating them.
She leverages CODAP and EPA data to explore climate-related phenomena by situating herself in data, interpreting the data related to her community and family experiences, and using that data to expand her definition of environmental racism and invite action through her multimodal composition. Through an interview with her father, interactions with a local climate-justice activist, and peer and instructor engagement, Daphne invites her audience to data-driven action and inquiry through storytelling.
In these ways, Daphne’s sociocritical explorations of data uniquely invite solidarity, asking audiences: Where are “you” located in this data, and how might that compel you to action? To whom do the issues represented in these data matter? Where am I, my family, and my community, located in the data? These relational engagements of audience help us envision a humanizing approach to data literacy toward solidarity against racial injustice.
Ultimately we learn from this case how young people can explore and leverage data in ways that are consequential to them, and how their engagements might demonstrate data’s relevance to their lived realities. While this study revealed solidarity as emergent in a context of data literacy learning, we also encourage future research to explore how such humanizing moves might be cultivated in different learning environments.

Authors

• Cherise McBride, Stanford University

• Collette Roberto, University of California - Berkeley

• Emily V. Reigh, University of California - Santa Cruz