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In this poster, we share preliminary reflections on the ways in which hermeneutic injustice emerges and operates within educational settings and interactions. Hermeneutic injustice is a type of epistemic injustice that occurs when someone’s experiences are not well understood by themselves or by others, either due to unavailability of known concepts or due to systemic barriers that produce non-knowing (Fricker 2007). In 2021, we entered into a collaborative project to design a high school curriculum on environmental injustice and climate change for California’s K-12 students. Although the project convenors aspired to support the diversity of California’s K-12 student population through representational inclusivity across the program participant, they reproduced essentialized notions of what it means to be an “included subject”. In our first inperson meetings, activities intended to invite difference in the curriculum writing and design community were encountered by participants as an opportunity to point to the margins of that community. Who was in the room and who was not? Initial counts excluded some writers whose identity was not readily apparent by race, ethnicity, or age. Some individuals who, to their consternation, were assumed to be white, revealed themselves as people of color. The project chose the “storyline model” of curriculum design to bring coherence across the teams. The model was developed by science educators to promote student agency and active learning. Lessons start with an anchoring phenomenon, which should hook students and produce enough questions to sustain inquiry cycles that culminate in consensus making. As a result, each grade-level unit of our curriculum was intended to focus on a single environmental phenomenon, like wildfire. However, informed by Gregory Bateson’s theory of learning, we sought to foreground complexity by recursively analyzing environmental injustice through case study analysis of many hazards, injustices, and places. It took multiple meetings over several months to arrive at an articulation of environmental injustice as our central phenomenon that recognizes the compounding impacts of both climate change and toxic pollution. It also required restructuring the working relationships between the project's administrative arm, the curriculum consultants, and the writing team. The image we include is a photograph of an exercise done together with another HS team as we were tasked to clarify the aims and goals of our imagined lessons. As is evidenced in the photograph, each writing team found it difficult to articulate learning outcomes as a series of checklists, or goals, separate from skill-development that represented the dynamic need for curriculum capable of examining climate change and the environmental justice needs for California’s students.

Tebbe, Margaret, Tanio, Nadine, and Srigyan, Prerna. 2023.  "Reflections on Hermeneutical Injustice in K-12 Curriculum Development." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science. Honolulu, Hawaii, Nov 8-11.

The authors review literature on the datafication of health, which they identify as the way through which health has been quantified on a number of different scales and registers. They focus primarily on the datafication of health in clinical health care and self-care practices, rather than medical research and public health infrastructures. From this literature, they identify three key themes: datafied power (the ways through which data permeates and exerts power over forms of life), living with data (focused on datafication as an intimate form of surveillance, and a technology of the self), and data-human mediations (which emphasizes the nonhuman elements mediating datafication dynamics and experiences—such as algorithms, data infrastructure and data itself).

In examining literature on datafied power, the authors acknowledge a lack of scholarship on understanding data and datafication in terms agency, rather than simply power and domination. For instance, data is sometimes mobilized in “creative and even pioneering ways (Rapp 2016)” (265).

They describe literature on “living with data” as increasingly focus examining the social, narrative, and affective dimensions of data practices and experiences (e.g. work on the “Quantified Self,” a group seeking self-knowledge through numbers – a form of relationality that might be described as datasociality). Some scholars have argued that data can render “‘feelings and problems more tangible and comparable” (Sharon & Zandbergen 2016, p. 11)” (267). Some have also acknowledged as well a “curious resonance between the vision of empowered, resisting individuals that many ethnographers of self-tracking celebrate, and the rhetoric of consumer empowerment found in discourses of digital health (Schull 2017, Sharon 2017)” (267).

The literature on data-human mediations emphasizes the agency, liveliness and/or performativity of nonhuman elements—essentially, how they structure and shape the possibilities for action. For instance: “as social expectations of normality and health become embedded in tracking devices’ target numbers, presentation of scores, and gamified incentives (Depper & Howe 2017, Whitson 2013), a “numerical ontology” comes to suffuse everyday practices and “the ways in which people relate to their own bodies” (Oxlund 2012, p. 53; see also Jethani 2015, p. 40)” (269). Perspectives and action can be enabled or disabled by wide variety of factors: the design and performativity of data technology software (user interface, operational and analytical algorithms), hardware (devices, sensors), data itself (as illustrated in different ways), and data infrastructures (labs, data centers, serve and cloud storage, and networks that organize how data is stored and circulated). An analytically constructive focus in this literature has emerged by applying the concept of “assemblage” as a way of tracing how data moves: “where it flows, where it finds impasses, how algorithms act on it along the way” (270).

Lastly, the authors identify scholarship on “data activism” as an emerging focus on exploring how data technology capacities might be employed to promote social justice, collective action, and political participation, as well as to challenged dominant norms and ideologies: “Individual self-tracking data, for instance, can have social and political potential when it is pooled to identify health inequalities, collective environmental exposure, or disparities in quality of life (Gabrys 2014).” (271)