Analyze

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)

Drawing on a long career as a Black critical health equity researcher, Bowleg quotes Black feminist Audre Lorde in arguing that the “master’s tools”—in order words, conventional theories and methods—"will never dismantle the master’s house”—intersectional structures of oppression from which health inequities are produced. Bowleg elaborates by explaining that conventional theories and methods “valorize almost exclusively individualistic and social cognitive approaches (Cochran & Mays, 1993; Weber & Parra-Medina, 2003); ignore the foundational roots of structural and intersectional inequality (Bowleg, 2012, 2020); center White, Western, cisgender male, middle-class, and heterosexual people and their experiences as normative (Henrich et al., 2010); prioritize amelioration, not transformation (Fox et al., 2009a); and view Black people primarily through the lens of deficit or pathology” (237).

Thus Bowleg offers 10 critical lessons for Black and other health equity researchers of color that she links with system and structural-level strategies. Bowleg also cautions that these lessons are risky and could damage one’s academic career—but that it is exactly this kind of risk that is necessary for change. Among these include: embrace critical perspectives, embrace a critical qualitative stance, learn research paradigms (e.g. positivist paradigm = a master’s tool, must learn to counter), foster community-based partnerships and collaborations, and highlight black communities’ strengths, assets, and acts of resistance. Bowledge also encourages researchers to “tell it like it is”: “Epistemological ignorance is one of the master’s most formidable tools. Epistemologies of ignorance refer to the examination of different types of ignorance and their production, maintenance, and functions (Sullivan & Tuana, 2007)” (239). Here, Bowleg emphasizes the importance of language by discussing how it can alternatively reveal or obscure structures of oppression as well as it shapes the nature of research.

 “Under a 1986 federal law titled the Emergency Medical Treatment and Labor Act (EMTALA), hospitals are required to treat people who come to the ED presenting with an emergency medical condition, defined as a condition that, without treatment, will likely lead to serious impairment or death. … EMTALA is one of the largest federal mandates to provide services to have gone unfunded (Friedman 2011); costs instead fall on states and local health care systems.” 481

“In bringing ethnographic attention to hot spotting as a technique of governance, we find that it provides lifesaving humanitarian interventions while operating within the racialized structures of violence that produce continual life crises. The institutional rationality of hotspotting and the encounters of care that it produces illustrate the often-contradictory role of medicine in the lives of poor people: both caring and coercive, it intertwines care and violence.” 475; “we conclude by suggesting that economic investment and return are becoming a reigning logic in the governance of poverty, generating hot spots as sites of interest for both policing and health care and decentering normative assessments of deviance, illness, and social problems” 476; “Neoliberal social assistance, as it is practiced in the health care safety net, is conceptualized as an “investment “in the population, as a strategic and targeted deployment of basic resources, one that promises to generate a return on investment for the state or health system in the form of cost savings.“ 485

The authors examine the practice of “hot spotting,” a form of surveillance and intervention through which health care systems in the US intensively direct health and social services towards high-cost patients.  Health care hot spotting is seen as a way to improve population health while also reducing financial expenditures on healthcare for impoverished people. The authors argue that argue that ultimately hot spotting targets zones of racialized urban poverty—the same neighborhoods and individuals that have long been targeted by the police. These practices produce “a convergence of caring and punitive strategies of governance” (474). The boundaries between the spaces of healthcare and policing have shifted as a “financialized logic of governance has come to dominate both health and criminal justice” (474).

The authors offer a review of themes within occupational health and environmental public health surveillance over the past decade. In reviewing the history of public health surveillance, the authors highlight key acts of Congress in the 1970s that have made the development of “modern” occupational health and environmental health surveillance possible—but which also failed to develop into a cohesive and well-connected data management systems across federal agencies. Separate agencies were tasked with different data collection, management and intervention tasks in ways that fragmented the surveillance system to the point of ineffectiveness.

The authors argue that effective surveillance for occupational and environmental health demands development of a clear purpose for collecting data and having the data available to make meaningful analysis possible. They turn to the CDC’s childhood lead prevention program to demonstrate these points.

• The process of designing curriculum is quite useful as it details how different activities correspond to learning goals in science, mathematics, and technology. Fig. 3 describes the steps: selecting content through content specialists in the POAC team, making a curriculum outline, individual meetings with content specialists, and making the lesson plans. I really like the activities they designed, such as comparing different mask materials and how they protected against differently-sized viruses. They were also given time to research career pathways and present on epidemiology careers, a step that invites students to imagine career pathways. 

• I realize the scope and audience of this paper is different, but I am so curious about how the Imhotep Academy created a setting that encouraged underrepresented students to participate and speak up, given that they cite evidence of how difficult that can be. How did they choose participants? 

• Having read Freire’s Pedagogy of the Oppressed recently, I am thinking about his approach to curriculum design that is based on a feedback loop between would-be learners and would-be educators. The roles of learners and educators aren’t fixed. Content development is not done beforehand just by content specialists but in an iterative process with multiple feedback loops. Since very few research teams have the time or the resources to deploy Freire’s rigorous approach, I am not surprised that most curriculum development does not follow the route. And educators are working with former experiences anyway. So I am curious about how the authors’ previous experiences shaped their approach to curriculum design?

• A context for this paper is the controversy on the proposed revisions to the California math curriculum that conservative media outlets argue “waters down” calculus–a cherry topping on the college admissions cake–to privilege data science in middle-school grades. Education researchers contend that apart from physics and engineering majors, not many colleges actually require calculus for admissions (many private institutions do), and that the relevance of advanced calculus for college preparation is overrated. 

• National Commission on Excellence in Education ‘s 1983 report Nation At Risk: the need for a new STEM workforce specializing in computer science and technology 

• National Council on Mathematics 2000 guidelines for preparing American students for college in Common Core Mathematics 

• Stuck in the Shallow End: Virtual segregation; Inequality in learning computer science in American schools focusing on Black students 

"Far from being anti-science and anti-education, BP has successfully embedded itself at the heart of elite UK science and education policy and practice networks – in particular, networks focused on development and delivery of STEM (Science, Technology, Engineering and Mathematics) education. Rather than limiting itself to the narrow promotion of pro-petroleum rhetoric, BP has long seen its interests as being best served by the general promotion of pro-business practices and values throughout UK public education. Petro-pedagogy, in the case of BP at least, is best understood as a core component of a more extensive corporate education reform network that, for the past decade, has focused on promoting a neoliberal model of STEM education in schools" p. 475

"This brings us back to the argument of Eaton and Day (2019) that began this article: to tackle the crisis of climate change, we ‘need to dismantle the corporate power of the fossil fuel industries and their petro-pedagogy’ (15). Doing this, however, will require a far different model of STEM education: one that can help students ‘understand how manipulative politics, economic power and myth making PR are subverting public democratic will,’ and encourage ‘young people to apprentice as critical scientific policy analysts,’ and ‘create innovative counter-narratives to the old dysfunctional stories of intensifying carbon dependence’ (Elshof 2011, 15)." p.486

• The examples of community and participatory-based work in action can be used to talk about the importance of qualitative data and how to frame people without formal scientific training as experts and engaged researchers. 

• I am curious if theater of the oppressed has been used in STEM and/or environmental education? Found the following

• Liberatory Science Education: Weaving Connections Between Feminist Theory and Science Education

• Challenging Social Exclusion in Computing via 'Theatre of the Oppressed' Pedagogy | Proceedings of the 51st ACM Technical Symposium on Computer Science Education

• http://www.labtecgc.udesc.br/tabd1/handle/123456789/18315 

• Review of Drama in Science Education

• Raphale’s call for future research along the following lines: systems thinking, investigation into why things work and fail, how aspirations of collaborative projects are met and unmet, how indeterminacy and complexity characterize participatory action and research–are questions that I am interrogating through my research as well. 

• The table on p. 26 on “Levels of Community Participation in Research” naturally raises the question for the reader: Where on this continuum are we? 

• The concise overview of engaged scholarship models: how do they overlap with similar approaches in pedagogy?

• What political developments have shaped engaged scholarship? For example, neoliberal restructuring has appropriated CBPR for market-oriented research and strengthened corporate-humanitarian networks rather than developing community capacities. 

• I want to think more about the idea of the timeline of community-university partnerships: are there benefits to short-term partnerships as well? Do all partnerships need to be sustainable to be mutually beneficial and meaningful?