Subject: Critical Data Justice Literature
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Taking Data Literacy to the Streets: Critical Pedagogy in the Public Sphere
Author(s): Markham, A. N. Date: 2020 Publication: Qualitative Inquiry Citation: Markham, A. N. (2020). Taking Data Literacy to the Streets: Critical Pedagogy in the Public Sphere. Qualitative Inquiry, 26(2), 227–237. https://doi.org/10.1177/1077800419859024 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) This article describes an ongoing series of public arts–based experiments that build critical curiosity and develop data literacy via self-reflexive public interventions. Examined through the lens of remix methodology the Museum of Random Memory exemplifies a form of collective–reflexive meta-analysis whereby interdisciplinary researchers generate immediate social change and build better questions for future public engagement. The experiments help people critically analyze their own social lives and well being in cultural environments of growing datafication and automated (artificial intelligence [AI]-driven) decision-making. Reflexivity, bricolage, and critical pedagogy are emphasized as approaches for responding to changing needs in the public sphere that also build more robust interdisciplinary academic teams. -
Critical data ethics pedagogies: Three (non-rival) approaches
Author(s): Murillo, L. F. R. Wylie, C. & Bourne, P. Date: 2023 Publication: Big Data & Society Citation: Murillo, L. F. R., Wylie, C., & Bourne, P. (2023). Critical data ethics pedagogies: Three (non-rival) approaches. Big Data & Society, 10(2). https://doi.org/10.1177/20539517231203666 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) In a moment of heightened ethical questioning concerning data-intensive analytics, “data ethics” has become a site of dispute over its very definition in teaching, research, and practice. In this paper, we contextualize this dispute based on the experience of teaching data ethics. We describe how the field of computer ethics has historically informed the training of computer experts and how, in recent years, the scholarship on science and technology studies has created opportunities for transforming the way we teach with the inclusion of critical scholarship on relational ethics and sociotechnical systems. The emergent literature on “critical data ethics” has created a space for interdisciplinary collaboration that integrates technical and social science research to examine digital systems in their design, implementation, and use through a hands-on approach. As a contribution to the recent efforts to reimagine and transform the field of data science, we conclude with a discussion of the approach we devised to bridge technology/society divides and engage students with questions of social justice, accountability, and openness in their data practices. -
Becoming Racially Literate About Data and Data-Literate About Race: Data Visualizations in the Classroom as a Site of Racial-Ideological Micro-Contestations.
Author(s): Philip, T. M. Olivares-Pasillas, M. C. & Rocha, J. Date: 2016 Publication: Cognition and Instruction Citation: Philip, T. M., Olivares-Pasillas, M. C., & Rocha, J. (2016). Becoming Racially Literate About Data and Data-Literate About Race: Data Visualizations in the Classroom as a Site of Racial-Ideological Micro-Contestations. Cognition and Instruction, 34(4), 361–388. https://doi.org/10.1080/07370008.2016.1210418 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) Data visualizations are now commonplace in the public media. The ability to interpret and create such visualizations, as a form of data literacy, is increasingly important for democratic participation. Yet, the cross-disciplinary knowledge and skills needed to produce and use data visualizations and to develop data literacy are not fluidly integrated into traditional K–12 subject areas. In this article, we nuance and complicate the push for data literacy in STEM reform efforts targeting youth of color. We explore a curricular reform project that integrated explicit attention to issues pertaining to the collection, analysis, interpretation, representation, visualization, and communication of data in an introductory computer science class. While the study of data in this unit emphasized viewing and approaching data in context, neither the teacher nor the students were supported in negotiating the racialized context of data that emerged in classroom discussions. To better understand these dynamics, we detail the construct of racial literacy and develop an interpretative framework of racial-ideological micro-contestations. Through an in-depth analysis of a classroom interaction using this framework, we explore how contestations about race can emerge when data visualizations from the public media are incorporated into STEM learning precisely because the contexts of data are often racialized. We argue that access to learning about data visualization, without a deep interrogation of race and power, can be counterproductive and that efforts to develop authentic data literacy require the concomitant development of racial literacy. -
Is literacy what we need in an unequal society?
Author(s): Pinney, L. Date: 2020 Publication: Data Visualization in Society Citation: Pinney, L. (2020). Is literacy what we need in an unequal society? In H. Kennedy & M. Engebretsen (Eds.), Data Visualization in Society (pp. 223–238). Amsterdam University Press. https://doi.org/10.1515/9789048543137-018 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) Having the skills and awareness to make sense of data visualizations has become a contributing factor in determining who gets to participate in our data-driven society. Initiatives that seek to enable people to make sense of some aspect of our digital, dataf ied worlds are often described in terms of literacy. However, taking a closer look at different usages of literacy across academia, policy, and practice reveals dif ferent notions of power embedded in different populations’ implicit understanding of the term. Situated in the emerging f ield of critical data studies, the f ield that is concerned with understanding data’s role in reproducing and creating social inequalities, this is a conceptual chapter that asks how useful literacy is in this context. -
Data-bodies and data activism: Presencing women in digital heritage research
Author(s): Thompson, T. L. Date: 2020 Publication: Big Data & Society Citation: Thompson, T. L. (2020). Data-bodies and data activism: Presencing women in digital heritage research. Big Data & Society, 7(2). https://doi.org/10.1177/2053951720965613 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) As heritage-as-the-already-occurred folds into heritage-in-the-making practices, temporal and spatial fluidity is made more complex by digital mediation and particularly by Big Data. Such liveliness evokes ontological, epistemological and methodological challenges. Drawing on more-than-human theorizing, this article reframes the notion of data-bodies to advance data activist-oriented research in heritage. Focused primarily on women, it examines how their distributed agency and voice with respect to data practices and the (re)makings of (digital) heritage could be amplified. I describe three methodological directions, influenced by feminist work in critical data studies, which could be employed by researchers: attuning to and becoming with data, making data physical and changing narratives. From data-bodies to haunted data, performative data curation and mapping data-bodies, and attuning to data streams and re-voicing narratives, this article contributes to discussions of how to engage critically and creatively with the datafication of digital heritage practices, knowings and ontologies. -
Contributions of Paulo Freire for a Critical Data Literacy: a Popular Education Approach
Author(s): Tygel, A. F. & Kirsch, R. Date: 2016 Publication: The Journal of Community Informatics Citation: Tygel, A. F. & Kirsch, R. (2016). Contributions of Paulo Freire for a Critical Data Literacy: a Popular Education Approach. The Journal of Community Informatics, 12(3), 108–121. https://doi.org/10.15353/joci.v12i3.3279 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) Paulo Freire is the patron of education in Brazil. His main work – the Popular Education pedagogy – influences many educators all over the world who believe in education as a way of liberating poor oppressed people. One of the outcomes of Freire’s work is a literacy method, developed in the 1960’s. In this paper, we propose the adoption of elements of Freire’s Literacy Method for use in a pedagogical pathway towards data literacy. After tracing some parallels between literacy education and data literacy, we suggest some data literacy strategies inspired on Freire’s method. We also derive from it a definition for critical data literacy. -
Calling for a feminist revolt to decolonise data and algorithms in the age of Datification
Author(s): Vargas-Solar, G. Date: 2022 Publication: International Forum 2022 Citation: Vargas-Solar, G. (2022). Calling for a feminist revolt to decolonise data and algorithms in the age of Datification. International Forum 2022- Decolonial Perspectives on Gender, Sexuality and Patriarchy: art, activism and academia. https://doi.org/10.48550/arXiv.2210.08965 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) Feminist and women groups, indigenous communities and scholars in the global south/north refusing to adhere to hegemonic datafication programs have started to organise and fight back from the inside. The first essential step is to show and problematise technological progress exhibiting the poverty, violence, exclusion, and cultural erase promoted by this “progress”. The second step is to promote technology, algorithmic and artificial literacy. Education is critical to learn how to revert and revoke the datified digital twin already colonising all Earth’s societies silently and with impunity. It is not the colonisation of body-territories; it goes beyond and occupies humanity’s mind’s essence, i.e., imagination and imaginary. Against the colonisation of the imaginary, militant groups are imagining and designing alternative algorithms, datasets collection strategies and appropriation methods. The paper discusses their actions and alternative thinking. -
Data visualization literacy: A feminist starting point
Author(s): D’Ignazio, C. & Bhargava, R. Date: 2020 Publication: Data Visualization in Society Citation: D’Ignazio, C., & Bhargava, R. (2020). Data visualization literacy: A feminist starting point. In M. Engebretsen & H. Kennedy (Eds.), Data Visualization in Society (pp. 207–222). Amsterdam University Press. https://doi.org/10.2307/j.ctvzgb8c7.19 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces were, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives.’ -
The visible body and the invisible organization: Information asymmetry and college athletics data
Author(s): Greene, D. Beard, N. Clegg, T. & Weight, E. Date: 2023 Publication: Big Data & Society Citation: Greene, D., Beard, N., Clegg, T., & Weight, E. (2023). The visible body and the invisible organization: Information asymmetry and college athletics data. Big Data & Society, 10(1). https://doi.org/10.1177/20539517231179197 Section on webpage: Critical Data Justice Literature Tenets: Using technology intentionally to build communities and enhance learning. Annotation: (Abstract) Elite athletes are constantly tracked, measured, scored, and sorted to improve their performance. Privacy is sacrificed in the name of improvement. Athletes frequently do not know why particular personal data are collected or to what end. Our interview study of 23 elite US college athletes and 26 staff members reveals that their sports play is governed through information asymmetries. These asymmetries look different for different sports with different levels of investment, different racial and gender makeups, and different performance metrics. As large, data-intensive organizations with highly differentiated subgroups, university athletics are an excellent site for theory building in critical data studies, especially given the most consequential data collected from us, with the greatest effect on our lives, is frequently a product of collective engagement with specific organizational contexts like workplaces and schools. Empirical analysis reveals two key tensions in this data regime: Athletes in high-status sports, more likely to be Black men, have relatively less freedom to see or dispute their personal data, while athletes in general are more comfortable sharing personal data with people further away from them. We build from these findings to develop a theory of collective informational harm in bounded institutional settings such as the workplace. The quantified organization, as we term it, is concerned not with monitoring individuals but building data collectives through processes of category creation and managerial data relations of coercion and consent.