‘The Production of Space’, in: Frans Jacobi, Imagine, Space Poetry, Copenhagen, 1996, unpaginated.

The Production of Space

Between Facts and Norms: Contributions to a Discourse Theory of Law and Democracy

Symposium Review: 25th Anniversary of Moral Boundaries by Joan Tronto

Authored by Dr. Safiya U. Noble, an assistant professor at the University of Southern California Annenberg School of Communication, this text is one of the preeminent works that explicitly addresse...

Algorithms of Oppression: How Search Engines Reinforce Racism

Edward W. Soja, Minneapolis, University of Minnesota Press, 2010, xviii+256 pp., indices, $24.95, ISBN 978-0-8166-6668-3 (paperback) The main argument of this book is that the spatial dimension has...

Seeking Spatial Justice

Data science is an interdisciplinary field that extracts insights from data through a multi-stage process of data collection, analysis and use. When data science is applied for social good, a variety of stakeholders are introduced to the process with an intention to inform policies or programs to improve well-being. Our goal in this paper is to propose an orientation to care in the practice of data science for social good. When applied to data science, a logic of care can improve the data science process and reveal outcomes of "good" throughout. Consideration of care in practice has its origins in Science and Technology Studies (STS) and has recently been applied by Human Computer Interaction (HCI) researchers to understand technology repair and use in under-served environments as well as care in remote health monitoring. We bring care to the practice of data science through a detailed examination of our engaged research with a community group that uses data as a strategy to advocate for permanently affordable housing. We identify opportunities and experiences of care throughout the stages of the data science process. We bring greater detail to the notion of human-centered systems for data science and begin to describe what these look like.

Care and the Practice of Data Science for Social Good

Researchers in human-centered computing have surfaced a feminist ethic of care in interaction with technologies, in data collection, and in data work. Drawing on two years of ethnographic fieldwork, we consider how democratic caring might be enacted and sustained through collaborative data work. We employ philosopher Joan Tronto's theory of caring democracy to structure our analysis of a resident-led initiative that uses data to organize and address issues of neglect and abandonment in their neighborhood. Adding to the CSCW literature on sociotechnical systems of care, we look particularly at Tronto's concept of caring democracy where caring needs and the ways in which they are met are an ongoing and inclusive process of assigning and reassigning caring responsibilities, characterized by both equality of voice and freedom from domination. This work develops grounded insight into the practice of democratic caring and how collaborative data work is relevant to this caring practice. We discuss opportunities and challenges for a data-supported caring democracy and address how caring democracy technologies are different from other modern civic technology practices. We conclude with a call to researchers to identify and enact democratic caring experiments in the small.

Collaborative Data Work Towards a Caring Democracy

In this paper, we document the counter-data action and data activism of a grassroots affordable housing advocacy group in Atlanta. Our observation and insight into these data activities and strateg...

https://journals.sagepub.com/doi/pdf/10.1177/2053951718796862

Grassroots resource mobilization through counter-data action:

Data has become central to the technologies and services that human-computer interaction (HCI) designers make, and the ethical use of data in and through these technologies should be given critical attention throughout the design process. However, there is little research on ethics education in computer science that explicitly addresses data ethics. We present and analyze Re-Shape, a method to teach students about the ethical implications of data collection and use. Re-Shape, as part of an educational environment, builds upon the idea of cultivating care and allows students to collect, process, and visualize their physical movement data in ways that support critical reflection and coordinated classroom activities about data, data privacy, and human-centered systems for data science. We also use a case study of Re-Shape in an undergraduate computer science course to explore prospects and limitations of instructional designs and educational technology such as Re-Shape that leverage personal data to teach data ethics.

Re-Shape: A Method to Teach Data Ethics for Data Science Education

Social media offers new ways for citizens to discuss and debate politics and engage in the democratic process. These online systems could be places for rich policy relevant debate, which is favored by scholars of deliberative democracy. Alternatively, social media might be a platform for an identity driven form of political discourse that is routinely scorned by scholars of democracy. To examine these two possibilities, we analyzed tweets sent during three national elections, the defining participatory process of democracy. Our dataset includes over 760,000 tweets gathered during national elections in Nigeria, Ghana and Kenya from 2011 to 2013. In order to analyze the degree to which Twitter was being used for policy relevant discussion we developed policy term sets through a text analysis of the major political party platforms. To examine the amount of discourse focused on identity issues we created identity term sets based upon national religious, tribal, and regional differences. In Nigeria, where divisive identity politics feed violence and electoral misconduct, discussion of tribe, region, and religion dominate mentions of platform policies. In contrast Ghanaians, who enjoy the most robust democracy of the three countries, were seven times more likely to discuss policy issues rather than identity. Kenyan democracy is still undergoing consolidation, and tweets again reflect this, with almost as many tweets devoted to tribal identity as campaign policy. These findings suggest that social media discussions may echo the state of democratic deepening found in a country during its national elections.

Amanda Meng

Papers

Care and the Practice of Data Science for Social Good

Collaborative Data Work Towards a Caring Democracy

Grassroots resource mobilization through counter-data action:

Re-Shape: A Method to Teach Data Ethics for Data Science Education

Twitter democracy: policy versus identity politics in three emerging African democracies