scholarly journals Theoretical Bases of Critical Data Studies

2020 ◽  
Vol 58 (1A(115A)) ◽  
pp. 96-109
Author(s):  
Łukasz Iwasiński

Purpose/Thesis: The paper presents main premises and analyzes the theoretical bases of critical data studies (CDS). Approach/Methods: The article uses critical review of the literature on CDS, social aspects of big data, sociology of knowledge, philosophy of knowledge and science and technology studies. Results and conclusions: Author identifies three main theoretical premises of CDS: (1) A critique of market-oriented instrumental rationality; (2) Rejection of the idea that data is independent from the research process; (3) Rejection of the concept of raw data. Article discusses intellectual roots of CDS. It is argued that CDS derive from constructivist sociology of knowledge, and science and technology studies. Originality/Value: The article brings together theoretical literature and empirical studies from diverse disciplinary fields to examine theoretical bases of CDS and situates it in its intellectual context. It stresses the need of critical view of data and data processing, which is especially important in the big data area. CDS are recognized in cultural studies and media studies (however poorly discussed in related Polish scholarship), but they remain almost absent in Information Studies, which would benefit from it.

2018 ◽  
Vol 5 (2) ◽  
pp. 205395171881819 ◽  
Author(s):  
Daniel Carter

Recent work on Big Data and analytics reveals a tension between analyzing the role of emerging objects and processes in existing systems and using those same objects and processes to create new and purposeful forms of action. While the field of science and technology studies has had considerable success in pursuing the former goal, as Halford and Savage argue, there is an ongoing need to discover or invent ways to “do Big Data analytics differently.” In this commentary, I suggest that attempts to produce new ways of working with Big Data and analytics might be hindered by how science and technology studies-influenced scholars have conceptualized assemblages. While these scholars have foregrounded objects’ relations within existing assemblages, new materialist philosophers draw attention to properties of objects that transcend those relations and might indicate opportunities for more creative or generative uses of Big Data and analytics.


Data & Policy ◽  
2021 ◽  
Vol 3 ◽  
Author(s):  
Annalisa Pelizza ◽  
Stefania Milan ◽  
Yoren Lausberg

Abstract The COVID-19 pandemic confronts society with a dilemma between (in)visibility, security, and care. While invisibility might be sought by unregistered and undocumented people, being counted and thus visible during a pandemic is a precondition of existence and care. This article asks whether and how unregistered populations like undocumented migrants should be included in statistics and other “counting” exercises devised to track virus diffusion and its impact. In particular, the paper explores how such inclusion can be just, given that for unregistered people visibility is often associated with surveillance. It also reflects on how policymaking can act upon the relationship between data, visibility, and populations in pragmatic terms. Conversing with science and technology studies and critical data studies, the paper frames the dilemma between (in)visibility and care as an issue of sociotechnical nature and identifies four criteria linked to the sociotechnical characteristics of the data infrastructure enabling visibility. It surveys “counting” initiatives targeting unregistered and undocumented populations undertaken by European countries in the aftermath of the pandemic, and illustrates the medical, economic, and social consequences of invisibility. On the basis of our analysis, we outline four scenarios that articulate the visibility/invisibility binary in novel, nuanced terms, and identify in the “de facto inclusion” scenario the best option for both migrants and the surrounding communities. Finally, we offer policy recommendations to avoid surveillance and overreach and promote instead a more just “de facto” civil inclusion of undocumented populations.


Author(s):  
Silke Gülker

This chapter begins by identifying an imbalance in the sociology of science and technology. Across sociology, hardly anyone would object to the idea that science is a social process. Science and technology studies and the sociology of science have deconstructed scientific work and revealed how it is socially embedded in many ways. From this perspective, scientific knowledge is co-produced by scientific and non-scientific actors in a process influenced by class, gender, and culture. Few authors, however, have investigated the role that religion might play in this process of knowledge production. This is striking because this relationship was one of the most important topics in the early stages of sociology of science, which is one of the forerunner fields of science and technology studies. This chapter discusses the work of two pioneering authors in sociology of science, Robert K. Merton and Ludwik Fleck. While Merton’s work can still be inspiring for contemporary investigations of the relationship between science and religion on a meso- and macro-level, Fleck’s concept of ‘thought collectives’ and ‘thought styles’ asks for comparative empirical studies on a micro-level. Against this background, the chapter presents an idea of how to implement such micro-level empirical work beyond the science versus religion dichotomy: specifically, by analyzing transcendence constructions, demonstrated here in the field of stem cell research.


2020 ◽  
Author(s):  
Ingmar Lippert

The PhD thesis and its related publications address how a carbon footprint of a multinational company was enacted. Related publications draw out a range of implications of this analysis for, inter alia, the sociology of the environment, Science and Technology Studies (STS), social studies of Big Data, the sociology of numbers and quantification.


2017 ◽  
Vol 3 ◽  
pp. 16 ◽  
Author(s):  
Yanni Loukissas ◽  
Anne Pollock

When widespread polling failed to accurately predict the 2016 US presidential election, producers and consumers of data didn’t abandon faith in numbers. Instead, they have reconfigured their relationships with big data. Producers are formulating redemption narratives, blaming specific datasets or poor interpretation, and the broader reception looks similar. Seeking an explanation for Trump’s unexpected victory, news audiences are calling out failed pre-election polling numbers, while at the same time embracing empirically dubious exit polls. This Critical Engagement piece argues that Science and Technology Studies scholarship has prepared us to see that polling errors would not undo the prestige and power of quantitative methods, but rather reveal the intensity of our attachment to data as a readily available arbiter. We show that data’s ambivalent qualities make it a durable ground for claims-making, with the capacity to be mobilized to do different kinds of work: blame, exoneration, and broader sense-making.


2018 ◽  
Vol 72 (1) ◽  
pp. 87-116
Author(s):  
Basile Zimmermann

Abstract Chinese studies are going through a period of reforms. This article appraises what could constitute the theoretical and methodological foundations of contemporary sinology today. The author suggests an approach of “Chinese culture” by drawing from recent frameworks of Science and Technology Studies (STS). The paper starts with current debates in Asian studies, followed by a historical overview of the concept of culture in anthropology. Then, two short case studies are presented with regard to two different STS approaches: studies of expertise and experience and the notion of interactional expertise, and the framework of waves and forms. A general argument is thereby sketched which suggests how “Chinese culture” can be understood from the perspective of materiality.


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