Call for papers: Critical data studies meet sociology

CALL FOR PAPERS

Special issue: Critical Data Studies meets Sociology

Guest editors: Ericka Johnson & Julia Velkova

New and powerful computational tools are changing the way many parts of society gather, analyze,and use data. This triggers a flurry of new empirical sites, theoretical reflections, and methodological approaches. It also highlights the political relevance and timely importance of the sociological considerations raised in the encounter with critical data studies.

In just over a decade, the field of critical data studies has grown into a vibrant, interdisciplinary arena for inquiry into the politics of computational and data-driven knowledge production. Scholars in this field tackle questions about the broad societal implications of “datafication”, often in terms of the reconfiguring of values, relations of power, inequalities and economies built around practices of recording and processing social data. This work draws inspiration from different strands of sociology, exploring shifting human-machine agencies and communication; objectivity, knowledge, and truthmaking claims. Others look at the performativity of data metrics and scores, as well as the values, materialities and labor that undergird data practices across a variety of sites, practices, and empiric objects. The field has also been developing an understanding about the experiences of everyday life with data, here, too, drawing on sociological work. Yet other researchers are exploring the material and infrastructural politics, that undergird large-scale computation technologies and defy industry narratives of ephemerality, automation, and immateriality. All in all, work in critical data studies spans across an ever-expanding array of social science perspectives and domains of social practice, including digital media, finance, urban and state governance, health, social services, climate science, environmental and energy politics, or warfare. It also animates questions about methods for doing analyses in these domains of social activity.

This special issue aims to showcase the generative tensions that occur when critical data studies meets sociology. Which questions and objects are fruitful and not fruitful to explore? What vocabularies, concepts and approaches we need to replace industry-driven buzz-word jargon like “AI”, “clouds”, or “digital twins”? What perspectives or methods do we lack or need more sustained engagement with?

Contributions may include, but are not limited to:

• Empiric engagement with the design or development of technologies that enable datafication – such as software systems, datasets, models, sensing devices, human and machine infrastructure
• Where and how critical methods can contribute to data technology evaluations
• Reflections on where/when in a data technology’s lifecycle critical engagement can be generative
• Discussions on using generative AI as a research or writing tool*
• New vocabularies and concepts that defy or nuance dominant industry buzz word jargon like “AI”, “digital twins” and “digital assistants”, “smart” things automated-decision making systems, etc.
• Inquiries into the temporalities of datafication, their uneven durations, failures, misfits and endings. These could include analyses of failed projects, decommissioned computational tools; the “retirement” of data technologies, platforms, software languages, models, etc. and/or the humans/expertise attached to them; or the need to abolish such.
• Analyses of the materialities of data – how do data practices relate to bodies, places, pipelines, cables, data centers, chemicals, carbon, lab equipment, minerals and fuels?
• Regional and/or historical perspectives and specificities of datafication – e.g. in Nordic welfare state contexts, Global South, or in other regions in the world
• Affectivities, lived experiences and changing human-machine relations with data computation technologies

Manuscripts can be written in Swedish, Norwegian, Danish, or English. We welcome empirical as well as theoretical texts from both junior and senior researchers. Articles should be between 4 000 – 10 000 words and book reviews 700 – 1 500 words. All articles undergo double-blind peer review. For further author instructions and information please visit www.sociologiskforskning.se.

The selection process is conducted in two stages. The deadline for extended abstracts (up to 2 000 words, including aim, methodological and theoretical framework, tentative results and conclusions as applicable to the chosen text form) is May 1, 2024. Abstracts should be sent to julia.velkova@liu.se

For the contributions that proceed, the deadline for full-length texts is September 30, 2024. Submission is at that point done via the journal's website. The issue is planned for the spring of 2025.

If you have any questions, please contact the editors of this special issue:

Julia Velkova: julia.velkova@liu.se

Ericka Johnson: ericka.johnson@liu.se

*All authors using ChatGPT or similar LLM tools are expected to clarify how and where in the text the tool was used and the author’s reflections on how the technology contributed to authorship, and how this form of authorship furthers understanding about key questions in the text