Digitization as politics: Smart farming through the lens of weak and strong data

This paper offers an alternative approach for engaging sociologically, ontologically, and politically with digital farming platforms. A challenge faced by any approach looking to upend intellectual conventions, especially ontological ones, lies in the question of representation, namely, how do we ta...

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Bibliographic Details
Published inJournal of rural studies Vol. 91; pp. 208 - 216
Main Author Carolan, Michael
Format Journal Article
LanguageEnglish
Published Elmsford Elsevier Ltd 01.04.2022
Elsevier Science Ltd
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Summary:This paper offers an alternative approach for engaging sociologically, ontologically, and politically with digital farming platforms. A challenge faced by any approach looking to upend intellectual conventions, especially ontological ones, lies in the question of representation, namely, how do we talk about digitization in novel theoretical ways using language rooted in more than two millennia of western human-centered thought? One way to deal with this challenge, the one adopted in this paper, involves decentering familiar terms and repurposing them. Thus, rather than organizing the argument around familiar terms like small and big data, I argue instead that we organize data-assemblages according to what they do, which makes this a political ontological project. To do this, I offer the relational predicate of weak data and strong data, suggesting that they are good to think with in this regard. The argument ultimately lands at a place for analyzing these platforms that offers the potential for critique and perhaps even a degree of optimism, as I suggest a framework for normatively evaluating these practices. The paper draws upon various empirical studies of digital agriculture conducted by the author, which include interviews with farmers, farm laborers, hacktivists, investors, and engineers from numerous countries and locales. •Digital farming platforms ought to be judged by what they do.•The outcomes and impacts of Agriculture 4.0 are unevenly distributed.•More social science research is needed on the subject.
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ISSN:0743-0167
1873-1392
DOI:10.1016/j.jrurstud.2020.10.040