Data-driven governance and performances of accountability

Critical reflections from US agri-environmental policy

Bibliographic Data

ID12205802
AuthorsRitwick Ghosh (0000-0001-7751-1835, School for the Future of Innovation in Society, Arizona State University, corresponding author)
Year2023
Volume33
Issue1
Pages70-96
Publication date2023-02-08
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueScience as Culture (JOURNAL)
Journal identifiersISSN: 0950-5431 • E-ISSN: 1470-1189
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/09505431.2023.2175654
OpenAlexW4319595445
LanguageEN
Citations received7
References cited45

Public institutions have increasingly responded to calls for more accountability by promoting ideas of data-driven governance. As this focus on using data tools to strengthen governance intensifies, it is important to examine how the tools that underlie such claims are made. In the context of US agri-environmental policy, policy leadership has spoken the language of data-driven decision-making for over thirty years, primarily in response to accountability demands. However, the reliance on metrics and calculation is most explicit in the newest initiative called the Conservation Stewardship Program (CSP). Unlike other initiatives, the CSP used a single environmental scoring and decision-making algorithm to allocate approximately US$3.8 billion to 68,000 farmers. Applying a Social Construction of Technology approach to the development of the tool shows that different social groups – political aides, program officials, and subject-matter specialists – interpreted data-driven governance differently. Tool design emerges not despite but through the contestations over the purpose and practicality of doing data-driven governance. Social groups involved in tool development are themselves embedded in different accountability structures that shape the rationalities they marshal when negotiating practical decisions about tool design. The final tool used in the CSP was technically contested and the tool development process was poorly documented, yet it had an important legitimacy function: it deflected accountability pressures for more rationalization in public spending without causing major policy disruption. Centering analysis on the negotiations entailed in making the tools that come to underlie claims of data-driven governance can explain how and to what extent a push for more data in public policy can strengthen (and weaken) accountability relations.KEYWORDS: Data-driven governancesocial construction of technologyenvironmental accountingaccountabilityagricultural policy AcknowledgmentsI thank Allison Loconto, the journal editors, and the three anonymous reviewers for their generous feedback through the review process. I am grateful to the organizers and participants of the 2018 Summer Institute on the Critical Studies of Environmental Governance in Toronto, Canada for the opportunity to workshop the paper. I also thank Kristine Ann Bybee-Finley, Ranjit Singh, and Samir Passi for their stimulating discussions on the paper. A special thanks to Trevor Pinch, Wendy Wolford, Todd Walter, and Steven Wolf who reviewed earlier versions of the paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by National Institute of Food and Agriculture.Notes on contributorsRitwick GhoshRitwick Ghosh is a Postdoctoral Research Fellow with the New Carbon Economy Consortium, hosted at Arizona State University. Ritwick received his PhD from Cornell University and also completed a Faculty Fellowship at New York University

Accountability · Business · Context (archaeology · Corporate governance · Data governance · Data quality · Economics · Environmental governance · Legitimacy · Management · Negotiation · Political science · Politics · Process management · Public relations · Rationalization (economics · Sociology · Stewardship (theology · Agricultural Innovations and Practices · Public Administration · Marketing

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