Rethinking rigor, knowledge hierarchies, and deskilled data collectors: An agenda for skilling research in global development

Timothy McLellan*, Ben Eyre

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Agricultural research for development (AR4D) often relies upon a centralized and mechanistic model of social science research. This is a model in which supposedly unskilled field officers (FOs) are recruited to implement household surveys that have been designed by faraway scientists. We argue that such research practices not only impede data quality and analysis but also devalue the work of FOs. We describe this phenomenon as a process of deskilling: One in which research protocols seek to limit the need for FOs to be skilled and also actively obscure the skilled work that FOs nevertheless do in the field. We link this process to a pervasive conception of “scientific rigor” that is grounded in an ideology of science as impersonal, disembodied, and mechanical. Drawing on feminist science and technology studies (STS), we highlight how the ideology and practice of deskilled research perpetuate colonial hierarchies of knowledge. We outline possibilities for and barriers to achieving more equitable and more generative relationships between scientists and FOs in AR4D.
Original languageEnglish
Pages (from-to)190-197
Number of pages8
JournalOutlook on Agriculture
Volume54
Issue number2
Early online dateMay 2025
DOIs
Publication statusPublished - 5 May 2025

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