Rethinking rigor, knowledge hierarchies, and deskilled data collectors: An agenda for skilling research in global development
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.
Authors
- Timothy McLellan (ORCID: https://orcid.org/0000-0002-2023-570X)
- Ben Eyre (ORCID: https://orcid.org/0000-0002-1944-4838)
Institutions
- University of East Anglia (GB)
- Australian National University (AU)
- Leverhulme Trust (GB)
Publication Details
- Journal
- Outlook on Agriculture
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1177/00307270251337111
- Primary Topic
- Income, Poverty, and Inequality
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Leverhulme Trust
- Economic and Social Research Council
- Division of Social and Economic Sciences
- H2020 European Research Council