Summary
This paper addresses the opacity in farm typology construction by developing a generalised framework that explicitly identifies and quantifies the impact of subjective decisions on classification outcomes. The authors have encapsulated this framework in an open-source RShiny application (TypologyGenerator) to improve reproducibility and enable practitioners to make informed decisions about farm categorisation without requiring deep technical expertise. The work is particularly relevant for sub-Saharan African contexts where farm typologies are widely used for research design, intervention targeting, and upscaling.
UK applicability
Whilst developed with sub-Saharan African smallholder systems in mind, the generalised framework and TypologyGenerator tool may have utility in UK farming systems research for systematically categorising diverse farm types and improving transparency in sampling design. However, direct application would require adaptation to UK farm size distributions, enterprise types, and agro-climatic conditions.
Key measures
Subjective decision points in farm typology construction and their impact on resulting farm classifications
Outcomes reported
The study presents a generalised framework for constructing farm typologies and quantifies how subjective decisions impact the resulting typologies. The framework has been implemented as an open-source RShiny application (TypologyGenerator) to support end-users in farm classification decisions.
Topic tags
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