Abstract
Efforts to improve the understanding of large scale land acquisitions (LSLAs) have been marred by methodological and epistemological challenges. Dominant approaches take a geopolitical lens that categorises the global north as ‘resource poor, financial haves’ and the global south as ‘resource rich, financial have-nots’ to generate data with often questionable accuracy. Case studies have prevailed to generate knowledge at community level that contributes to meta-analyses of LSLAs. However, as the post 2013 LSLA research agenda shifts from quantifying seized hectares of land and naming ‘land grabbers’ towards understanding processes of LSLAs, case studies have proved limited in sufficiently and systematically reflecting dynamics that underpin LSLAs that are local, national, regional and international in scope. The focus on case studies isolates studied cases from drivers and effects of LSLAs at different policy and geographic levels. This paper proposes a conceptual framework for improving our understanding of socio-economic and environmental implications of LSLAs at different policy and geographic levels. Literature has been reviewed on the methodological and epistemological challenges that have rendered elusive a comprehensive understanding of LSLAs. In addition, focus group discussion interviews were done in Nansanga farm block, a Zambian government-led LSLA program to complement reviewed literature. The framework is applied to the farm block. The interviews were therefore, done to qualitatively contribute to the understanding of positive and adverse lived experiences of community members following the LSLA program. Without claiming to be a panacea for challenges of researching LSLAs, the framework makes a compelling case for a mix of methodological approaches that simultaneously consider context specific micro level processes and how they are linked to broader, higher policy and geographic level spaces and contexts. The framework points to the danger of researching cases of LSLAs in isolation from their drivers/causes and effects/impacts at different policy and geographic levels.
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