2017
DOI: 10.1080/14735903.2017.1314754
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A new professionalism for agricultural research for development

Abstract: There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies. In this paper, we share learning from efforts to mainstream such an approach thr… Show more

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Cited by 32 publications
(12 citation statements)
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“…There is now a new suite of complexity-aware approaches to evaluation most prevalent in the development sector (e.g., [68][69][70][71][72]) that employ reflexive use of theory of change as both a process and a product. In contrast to a linear view of change and measurement approach to impact, the approach argues for a combination of inductive and deductive reasoning-through reflecting on underlying assumptions about how change happens that have been made explicit at the outset (double loop learning)-it is possible to build middle range theory of how change happens, as it happens.…”
Section: Transformation Emergence and Evaluationmentioning
confidence: 99%
“…There is now a new suite of complexity-aware approaches to evaluation most prevalent in the development sector (e.g., [68][69][70][71][72]) that employ reflexive use of theory of change as both a process and a product. In contrast to a linear view of change and measurement approach to impact, the approach argues for a combination of inductive and deductive reasoning-through reflecting on underlying assumptions about how change happens that have been made explicit at the outset (double loop learning)-it is possible to build middle range theory of how change happens, as it happens.…”
Section: Transformation Emergence and Evaluationmentioning
confidence: 99%
“…CSA is a set of guiding principles for farmers to adapt to growing natural resource constraints and increasingly unpredictable weather conditions [15,16]. CSA is defined by three objectives: (i) increasing agricultural productivity to support increased incomes, food security, and development; (ii) increasing adaptive capacity and resilience to climate variability at multiple levels (from farm to nation); and (iii) decreasing greenhouse gas emissions where possible and appropriate [17].…”
Section: Introductionmentioning
confidence: 99%
“…The traditional linear approach for technology development and transfer involves upstream research institutions that engage in scientific discovery and proof-of-concepts, which once validated, are handed over to downstream practitioners for piloting, who in turn transfer technologies and products to extension services who pass them to farmers. The focus has now shifted to the facilitation of learning and joint action in multi-stakeholder settings, often in relation to innovation systems [17]. In this context, an active and continuous reassessment of the necessary field conditions, genotypes, agronomic management practices, and enabling policies calls for a continual stream of validated upstream research products suitable for downstream adoption and adaptation.…”
Section: Introductionmentioning
confidence: 99%
“…A focus on learning in impact assessment gives more attention to the questions of how and why research activities have contributed to positive change and what lessons can be drawn to inform future activities (Horton and Mackay 2003). Douthwaite et al (2017a) have called for a 'new professionalism' in agricultural development,…”
Section: Discussionmentioning
confidence: 99%
“…The uncertainty of change processes supports a renewed focus on learning and capacity building within innovation systems (Douthwaite et al 2017a). Hall argues for an approach to capacity building that extends beyond support for technical science skills to include building skills in partnering with diverse (non-research) organisations, networking, policy development, and supporting institutional learning and change (Hall 2002(Hall , 2005.…”
Section: Multiple-source and Systems Modelsmentioning
confidence: 99%