Social learning in multi-actor innovation networks is increasingly considered an important precondition for addressing sustainability in regional development contexts. Social learning is seen as a means for enabling stakeholders to take advantage of the diversity in perspectives, interests and values for generating more sustainable practices and policies. Although more and more research is done on the meaning and manifestations of social learning, particularly in the context of natural resource management, little is known about the social dynamics in the process of social learning.
This brief report lays out ten theories of advocacy and policy change. These theories are intended to articulate the policy making process and identify causal connections supported by research to explain how and why a change may or may not occur. It further provides examples of the way in which advocates, funders, and evaluators can use these theories in their work.
The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is a research in development program which aims to foster innovation to respond to community needs, and through networking and social learning to bring about development outcomes and impact at scale. It aims to reach the poorest and most vulnerable communities that are dependent upon aquatic agricultural systems. AAS uses monitoring and evaluation to track progress along identified impact pathways for accountability and learning.
This paper captures lessons from recent experiences on using ‘theories of change’ amongst organisations involved in the research–policy interface. The literature in this area highlights much of the complexity inherent in the policymaking process, as well as the challenges around finding meaningful ways to measure research uptake. As a tool, ‘theories of change’ offers much, but the paper argues that the very complexity and dynamism of the research-to-policy process means that any theory of change will be inadequate in this context.
This report refers to the workshop which was held on October 21-25, 2013 at ILRI Campus in Nairobi, Kenya. The workshop involved a variety of sessions which made use of presentations, card exercises, group work and discussions to facilitate the engagement of the participants in sharing, learning, discussing and planning around CapDev in CGIAR. This report provides an overview of the workshop sessions, focusing mainly on the key discussion topics, results and next steps.
This paper has been prepared under the guidelines provided by the TAP Secretariat at the FAO, as a contribution to the G20 initiative TAP, which includes near 40 partners and is facilitated by FAO. Its purpose is to provide a Regional synthesis report on capacity needs assessment for agricultural innovation, with capacity gaps identified and analyzed, including recommendations to strengthen agricultural innovation systems (AIS) and draft policy recommendations to address the capacity gaps.
The agricultural innovation systems approach emphasizes the collective nature of innovation and stresses that innovation is a co-evolutionary process, resulting from alignment of technical, social, institutional and organizational dimensions. These insights are increasingly informing interventions that focus on setting up multi-stakeholder initiatives, such as innovation platforms and networks, as mechanisms for enhancing agricultural innovation, particularly in sub-Saharan Africa.
This paper is an attempt to take stock of the authors' work. In Section 2, the authors reflect upon the emergence and fairly rapid diffusion of the concept ‘national system of innovation’ as well as related concepts. In Section 3, they describe how the Aalborg-version of the concept evolved by a combination of ideas that moved from production structure towards including all elements and relationships contributing to innovation and competence building.
This report describes the 2012 NAIS Assessment was piloted in 4 countries: Botswana, Ghana, Kenya and Zambia. Data were collected through a survey questionnaire, open-ended interview questions, and data mining of secondary sources. A team led by a national coordinator took charge of data collection from various partner organizations in each country.
The paper explores the implications of rural livelihood diversity for agricultural innovation policies. It summarises literature on the nature of rural poverty, with particular emphasis on the relative roles of farm and non-farm income. It also reviews the various roles, direct and indirect, that agricultural innovation can play in rural poverty reduction. Finally, it uses an agricultural knowledge and information systems (AKIS) perspective to argue for a differentiated approach to targeting agricultural innovations, based on an analysis of rural assets.