The role of civil society in influencing public opinion towards more democratic and developmental approaches is now well-recognised in diverse fields such as health, education, livelihoods, issues relating to disadvantaged social groups and the environment. Yet, science and technology in India is predominantly seen as the preserve of the state, and more recently the market. In the linear model of innovation, civil society is seen at best as having a role in extension or the delivery of technology produced elsewhere.
The Community Based Participatory Monitoring and Evaluation (CB-PME) tool empowers poor local farming communities to improve their livelihoods. While this process is people centred, it draws on local people’s capacities, while giving the end users of a technology a voice. The experience of the Katamata farmers’ group in Tororo district using PM&E (the participatory approach to monitoring and evaluation) is given in this paper.
There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.
This paper identifies market failures that limit agricultural R&D for Africa and other resource-poor environments, and proposes a way to complement existing institutions with cash prizes for the dissemination of successful new technologies adopted by low-income farmers. The proposed prize institution would use agronomic experiments and farm surveys to document the value of innovations after their initial diffusion, and offer payments in proportion to estimated social benefits in target regions.
Biotechnology offers great potential to contribute to sustainable agricultural growth, food security and poverty alleviation in developing countries. Yet there are economic and institutional constraints at national and international levels that inhibit the poor people's access to appropriate biotechnological innovations.
Local innovation refers to the dynamics of Indigenous Knowledge (IK) - the knowledge that grows within a social group, incorporating learning from own experience over generations but also knowledge gained from other sources and fully internalized within local ways of thinking and doing. Local innovation is the process through which individuals or groups discover or develop new and better ways of managing resources - building on and expanding the boundaries of their IK.
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This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.
This paper discusses the challenges and determinants of agro-operations and innovation initiatives in developing countries. With particular reference to the Caribbean region, available country statistics and data are analysed. A generic model of collaborative innovation for agriculture that stresses collaboration among the stakeholders (government, knowledge institutions, public and private firms and others) is described.
This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.
This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.