We are facing complex societal problems such as climate change, human conflict, poverty and inequality, and need innovative solutions. Multi-stakeholder processes (MSPs) are more and more seen as a critical way of coming to such innovative solutions. It is thought that when multiple stakeholders are able to meet, share experiences, learn together and contribute to decisions, new and innovative ways of dealing with problems are found and turned into action. Still, much remains to be understood about the role and effectiveness of social learning in multi-stakeholder settings.
The present manual provides a reference framework for the strategic and operational work in the field of capacity development. It is addressed to all staff of ADC in Austria as well as in the coordination offices, to non-governmental and implementing organisations, to stakeholders in partner countries, other donors and members of the public interested in development policy.
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 introduces a new research framework for social learning, to be able to derive ways to facilitate social learning. The authors report on an explorative interview study to substantiate the framework. One interesting conclusion was that hidden agenda’s were shown to undermine trust, which in turn undermined the social learning process. This explains the importance of openness for social learning. Research results show substantiate the research framework, and show that it can be used to derive methods to facilitate social learning.
The present case study investigated a policy-induced agricultural innovation network in Brandenburg.
This report has the aim of contributing to the PRO AKIS overall goal of exploring and identifying the possibilities, conditions and requirements of rural networks to enhance the farmers’ ability to create, test, implement and evaluate innovation in cooperation with other actors.In particular, the report presents two cases: the Small Fruit Cluster (SFC) and the Drosophila Suzukii Monitoring (DSM) network. The SFC is a nationwide, multi-actor network composed of several actors, interacting in the small fruit sector in Portugal.
This report compiles country-reports that describe the agri-food research landscape in 2006/2007 in 33 countries associated to the 6th Framework Programme (FP6), which defined the European for the period from 2002 to 2006. Each country-report presents information about the main research players in 2006/2007 and about the current trends and the future needs for research topics and for the organisation of the agri-food research system.
This document provides a review of existing reports regarding the agri-food research landscape in 2006/2007 for 14 EU countries (Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia, Turkey) and also explores trends and needs in other EU or associated countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, Norway, Portugal, Spain, Sweden, Switzerland, The Netherlands, United Kingdom).
As the name suggests, the original aim of the Rural Knowledge Network (RKN) was to make more information available specifically about markets, to smallholder farmers. The core idea was to provide information to farmers and traders about current market prices in different markets around the country. This was done by building a network of entrepreneurs who regularly collected the price information and sent it to a central collecting Internet platform facility.
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.