The main purpose of this paper is to take stock of some of the most significant results emanating from The International Development Research Centre (IDRC)‐supported programmes, in recent years in the area of organizational capacity development, and feeding into the consultation process for the formulation of IDRC`s next Corporate Strategy Program Framework (CSPF) for the 2010‐2015 period.
Many capacity development (CD) programs and processes aim at long‐term sustainable change, which depends on seeing many smaller changes in at times almost invisible fields (rules, incentives, behaviours, power, coordination etc.). Yet, most evaluation processes of CD tend to focus on short‐term outputs focused on clearly visible changes.
In this article is presented an emergent capacity development approach that the authors have developed through participatory action research in Peru and Ecuador, which they call ‘systemic theories of change’ (STOC), for organisational capacity development. They argue that capacity development should be understood as systemic learning. The STOC approach promotes reflection about how we as individuals, organisations, and broader social groups and societal configurations, understand how change occurs.
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.
The process of knowledge brokering in the agricultural sector, where it is generally called agricultural extension, has been studied since the 1950s. While agricultural extension initially employed research push models, it gradually moved towards research pull and collaborative research models. The current agricultural innovation systems perspective goes beyond seeing research as the main input to change and innovation, and recognises that innovation emerges from the complex interactions among multiple actors and is about fostering combined technical, social and institutional change.