Applying Complexity to Evaluation: Case Based on the GEF’s Resilient Food Systems Program: Integrated Landscape Management to Enhance Food Security and Ecosystem Resilience.
Applying Complexity to Evaluation: Cases Based on the Global Environment Facility’s Resilient Food Systems Program
I have been working on a research proposal to study whether and how constructs from Evolutionary Biology and Ecology might be useful in Evaluation. This is the second of two posts that come from the introductory material in the first proposal. The first is: Evolutionary and Ecological Thinking – Escaping Disciplinary Boundaries.
I have been working on a research proposal to study whether and how constructs from Evolutionary Biology and Ecology might be useful in Evaluation. This is the first of two posts that come from some of the introductory material in the proposal. The second is: Evolutionary and Ecological Constructs that may be Useful in Evaluation.
The graphic superimposes a chessboard on a random walk. It symbolizes a core challenge in evaluation. The Chessboard Program outcomes are predictable in the commonsense definition of predictability.“If I provide service X, outcome A will occur.” That statement is a model: X-->A, and it is the foundation of almost every evaluation model I have seen. … Continue reading What Does the Graphic Header say About Evaluation?
A friend of mind and I were discussing the nature of AEA. I have come to quite a few conclusions about this, but my current thinking is more in the way of questions than answers. As I see it, what’s needed is an exploration of four questions. Where does the evaluation that we do fit … Continue reading Four facets of AEA. Four questions. No answers provided.
In recent years, the evaluation community has been looking to “complexity” as a source for addressing these difficulties.
I am involved in a project that involves helping people make a single choice among multiple technologies. They must commit to one, so there is no waffling. This is one more of many such exercises that I have been involved in over the course of my career, and I have never been fully satisfied with any of them. On an intuitive level, everyone knows they cannot make the best choice, but everyone thinks that they should be able to. I finally figured out why they cannot. I don’t mean that people are not smart enough. I mean that it is impossible. The behavior of complex systems makes it impossible.
The computer science of SCAMP drew me in, but what really interested me was its novel approach to modeling social phenomena. SCAMP looks at network-based phenomena in ways that traditional networking does not.
SCAMP is a network-based scenario-simulation methodology whose runs can reveal new understanding about known topics of research, and also, reveal hitherto unrealized research questions. SCAMP has this capacity because it treats networks in novel ways.