This is the abstract for a book chapter I am writing on the evaluation of transformation. It is a draft and will undoubtedly change quite a bit by the time it is published.
This chapter draws from complexity science to present a metatheory of transformation that can be applied to discrete theories of change that are constructed to guide model building, methodology, and data interpretation for the evaluation of individual change efforts. The focus is on six specific behaviors of complex systems – stigmergy, attractors, emergence, phase transition, self-organization, and path dependence. These can be invoked singly or in combination to understand pattern, predictability, and how change happens. The importance of both “explanation” and “prediction” is woven into the discussion. A definition of “transformation” is offered in which a qualitatively new reality becomes the default choice that constitute a new normal. Indicators of transformation include measurable ranges (as opposed to specific values) for level of energy use and the time over which the change endures. Because complex systems behave as they do, the recommended theory of change is sparse – it has few well-defined elements or relationships among those elements. There is already good progress in the application of complexity to the evaluation of transformation. An argument is made that these efforts should be strengthened by deliberately incorporating what is known about complex system behavior, and that by so doing, both prediction and explanation would better serve the purpose of practical decision making.
Here is the entire chapter.
In a previous blog post and in one of my You Tube videos I tried to make the case that different disciplines orient problem definition and solution in different ways, and that evolutionary biology and ecology lead researchers in different directions than do the social sciences. I followed this line of reasoning with the argument that evaluators’ traditional grounding in social science normally has been productive and that for the most part, we should continue to do what we have always done. Then, I tried to make the point that there are circumstances where thinking in terms of evolutionary biology and ecology can be a powerful addition to how we normally do our work. In this blog post I will show how policy evaluation is one of those circumstances when evolutionary / ecological thinking can be valuable. Continue reading “Using the Biotic Hierarchy as a Framework for Moving Policy Evaluation Away from a Program Evaluation-like Activity”
What you see here is a brief overview of my recent thoughts about the field of evaluation and the future of AEA. See the PDF for a more fleshed out explanation. Fair warning, it runs to 2,500 words. I am not advocating change, I’m only advocating that we recognize where we are and where we are going, and that we contemplate the consequences. AEA_Evaluation_Evolutionary_Path_Long
The challenge of contending points of view in a representative democracy goes back to the founding of the Republic. James Madison saw the polity as a collection of “factions” and believed that a stable democracy required a diversity of contending factions.
One way to think about the purpose of evaluation is to see it as an honest broker to which those factions can turn. This is not to say that any given evaluation can be, or should be, “objective”. Supporters of one or another point of view will inevitably find the results of any single evaluation wanting.
The question is whether over time, and across evaluations, it matters whether we are seen as taking sides. That perception has consequences for evaluation use, and I can see how outsiders would get the impression that we do take sides. If they do, they will shop elsewhere for evaluation information.
I’m not sure if we can or should change. But I do not think we should continue on our path without awareness of where that path is taking us.
I put together a slide deck on the advantages of adding constructs from evolutionary biology and ecology to traditional evaluation. Adding those constructs is worth the trouble when the focus is on:
- populations of a program types, and
- rates of change over time
Specific topics covered are:
- Policy as ecosystem change
- Evolution of program forms
- Sustainability in terms of ecosystems as attractors
- Use of ecosystem analysis to interpret outcome evaluation
- Using population trends to interpret data on program outcome
Go here for the slides. UD_EBT_Evaluation_Meeting