Workshop – Complex Behavior in Models, Methodology, and Metrics

Complexity in Evaluation: My Latest Thinking on What Matters

Complex behavior can be evaluated using comfortable, familiar methodologies – Part 4 of a 10-part series on how complexity can produce better insight on what programs do, and why

Ignoring complexity can make sense – Part 3 of a 10-part series on how complexity can produce better insight on what programs do, and why 

Evaluating for complexity when programs are not designed that way Part 10 of a 10-part series on how complexity can produce better insight on what programs do, and why

A few very successful programs, or many, connected, somewhat successful programs? Part 9 of a 10-part series on how complexity can produce better insight on what programs do, and why

How can the concept of “attractors” be useful in evaluation? Part 8 of a 10-part series on how complexity can produce better insight on what programs do, and why

Why should evaluators care about emergence? Part 7 of a 10-part series on how complexity can produce better insight on what programs do, and why

Joint optimization of unrelated outcomes – Part 6 of a 10-part series on how complexity can produce better insight on what programs do, and why

A pitch for sparse models – Part 5 of a 10-part series on how complexity can produce better insight on what programs do, and why

Complex systems or complex behavior? Part 1 of a 10-part series on how complexity can produce better insight on what programs do, and why

Complexity has awkward implications for program designers and evaluators – Part 2 of a 10-part series on how complexity can produce better insight on what programs do, and why