### Table of Contents

Complexity is About Stability and Predictability

Example 1: Attractors

Example 2: Strange Attractors

Example 3: Fractals

Example 4: Phase Transitions

Example 5: Logistic Maps

Example 6: Power Laws

Example 7: Cross Linkages

Example 8: Emergence

What Does All This Mean for Evaluators?

Example 1: Attractors

Example 2: Strange Attractors

Example 3: Power Laws

Example 4: Timeframes, Attractors, and Power Laws

Example 5: Emergence

Example 6: Fractals

Example 7: Phase Shifts

### Complexity is About Stability and Predictability

I have been thinking about how complexity is discussed in evaluation circles. A common theme seems to be that because programs are complex we can’t generalize evaluation findings over space and time because of the inherent uncertainties that reside in complex systems. (Sensitive dependence on initial conditions, evolving environments, etc.) The more I think about the emphasis on instability and unpredictability, the less I like it. See figure 1. Ban the butterfly! Continue reading