Power Law Distributions: Part 2 of 6 Posts on Evaluation, Complex Behavior, and Themes in Complexity Science

Common Introduction to all 6 Posts

History and Context
These blog posts are an extension of my efforts to convince evaluators to shift their focus from complex systems to specific behaviors of complex systems. We need to make this switch because there is no practical way to apply the notion of a “complex system” to decisions about program models, metrics, or methodology. But we can make practical decisions about models, metrics, and methodology if we attend to the things that complex systems do. My current favorite list of complex system behavior that evaluators should attend to is:

Complexity behavior Posting date
·      Emergence up
·      Power law distributions up
·      Network effects and fractals Sept. 28
·      Unpredictable outcome chains Oct. 5
·      Consequence of small changes Oct. 12
·      Joint optimization of uncorrelated outcomes Oct. 19

For a history of my activity on this subject see: PowerPoint presentations: 1, 2, and 3; fifteen minute AEA “Coffee Break” videos 4, 5, and 6; long comprehensive video: 7.

Since I began thinking of complexity and evaluation in this way I have been uncomfortable with the idea of just having a list of seemingly unconnected items. I have also been unhappy because presentations and lectures are not good vehicles for developing lines of reasoning. I wrote these posts to address these dissatisfactions.

From my reading in complexity I have identified four themes that seem relevant for evaluation.

  • Pattern
  • Predictability
  • How change happens
  • Adaptive and evolutionary behavior

Continue reading “Power Law Distributions: Part 2 of 6 Posts on Evaluation, Complex Behavior, and Themes in Complexity Science”

Emergence: Part 1 of 6 Posts on Evaluation, Complex Behavior, and Themes in Complexity Science

Common Introduction to all 6 Posts

History and Context
These blog posts are an extension of my efforts to convince evaluators to shift their focus from complex systems to specific behaviors of complex systems. We need to make this switch because there is no practical way to apply the notion of a “complex system” to decisions about program models, metrics, or methodology. But we can make practical decisions about models, metrics, and methodology if we attend to the things that complex systems do. My current favorite list of complex system behavior that evaluators should attend to is:

Complexity behavior Posting date
·      Emergence up
·      Power law distributions Sept. 21
·      Network effects and fractals Sept. 28
·      Unpredictable outcome chains Oct. 5
·      Consequence of small changes Oct. 12
·      Joint optimization of uncorrelated outcomes Oct. 19

For a history of my activity on this subject see: PowerPoint presentations: 1, 2, and 3; fifteen minute AEA “Coffee Break” videos 4, 5, and 6; long comprehensive video: 7.

Since I began thinking of complexity and evaluation in this way I have been uncomfortable with the idea of just having a list of seemingly unconnected items. I have also been unhappy because presentations and lectures are not good vehicles for developing lines of reasoning. I wrote these posts to address these dissatisfactions. From my reading in complexity I have identified four themes that seem relevant for evaluation.

  • Pattern
  • Predictability
  • How change happens
  • Adaptive and evolutionary behavior

Continue reading “Emergence: Part 1 of 6 Posts on Evaluation, Complex Behavior, and Themes in Complexity Science”

Applying Complexity to Make Practical Decisions About Evaluation

Lately I have been speaking to as many audiences as I can about the need to focus on complex behavior rather than on complex systems. The reason is that there is no practical way to apply the notion of a “complex system” to practical decisions about program models, metrics, or methodology. But it is possible to make those decisions with respect to the things that complex systems do. I just completed a series of three short “coffee break” sessions on this topic for the American Evaluation Association.

Go here for the slides.

www.jamorell.com/documents/AEA_Coffee_Break_Part_1.pdf

www.jamorell.com/documents/AEA_Coffee_Break_Part_2.pdf

www.jamorell.com/documents/AEA_Coffee_Break_Part_3.pdf

If you are a member of AEA you can also hear the audio presentation. Go here for the audio tapes.

https://vimeo.com/269709240/e1b05b4857

https://vimeo.com/267297243/523c1a8c44

https://vimeo.com/265410410/8edd0dd3b7

Case Study Example: Drawing on Complexity to do Hands-on Evaluation

In 2016 I developed a case for a workshop I did at the Canadian Evaluation Society on the use of complexity in evaluation. I was doing some archeology and unearthed it. It offers pretty rich opportunity to think about complex behavior in evaluation, so I decided to share it.

Construction of the Case
This is the example we will use throughout this workshop to illustrate how knowledge of system behavior can be applied in evaluation. The example is hypothetical. I made it up to resemble a plausible evaluation scenario that we may face, but which is elaborated to make sure it contains all the elements needed to explain the topics in the workshop. I am sure that none of us (me included) have ever been involved in an evaluation that is as far reaching and in-depth as the example here. But I am sure that all of us have been involved in evaluations that are similar to parts of the example, and, if you are like me, I bet you have dreamed of being involved in an evaluation of the size and scope of the example.

There are three initiatives. One aimed at adults. One aimed at mothers and young children. One aimed at teens. Each initiative has several individual programs that share some common outcomes, and which also have some unique outcomes. Continue reading “Case Study Example: Drawing on Complexity to do Hands-on Evaluation”

Depicting Complexity in 2-D

There is an interesting discussion going on in the Linked-In discussion group of the European Evaluation Society with respect to a question someone asked: How do linear models address the complexity in which we work? I can’t help but to weigh in. I also placed a link to this blog post on the EES discussion thread. My thoughts on this topic run in two directions.

1) Putting a lot of stuff in a model, and
2) What does it mean to “address complexity”?

Putting a Lot of Stuff in a Model

I am a big fan of information density. The more information that can be juxtaposed, the greater the amount of meaning that can be conveyed. The countervailing force to this inclination is that I’m also a big fan of information being readable. My solution is to think of rendering a model as an exercise in the joint optimization of two goals: Continue reading “Depicting Complexity in 2-D”

Drawing on Complexity to do Hands-on Evaluation (Part 3) – Turning the Wrench

Common Introduction to all Three Posts
What is the Contribution of Complexity to Evaluation?
Drawing from Research and Theory in Complexity Studies

Common Introduction to all Three Posts

This is the third of three blog posts I have been writing to help me understand how “complexity” can be used in evaluation. If it helps other people, great. If not, at least it helped me.

Part 1:  Complexity in Evaluation and in Studies on Complexity
In this section I talked about using complexity ideas as practical guides and inspiration for conducting an evaluation, and how those ideas hold up when looked at in terms of what is known from the study of complexity. It is by no means necessary that there be a perfect fit. It’s not even a good idea to try to make it a perfect fit. But the extent of the fit can’t be ignored, either.

Part 2: Complexity in Program Design
The problems that programs try to solve may be complex. The programs themselves may behave in complex ways when they are deployed. But the people who design programs act as if neither their programs, nor the desired outcomes, involve complex behavior. (I know this is an exaggeration, but not all that much. Details to follow.) It’s not that people don’t know better. They do. But there are very powerful and legitimate reasons to assume away complex behavior. So, if such powerful reasons exist, why would an evaluator want to deal with complexity? What’s the value added in the information the evaluator would produce? How might an evaluation recognize complexity and

Part 3: Turning the Wrench: Applying Complexity in Evaluation
This is where the “turning the wrench” phrase comes from in the title of this blog post1. Considering what I said in the first two blog posts, how can I make good use of complexity in evaluation? In this regard my approach to complexity is no different than my approach to ANOVA or to doing a content analysis of interview data. I want to put my hands on a tool and make something happen. ANOVA, content analysis and complexity are different kinds of wrenches. The question is which one to use when, and how.

Complex Behavior or Complex System?
I’m not sure what the difference is between a “complex system” and “complex behavior”, but I am sure that unless I try to differentiate the two in my own mind, I’m going to get very confused. From what I have read in the evaluation literature, discussions tend to focus on “complex systems”, complete with topics such as parts, boundaries, part/whole relationships, and so on. My reading in the complexity literature, however, makes scarce use of these concepts. I find myself getting into trouble when talking about complexity with evaluators because their focus is on the “systems” stuff, and mine is on the “complexity” stuff. In these three blog posts I am going to concentrate on “complex behavior” as it appears in the research literature on complexity, not on the nature of “complex systems”. I don’t want to belabor this point because the boundaries are fuzzy, and there is overlap. But I will try to draw that distinction as clearly as I can. Continue reading “Drawing on Complexity to do Hands-on Evaluation (Part 3) – Turning the Wrench”

Drawing on Complexity to do Hands-on Evaluation (Part 2) – Complexity in Program Operation, Simplicity in Program Design

Common Introduction to all Three Posts
Why do Policy and Program Planners Assume Away Complexity?
How Can Evaluators Apply Complexity in a way that will Help Program Designers?

Common Introduction to all Three Posts
This is the second of three blog posts I have been writing to help me understand how given the reality of how programs are designed, “complexity” can be used in evaluation . If it helps other people, great. If not, at least it helped me.

Part 1:  Complexity in Evaluation and in Studies on Complexity
In this section I talked about using complexity ideas as practical guides and inspiration for conducting an evaluation, and how those ideas hold up when looked at in terms of what is known from the study of complexity. It is by no means necessary that there be a perfect fit. It’s not even a good idea to try to make it a perfect fit. But the extent of the fit can’t be ignored, either.

Part 2: Complexity in Program Design
The problems that programs try to solve may be complex. The programs themselves may behave in complex ways when they are deployed. But the people who design programs act as if neither their programs, nor the desired outcomes, involve complex behavior. (I know this is an exaggeration, but not all that much. Details to follow.) It’s not that people don’t know better. They do. But there are very powerful and legitimate reasons to assume away complex behavior. So, if such powerful reasons exist, why would an evaluator want to deal with complexity? What’s the value added in the information the evaluator would produce? How might an evaluation recognize complexity and still be useful to program designers?

Part 3: Turning the Wrench: Applying Complexity in Evaluation
This is where the “turning the wrench” phrase comes from in the title of this blog post1. Considering what I said in the first two blog posts, how can I make good use of complexity in evaluation? In this regard my approach to complexity is no different than my approach to ANOVA or to doing a content analysis of interview data. I want to put my hands on a tool and make something happen. ANOVA, content analysis and complexity are different kinds of wrenches. The question is which one to use when, and how.

Complex Behavior or Complex System?
I’m not sure what the difference is between a “complex system” and “complex behavior”, but I am sure that unless I try to differentiate the two in my own mind, I’m going to get very confused. From what I have read in the evaluation literature, discussions tend to focus on “complex systems”, complete with topics such as parts, boundaries, part/whole relationships, and so on. My reading in the complexity literature, however, makes scarce use of these concepts. I find myself getting into trouble when talking about complexity with evaluators because their focus is on the “systems” stuff, and mine is on the “complexity” stuff. In these three blog posts I am going to concentrate on “complex behavior” as it appears in the research literature on complexity, not on the nature of “complex systems”. I don’t want to belabor this point because the boundaries are fuzzy, and there is overlap. But I will try to draw that distinction as clearly as I can. Continue reading “Drawing on Complexity to do Hands-on Evaluation (Part 2) – Complexity in Program Operation, Simplicity in Program Design”