Models and frameworks for assessing reality must reduce complexity in order to be useful. So there is a fine balance that must be struck between simplification and accuracy in order for the model or framework to not leave out so much detail that it becomes useless.

The question to ask yourself is: "what is being left out of the model?"

As an example: If we are modeling the social power of a group of individuals, and we are looking at their economic standing, educational backgrounds, and social interconnectedness, but we are leaving out their cultural background and historic access to resources, then our model is going to provide skewed results that give us a terrible depiction of some individuals within the group. This kind of modeling has often resulted in things like racism.

So being aware of what is excluded is often even more important than what is included.

#CoordinationAsPower