How good a model is cannot be determined without specifying purpose of this model. In particular, there is no universally-correct granularity—some models track a lot of little details and effects, while others do not and aggregate all of them into a few measures or indicators. Both types can be useful depending on the purpose. In particular, a more granular model is not necessarily a better model.
This general principle applies here as well. Sometimes you do want to model a group of humans as a group of distinct humans, and sometimes you want to model a group of humans as a single entity.
Well, let’s step back a little bit.
How good a model is cannot be determined without specifying purpose of this model. In particular, there is no universally-correct granularity—some models track a lot of little details and effects, while others do not and aggregate all of them into a few measures or indicators. Both types can be useful depending on the purpose. In particular, a more granular model is not necessarily a better model.
This general principle applies here as well. Sometimes you do want to model a group of humans as a group of distinct humans, and sometimes you want to model a group of humans as a single entity.