The article touches on it, but the clear differentiator I see here is whether the "crowd" has expert knowledge of the domain.
If it does, then the noise of experts clashing (resolving conflicts between equally informed ideas) starts outweighing the benefits of them contributing the ideas to begin with. Basically you get a too many chiefs issue.
If it doesn't, you're seeking to average variably-educated wild ass guesses and taking advantage of the fact that WAGs have a tendency to form a bell curve around the actual answer if there's any ability to estimate whatsoever. Since there's otherwise no special knowledge, that ends up being the best you can get but requires a lot of people to get right.
Without having read up on it, my guess is the latter is related to central limit, with each person's WAG forming the first term of the mean of means; a WAG is itself sampling your own mental model and boiling it to a number. Given enough of those you get a normal that you can average.
If it does, then the noise of experts clashing (resolving conflicts between equally informed ideas) starts outweighing the benefits of them contributing the ideas to begin with. Basically you get a too many chiefs issue.
If it doesn't, you're seeking to average variably-educated wild ass guesses and taking advantage of the fact that WAGs have a tendency to form a bell curve around the actual answer if there's any ability to estimate whatsoever. Since there's otherwise no special knowledge, that ends up being the best you can get but requires a lot of people to get right.
Without having read up on it, my guess is the latter is related to central limit, with each person's WAG forming the first term of the mean of means; a WAG is itself sampling your own mental model and boiling it to a number. Given enough of those you get a normal that you can average.