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by jvanderbot 883 days ago
The title explains literally the whole concept:

Representing the "opinions" (or more appropriately dispositions) of each person as a vector, the belief system of a "tribe" (connected set of individuals) is probably the mean of these vectors.

And relgions seek to optimize the "morality" they preach (vector they propose as "god") to maximize membership / agreement / centralness of their god. Which of course (author does not point this out) is the mean of the population.

They could have expanded a little:

* By what metric do we define "closeness"? A higher norm would penalize dissent / divergence from "god" more. * In the limit, how does dissent penalties affect the "coverage" of available religions? This is basically k-means with different defintions of "mean" * You could model the problem as unsupervised clustering where k is unknown to predict how many religion clusters form, for a given population - if opinions could be measured.

on and on. Title was the most interesting part, the rest was just coffee kicking in.

2 comments

I thought the analogy to linear algebra added very little. It seems more they’ve just littered words about vectors around the word average. They just want the word average.

I think there might be some interesting analogies to vectors out there, so it annoys me that they’ve basically made a head-fake toward them and then just used the word average.

I think you are going in a better direction. I’d call a person’s opinions a point in a many-dimensional space, a space of issues. Then, to come up with a discourse we project those opinions into a some space of ideals. I think what things like the 1D left/right spectrum and the 2D political compass miss is that there isn’t some objectively correct way of picking the unit vectors for the space you are projecting onto. Probably we’d want to do the PCA, but that’s based on the population.

I’d also place the discussion in terms of political opinions rather than some analogy to a god or some gods, since they bring in a lot of feelings.