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User talk:Rspeer/Wikipolitical Compass

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Terminology

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You say you're not using the term "!vote", which is good, because it's a silly term. How about "opinion" instead? --bainer (talk) 13:50, 9 May 2007 (UTC)[reply]

Why change the word? RfA looks like a vote and quacks like a vote. Also, for the purposes of statistics, I have to assume that it is a vote. As an example, you won't see the opinions that Kelly Martin posts under "Neutral" votes show up here. rspeer / ɹəədsɹ 15:12, 9 May 2007 (UTC)[reply]

The "swoosh"

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The candidate distribution along axes 0 and 2: x axis = "agreeability" (0), y axis = "balance" (2), red = fail, green = success.

This is just pure conjecture, but to me, the candidate distribution seems to consist of two populations, both approximately gaussian: one (call it population A) containing mostly successful candidates and the other (B) mostly unsuccessful ones. For both populations, the axes are correlated, but the signs of the correlation are opposite. In fact, except for the higher variance of the non-successful population, the two seem like almost mirror images of each other along the x axis ("agreeability").

This makes perfect sense to me: the voter distribution shows that there are a lot of agreeable voters. If these voters tend to support candidates in population A and oppose those in population B, the two populations would naturally end up mirrored along the agreeability axis. The correlation between the axes within each population would seem to suggests that, for candidates with high "balance" (y axis), the "agreeability" (x axis) is a good predictor of voting results, while for specialized candidates other considerations muddle the voting pattern. The higher variance of the B population is also easy to explain, since, presumably, most of the oddball candidates will tend to belong there.

So my analysis of the graph, in condensed form, would be:

  1. There are candidates who will pass, and there are candidates who won't. The two groups are mostly distinct.
  2. Among the group likely to pass, being a specialized editor may draw oppose votes. For those who would otherwise not succeed, however, it may actually help.

Of course, none of this actually contradicts what you wrote in your own analysis; it's just a different way of looking at it.

One issue the graph does not answer is whether the lower agreeability difference between the two populations on the less balanced side actually translates into a lower score difference, or whether it merely means that agreeability is a worse predictor of score for them. In particular, it would be useful to see a version where the points for candidates were colored continuously according to the support/oppose ratio, not merely by pass/fail. On such a plot, it would be interesting to see whether the candidates in the area where the populations overlap had scores close to each other and to the current pass/fail limit, or whether candidates from the two populations still had distinct scores even when their agreeability was similar. —Ilmari Karonen (talk) 00:09, 10 May 2007 (UTC)[reply]

Axis 2?

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Ok, I just skimmed this, but I didn't see an explanation of how Axis 2 numbers were measured. Some detail there might be nice. JoshuaZ 00:38, 10 May 2007 (UTC)[reply]

Current situation

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It would be interesting to know if things have changed 8 years later! gidonb (talk) 22:38, 30 November 2015 (UTC)[reply]