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« Aggregates and Votes in Quantitative Ideology Models | Main | Sotomayor and "Measurement Error" »
Monday
Aug102009

Sotomayor's Predicted Liberalism Using Newspaper Scores

(sent to Law-courts)


Jeff Segal wrote in response to Paul's Finkelman's mail, "The predictive value is this: for the justices appointed since Warren, the editorial scores correlate at about .8 with the percentage of times the justices vote liberally."
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First, for any given justice, flipping coins will predict that their score will be 50. So the question becomes how well these media-impression workshops that Jeff recreates improves upon this efficacy. This is called Proportional Reduction in Error (PRE). The PRE on the logit models do show improvement upon blind guessing at 50, but several things must be noted:

1. No one guesses in the blind. Whether these scores are worth their labor is a function of what other perception workshops would tell us. I bet that polling empirical scholars would be better than constructing something from editorials. No one who watches the scores would expect anything more than a 60-ish number anyway, especially when you consider what that number really is.

2. The scores only improve blind guessing (at 50) by about 24%. But if you take away the extremely- directional justices -- the ones no longer on the Court -- the number is 9%. (Subtracted: Rehnquist, Brennan, Marshall, Fortas, Douglas and Goldberg).

3. If you consider the whole docket, of course, all bets are off. You have a statistically-insignificant model from 1948-2004. (about 60,000 so-called "votes"). Model is logit. The PRE is terrible anyway.

4. A couple additional things:

People need to ask themselves to what extent the model really indulges metaphysics. Think about it. As a scientist, you know that the media-perception scores are only a form of prognostication. That's what Jeff has done. He's turned their content into a prediction for either a justice's state of mind or his or her work consequences for criminal-plus claimants.

But if journalists really knew this, the story would be one of clairvoyance or perhaps conspiracy (like insider trading). There is nothing in those editorials different from what, say, informed list members might believe about these things. If Jimmy the Greek predicted numbers well for six weeks in a row, would you go off and say that science was the cause, or that metaphysics (or corruption) was? I think luck would be the real cause. My point is there is nothing special about journalists feelings in this respect. Many of us could do better than a coin flip. There is no need to make either metaphysics or science out of this.

One last point. If Jeff's measures have any significance to anything, it probably is similar to the correlation that young children have in picking presidential elections. That's what it reminds me of. But there, what we say is that this is "carrier evidence." That it shows image perception at some base level of psychology. Here the mistake is not to ask the same question: why is it that a small media-perception work group constructed during the confirmation ritual has any relationship whatsoever to a yes-no tally of claimants winning in criminal-plus cases? The answer really only lies in this:

1. The 6 to 8 extreme justices that drive the results
2. It's an easy game. Pick from 35 to 45 for republicans; 55 to 65 for Democrats - and you'll do fine.

And, if you can find some sort of naturally-occurring process that generates numbers like this -- like media perceptions of a president's pick -- now you have something really neat. It makes the whole thing look automated.

Regards and thanks.

(P.S. -- Paul, see my paper if you want a technical overview of Jeff's model. It is on SSRN, below my signature)

Dr. Sean Wilson, Esq.
Assistant Professor
Wright State University
Redesigned Website: http://seanwilson.org
SSRN papers: http://ssrn.com/author=596860
Twitter: http://twitter.com/seanwilsonorg
Facebook: http://www.facebook.com/seanwilsonorg
New Discussion Group: http://seanwilson.org/wittgenstein.discussion.html

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