"The underrepresentation of the needy is especially pronounced when it comes to financial contributions to politics. Figure 16.4, which presents data about the effects of the participatory process on the representation of people with actual economic need, clarifies how this result comes about...The amount of money given to politics, we noted, was tightly constrained by the need to have the relevant resource--money."In case you were pondering the inscrutable question of why poor people donate less, now science has your answer.
--Voice and Equality: Civic Voluntarism in American Politics
Sunday, September 06, 2009
Oh, so this is why we have quantitative political science
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4 comments:
"Figure 16.4, which presents data about the effects of the participatory process on the representation of people with actual economic need"
That's a mouthful, but don't all people have "actual economic need?" Probably just trying to fill page after page with gobbledygook until the magic number, 30, is reached.
PS. I was going to use a four letter word, but went with gobbledygook instead. You should be proud.
In fact, the magic number for this book, including no fewer than six appendices, is 625. They do specify though that by "actual economic need" they mean people on welfare. It's not actually a terrible book, but only about 30 pages of it make something other than statements of the obvious.
I am proud. I would also suggest "tripe" as a good substitute.
"Participation in combat was positively correlated with fears about injury or death." - RAND monograph
I would contend that the reason there is quantitative political science is that that sort of gobbledygook is no longer sufficient to hide the lack of ideas in such a book - it takes a big table and some nonsense about confidence intervals and the t-test to do that. In most cases the people talking about confidence intervals or the t-test don't understand what they are saying any more than the people being intimidated by it, but that wasn't the point.
I will grudgingly admit that there are probably cases where the quantitative work does provide real insights, and the people doing that work do know what they are talking about, but I bet that they can state their conclusions clearly and without reference to statistical jargon...
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