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What I am questioning is the concept in the article as stated specifically in the article's title about compassion and linking that directly to a monetary sum.

Well it can't be denied that when a group declares its self committed to a virtue or principle and in fact the ones it accuses of acting contrary to it turns out to perform more... it is an interesting story.

It would be like if it were found out via research that committed Catholics where actually getting more abortions than say.... non-religious people.

That would be interesting.

Your acting as if "this" study is not is quite transparent.

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More propoganda. Can't believe people fall into this trap to get people going into religion. If the conservatives contribute alot of to charity, tell me why they hate subsidized housing? Tell me why they don't like helping the poor in rural communities? Tell me! Ridiculous perspective the article have produced.

Its unsurprising use of statistics to fit certain ridiculous logic. Here's another take on the matter given the way numbers can be manipulated to fit seemingly contradictory philosophical origins to charity and helping those in need:

<h3 class="title">Charitable Giving: Liberals vs. Conservatives</h3>

An interesting article on charitable giving via Greg Mankiw.

The conventional wisdom runs like this: Liberals are charitable because they advocate government redistribution of money in the name of social justice; conservatives are uncharitable because they oppose these policies. But note the sleight of hand: Government spending, according to this logic, is a form of charity.

I suppose many on the Left might object that this is somewhat of strawman in that they don't necessarily claim that conservatives are not charitable or that "giving via government redistribution" is a form of charity, but still the notion that conservatives are greedy SOBs who don't care about the poor and less fortunate is a standard type of rhetoric used by the Left.

Let us be clear: Government spending is not charity. It is not a voluntary sacrifice by individuals. No matter how beneficial or humane it might be, no matter how necessary it is for providing public services, it is still the obligatory redistribution of tax revenues. Because government spending is not charity, sanctimonious yard signs do not prove that the bearers are charitable or that their opponents are selfish.

This is exactly right and I'd also point out that it isn't really charity when it is somebody else's money. Prof. Brooks goes on to point out that the data in terms of private charitable giving indicate that people who he defines as conservatives give far more than those he defines as liberal. At this point one might wonder, how does he define liberal vs. conservative? Well, here is how he does it,

First, we must define "liberals" and "conservatives." Most surveys ask people not just about their political party affiliation but also about their ideology. In general, about 10 percent of the population classify themselves as "very conservative"; and another 10 percent call themselves "very liberal." About 20 percent say they are simply "liberal," and 30 percent or so say they are "conservative." The remaining 30 percent call themselves "moderates" or "centrists." In this discussion, by "liberals" I mean the approximately 30 percent in the two most liberal categories, and by conservatives I mean the 40 percent or so in the two most con­servative categories.

I would be curious to see what the data says for the "moderates". Still, it looks like the conservatives really do care about other people, even the less fortunate.

Update: Commenter Cernig points to this post by James Lindgren that takes a closer look at the analysis by Brooks and the results are far less stron than Brooks is claiming.

I am skeptical of basing so much on the SCCBS, in large part because it reports that liberal families make more money than conservatives (it is not clear from Brooks's book whether the survey is of a representative national sample). In the 2000, 2002, and 2004 General Social Surveys, which are representative samples of the US, conservative families make $2,500 to $5,600 a year more than liberal families in each one. Although I don't have the ANES data handy, my recollection is that the economic differences between conservatives and liberals are usually in the same direction and even larger in the ANES than in the GSS. Further, in each of these 3 GSSs, the lowest income families were the political moderates, who usually made substantially less than either liberals or conservatives.

Which does raise a good question about the quality of the data that Brooks used.

I found this part amusing though,

This raises another problem with Brooks' analysis: the contrast in Who Really Cares is frequently made between liberals (about 30% of the population) and conservatives (about 40% of the population), but I find that often the group that contrasts most strongly with conservatives is not liberals (who share with conservatives higher than average educations), but political moderates (about 30% of the population).

This problem comes to a head in Brooks's probit and regression models analyzing SCCBS data (pp. 192-193). After controlling for a lot of things that you might not want to control for (i.e., being religious or secular), Brooks concludes that "liberals and conservatives are not distinguishable" in whether they have made any donation in the last year. This is literally true, but he fails to note that in the model liberals give significantly more than moderates, if a traditional .05 significance level is used, while conservatives do not differ significantly from moderates. Yet in Table 6, the significance level used as a threshold for identification with an asterisk is .01, not .05, as he uses in some of the other tables. In one table (p. 197), Brooks even reports significance at the .10 level, as well as at the .05 and .01 levels.

This highlights, for me at least, the absurdity of using Frequentist statistics. "Well, it certainly does become statistically significant once we change the level of significance!" Big deal, so it is significant at the 5% level, but not the 1% level. I prefer Bayes Factors which gives us a "weight of evidence" and we don't have to worry about some arbitrarily chosen level of significance.

The rest is Dannologic at work. Why anyone would be surprised with that kind of 'analysis' really shouldn't be something new.

bump before I leave.

Wishing you ten-fold that which you wish upon all others.

 

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