What accounts for public conflict over science-religiosity or political predispositions? Here are some data: you declare the winner in this RAT vs. CAT fight! - Cultural Cognition of Health

Outsourcing my critical reading (i.e., just plain reading!) of this article worked really well.  Given the great points that came out in the comments , I don’t think there’s any value added in my offering a full assessment of the paper, which reported the results of a study that analyzed less than ideal data with a questionably specified statistical model from which the authors seemed to draw very debatable inferences.

But I do think it might be interesting to explore, at least to a degree, what one might learn about the authors’ research questions if one applied a valid statistical model to data that could support some reasonable inferences.

Basically, the authors purport to find that “religious variables,” but not “partisan identification,” predict a general hostility to science as manifested by attitudes toward climate change, evolution, and stem-cell research.  They treat this finding as suggesting reason to doubt claims that partisan political predispositions (e.g., Gauchat 2012), shaped by elite discourse (e.g., Mooney 2005; Brulle et al. 2012), account for public conflict over science issues.

Because the authors believe that  religiosity bears a greater share of the responsibility for such conflicts than is normally appreciated, let’s call this the “Religion-science Antipathy thesis” (RAT).

The main “political” competitor the authors advert to is one that attributes such conflict to antipathy—perhaps psychologically grounded (Mooney 2012), perhaps economically (Brulle et al., 2012), or maybe both—between a conservative political orientation and science. Let’s call this the Conservativism-science Antipathy Thesis” (CAT).

So here’s what I’m going to do.  I’ve compiled a bunch of observational (i.e., survey!) data and modeled them in a way that I think arguably bears on the relative plausibility of RAT and CAT.

But exercising a credulity-defying degree self-restraint, I am going to refrain, for at least 24 hrs , from telling you what sorts of conclusions I think these data support.

In that period, you , the 14 billion readers of this blog, will be afforded the exclusive opportunity to specify and defend your own inferences !

How many of the myriad other “cultural cognition blogs” out there do you think would have the necessary levels of self-confidence and respect for their readers to surrender their “first word” prerogative?  That’s right— not a one!

Let’s start with global warming.

As you can see, this figure plots the probability of agreeing that there is “solid evidence” for human-caused global warming in relation to right-left political outlooks conditional on one’s level of “religiosity.”  Political outlooks and religiosity are measured with separate multi-item scales. (Because partisan self-identification and liberal-conservative ideology are both indicators of the same thing—an unobserved or latent political disposition—it is really not a good idea to treat them as “independent” right-hand side variables in a multivariate regression.)  The colored hashmarks are the 0.95 confidence intervals for the predicted probability at the indicated point on the left-right political outlook scale.

If you want to “see” the regression model or the “raw data,” then click on the specified thumbnails in the margin.

As you can tell, there’s an interaction between religiosity and political outlooks: the contribution that moving left in outlook makes to acceptance of climate change is bigger the less religious one is.

If you get only this, demand a refund! But I won’t say anything more than that!  What this signifies in the battle between RAT and CAT is your call to make!

Next, let’s look at belief in evolution.  Same model, used now to examine the impact of political outlooks on belief in evolution conditional on religiosity.

Next, support for stem-cell research.

Actually, I’ve never collected data on this topic.  So I popped open a canned dataset that has such data: the super great 2009 Pew public attitudes toward science survey.

I again constructed a political outlook scale by aggregating response to partisan self-identification and liberal-conservative ideology items.

Pew didn’t have all the same items from which I constructed the religiosity scale in the previous models.  So I constructed one using self-reported church attendance (one of the items that I did have in my CCP data set), self-identified “born again” evangelical status, and a “non-religious” self-identification variable that separated out persons who self-identified as agnostics or atheists from those who reported affiliation with any religious denomination.

How good a measure is this?  I wasn’t sure, so I came up with a method to externally validate it.