Science literacy, numeracy and science policy challenges

Dan Kahan, the Yale “cultural cognition” guy, has a new paper highlighting the problem with the argument that a more scientifically literate public will solve all our scientized problems, things like climate change, GMOs and nuclear stuff where the scientific argument has become intractably embedded in a political context.  (The paper’s actually targeted at climate change, but I think the argument extends to a much broader sphere.)

The paper’s in Nature Climate Change, and Dan’s done a nice summary on his blog:

We find that individuals who display high comprehension of science (i.e., those who score higher in science literacy and numeracy) are in fact more culturally polarized than those who display low science comprehension.

I’ve commented before on how these data relate to the popular surmise that seeming public ambivalence toward evidence on climate change reflects the predominance of what Kahneman (in his outstanding book Thinking: Fast & Slow, among other places) calls “system 1” reasoning (emotional, unconscious, error-prone) on the part of members of the public.

Our findings don’t fit that popular hypothesis. On the contrary, they show that individuals disposed to use system 2—conscious, reflective, deductive—reasoning (a disposition measured by the numeracy scale) are even more culturally divided than those disposed to use system 1.

This stuff is very much on my mind after participating in one of the most useful conference panel discussions I’ve ever done last week at the Tahoe Science Conference.

Tamara Wall from the Desert Research Institute invited me, and based on the initial discussions I assumed I would be playing my usual “science communicator” role. This is where scientists who’ve seen me successfully write about their work (or so they think) invite me in to explain how they can better get their point across to a sometimes recalcitrant public. I used to enthusiastically jump at these opportunities to explain how it’s done. These days I’ve adopted the glum “science communication is harder than you think”, “the deficit model doesn’t really work, and even if it did, I’m not gonna be able to fix the deficit”, etc.

But Wall was one step ahead of me. In addition to the climate scientist on the panel (David Pierce from Scripps, who ably explained how scientists approach the problem of attributing climate change to natural and anthropogenic causes), she invited two social scientists. Patricia Mynster at UNLV is doing field work on understanding and attitudes toward climate change among residents of rural northern Nevada. Kim Klockow at the University of Oklahoma is applying Kahan’s “cultural cognition” framework to people’s perceptions of weather and climate.

So when we were eating dinner the night before scheming about the panel, and Klockow brought up Kahan’s work, I’m thinking to myself, “Wait. You mean I’m not going to have to explain the science behind why my work is received in such varied ways?”

To say that I was happy is an understatement. I usually feel kinda lonely at these things.

One Comment

  1. John,
    Thanks for all this information. I would say that science communication is not ‘harder than you think’ but ‘way harder than you think.’
    I have given reviews of Kahneman, Ariely, and other authors on my blog, Getting There From Here.
    One of my goals is to understand why comprehension of science and technology is so hard for many people. I apply this understanding to talking to and interacting with non scientists and to the difficulties of water regulation, as you and David Zetland know.

    A second goal is to incorporate an understanding of this difficulty into our growing molecular model of brain function. So far the model is semipredictive in that it predicts the increasing difficulty for classes of people but not for individuals, since we all have different life histories.

    The finding by Kahan that more educated people are more polarized on scientific debate is fascinating. I have a guess as to why this might be true, but will have to wander off, watch some birds, and see whether my guess might be right. Our molecular model of brain function had not gotten to Kahan’s findings yet. I guess the model will have to become more nuanced and bigger.

    I wonder if the degree of polarization depends on whether the two educated camps are talking face to face or through written materials and whether it matters whether non-scientists are in the room when the two camps are talking face to face.

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