Note: I have joined the “virtual class” component of Dan Kahan‘s Science of Science Communication course at Yale University. As part of this I am endeavoring to write a response paper in reaction to each week’s set of readings. I will post these responses here on my blog – my paper for week six is below. Previous responses are here.
I will also be participating in the discussion on Kahan’s own blog.
Since the publication of John Cook’s 2013 study confirming climate scientists’ 97 percent consensus on humans’ responsibility for climate change, many science communicators have vigorously argued the importance of “teaching the consensus.” On a common-sense level, teaching the consensus seems like an obviously good idea. If you tell someone that 97 percent of experts on a subject agree, how could he carry on maintaining the minority position?
But science communication isn’t that simple. It’s much more frustrating, and fascinating.
Evidence for “teaching the consensus”
Let’s have a brief look at some of the evidence for teaching the consensus – which is backed not just by common sense but by several studies. Stephan Lewandowsky, in particular, has been a strong proponent of this approach. In “The pivotal role of perceived scientific consensus in acceptance of science,” he and his colleagues found that subjects told about the 97 percent scientific consensus expressed a higher certainty that CO2 emissions cause climate change – 4.35 on a 5-point Likert scale, versus 3.96 for members of a control group not exposed to the consensus message.
In addition, the consensus message appeared to have effectively erased ideology’s influence on global warming opinions. Those exposed to the message had a high level of agreement that CO2 causes climate change, regardless of their free-market ideology; whereas in the control condition, free-market endorsement was associated with a marked decrease in acceptance of human-caused climate change (see chart above).
Meanwhile, back in the real world…
But Dan Kahan points out that these findings don’t seem borne out by real-world evidence. From 2003 to 2013, the proportion of the US public who said human activities were the main cause of global warming declined from 61 to 57 percent.
During this period researchers published at least six studies quantifying the consensus, and there were also several notable efforts to publicize the consensus, including:
- prominent inclusion in Al Gore’s documentary film and book “The Inconvenient Truth”;
- prominent inclusion in the $300 million social marketing campaign by Gore’s Alliance for Climate Protections;
- over 6,000 references to “scientific consensus” and “global warming” or “climate change” in major news sources from 2005 to May 1, 2013.
What accounts for this discrepancy? According to Kahan, “The most straightforward explanation would be that the NCC [Lewandowsky] experiment was not externally valid—i.e., it did not realistically model the real-world dynamics of opinion-formation relevant to the climate change dispute.”
What should consensus publicity look like?
I think there’s another possible explanation: that Lewandowsky did realistically model the changes in opinion that might happen with a concerted and well designed consensus-publicity effort – but that from 2003 to 2013, we did not actually see such an effort.
Kahan implies that messaging during this period was widespread and well-funded. But was it as widespread as we would need such a campaign to be? And were the campaigns carried out in the best manner possible? For example, did the communicators use the best dissemination methods, the best language and the best graphical representations? Should they have targeted different populations with different, tailored messages?
I would like to see a more comprehensive analysis asking the questions:
- What did communication of the climate change consensus from 2003 to 2013 consist of? and
- Did it meet certain criteria that we should require of such a campaign?
Whether the actual consensus messaging carried out from 2003 to 2013 had the same characteristics that made Lewandowsky’s messaging effective, I could not say. But it certainly seems worth investigating what those characteristics might be. Of course, a prime concern is to discover if those characteristics include or depend on the artificial psychology lab environment – which would indicate that it is impossible to influence climate change opinions through consensus messaging in the real world.
An aside on sample size
I also note that Kahan doesn’t question the validity of Lewandowsky’s sampling. I can’t help wondering if Lewandowsky’s findings might not be, in some part, an artifact of small selection size.
The researchers compared a control group of 47 to a consensus condition group of 43. This means they were not literally testing the effect of consensus messaging on individual participants, but concluding that the difference in opinions between the two groups was due to the consensus messaging that one group received.
While this approach is advisable (a literal “before and after” set-up presents the problem of demand effect, as our class saw in its examination of Ranney et al,) it also depends on a large enough sample size to minimize the possibility that uncontrolled and unseen variables are affecting results. I’m not convinced that Lewandowsky’s sample size was large enough for that.