From something I'm working on . . .
I. EBSC: the basic idea. “EBSC” is a response to a deficient conception of how empirical information can be used to improve the communication of decision-relevant science.
Social psychology, behavioral economics, and other disciplines have documented the contribution that a wide variety of cognitive and social mechanisms make to the assessment of information about risk and related facts. Treated as a grab-bag of story-telling templates (“fast thinking and slow”; “finite worry pool”; "narrative"; "source credibility"; “cognitive dissonance”; “hyperbolic discounting”; “vividness . . . availability”; “probability neglect”), any imaginative person can fabricate a plausible-sounding argument about “why the public fails to understand x” and declare it “scientifically established.”
The number of “merely plausible” accounts of any interesting social phenomenon, however, inevitably exceeds the number that are genuinely true. Empirical testing is necessary to extract the latter from the vast sea of the former in order to save us from drowning in an ocean of just-so story telling.
The science of science communication has made considerable progress in figuring out which plausible conjectures about the nature of public conflict over climate change and other disputed risk issues are sound—and which ones aren’t. Ignoring that work and carrying on as if every story were created equal is a sign of intellectual charlatanism.
The mistake that EBSC is primarily concerned with, though, is really something else. It is the mistake of thinking that valid empirical work on mechanisms of consequence in itself generates reliable guidance on how to communicate decision-relevant science.
In order to identify mechanisms of consequence, the valid studies I am describing (there are many invalid ones, by the way) have used “laboratory” methods—ones designed, appropriately, to silence the cacophony of potential influences that exist in any real-world communication setting so that the researcher can manipulate discrete mechanisms of interest and confidently observe their effects. But precisely because such studies have shorn away the myriad particular influences that characterize all manner of diverse, real-world communication settings, they don’t yield determinate, reliable guidance in any concrete one of them.
What such studies do—and what makes them genuinely valuable—is model science communication dynamics in a manner that can help science communicators to be more confident that the source of the difficulties they face reflect this mechanism as opposed to that one. But even when the model in question generated that sort of insight by showing how manipulation of one or another mechanism can improve engagement with and comprehension of a particular body of decision-relevant science, the researchers still haven’t shown what to do in any particular real-world setting. That will inevitably depend on the interaction of communication strategies with conditions that are richer and more complicated than the ones that existed in the researcher’s deliberately stripped down model.
The researchers’ model has performed a great service for the science communicator (again, if the researchers’ study design was valid) by showing her the sorts of processes she should be trying to activate (and which sorts it will truly be a waste of her time to pursue). But just as there were more “merely plausible” accounts than could be true about the mechanisms that account for a particular science communication problem, there will be more merely plausible accounts of how to reproduce the effects that researchers observed in their lab than will truly reproduce them in the field. The only way to extract the genuinely effective evidence-informed science communication strategies from the vast sea of the merely plausible ones is, again, by use of disciplined empirical observation and inference in the real-world settings in which such strategies are to be used.
Too many social science researchers either don’t get this or don’t care. They engage in ad hoc story-telling, deriving from abstract lab studies prescriptions that are in fact only conjectures—and that are in fact often completely banal ("know your audience") and self-contradictory ("use vivid images of the consequences of climate change -- but be careful not to use overly vivid images because that will numb people") because of their high degree of generality.
This is the defect in the science of science communication that EBSC is aimed at remedying. EBSC insists that science communication be evidence based all the way down—from the use of lab models geared to identifying mechanisms of consequence to the use of field-based methods geared to identifying what sorts of real-world strategies actually work in harnessing and channeling those mechanisms in a manner that promotes constructive public engagement with decision –relevant science.
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IV. On “measurement”: the importance of what & why. Merely doing things that admit of measurement and measuring them doesn’t make science communication “evidence based.”
“Science communication” is in fact not a single thing, but all of the things that are forms of science communication have identifiable goals. The point of using evidence-based methods to promote science communication, then, is to improve the prospect that such goals will be attained. The use of empirical methods to “test” dynamics of public opinion that cannot be defensibly, intelligently connected to those goals is pointless. Indeed, it is worse than pointless, since it diverts attention and resources away from activities, including the use of empirical methods, that can be defensibly, intelligently understood to promote the relevant science communication goals.
This theme figures prominently and persuasively in the provocative critique of the climate change movement contained in the January 2013 report of Harvard sociologist Theda Skocpol. Skocpol noted the excessive reliance of climate change advocacy groups on “messaging campaigns” aimed at increasing the percentage of the general population answering “yes” when asked whether they “believe” in global warming. These strategies, which were financed to the tune of $300 million in one case, in fact had no measureable effect.
But more importantly, they were completely divorced from any meaningful, realistic theory of why the objective being pursued mattered. As Skocpol notes, climate-change policymaking at the national level is for the time being decisively constrained by entrenched political economy dynamics. Moving the needle" on public opinion--particularly where the sentiment being measured is diffusely distributed over large segments of the population for whom the issue of climate change is much less important than myriad other things -- won't uproot these political economy barriers, a lesson that the persistent rebuff of gun control and campaign-finance laws, measures that enjoy "opinion poll" popularity that climate change can only dream of, underscores.
So what is the point of EBSC? What theory of what sorts of communication improve public engagement with climate science (or other forms of decision-relevant science) and how should inform it? Those who don't have good answers to these questions can measure & measure & measure -- but they won't be helping anyone.