Since we’ve already called out the March for Science, and some of the commentary surrounding it, we figured this would be a good inaugural topic. There’s no shortage of support, criticism, or journalistic assessment for the movement. Advocates raise numerous motivations for participating including standing up to misinformation, advocating for funding, and “reinstating evidence-based decision making” in government. Critics fear the politicization of science, and regret the possibility that participating scientists could appear to be self-interested political actors.
Setting aside the conflation of the March for Science with other political objectives, the March for Science debate swirls around whether it’s a good thing for capital-‘S’ Science and whether scientists should participate. But there are many sub-currents at play, including definitions of science, the reality (or not) of ‘evidence-based policy,’ and different conceptualizations of the role of science in policy. A healthy reflection on these sub-currents might inform judgments of the overarching debates; in particular, should we participate?
First, we argue that march organizers and would-be participants should clearly define the ‘Science’ they are marching for. The scientific method comes to mind as a unifying feature of a capital-‘S’ Science but it is often more a normative goal than a reflection of science in practice. Karl Popper’s premise for a unifying theory of science was falsifiability: Science cannot prove a hypothesis to be true, it can only demonstrate it as false. Yet Popper’s ideal falls short in practice. We tend not to throw out our best theories in the face of empirical evidence showing them wrong; we wait until we have a better theory. Thomas Kuhn highlighted this phenomenon in his groundbreaking, “The Structure of Scientific Revolutions.” Perhaps we don’t have ‘one’ Science but instead have many sciences, all updating theories not as they are proven wrong but as better theories and ideas develop.
Further, there are myriad scientific disciplines differentiated by objects of study, scales of investigation, and supporting institutions. For example, electrons, the study objects of many chemists and physicists, are a great deal more mathematically predictable than human cells, the objects of some biologists and medical researchers. And studying human cells is quite different from investigating entire cultural and social human-systems, the research subjects of anthropologists. Layered on top of the multiplicity of science is the diversity of scientists themselves who, despite being rather politically homogenous, still have unique political, social, and scientific ideals.
Okay, so you may be wondering, what does the non-monolithic nature of Science have to do with the decision to march? Well actually, it matters quite a bit if we’re marching under the guise of “Science for Policy!” These differences have implications for how we (decision-makers included) interpret research outcomes. For example, perpetual “physics envy” has many social scientists fighting to prove the statistical significance in their research outcomes when, of course, people are not electrons. In this case, metrics and statistics cloud rather than clarify, particularly when they neglect qualitative explorations of the phenomena and of assumptions inherent to statistical analyses. These differences hinder our ability to measure scientific excellence, thus having implications for “Policy for Science!” as well. If our metrics are biased toward quantitative sciences, which potentially important qualitative research programs are going without support? And which research questions are going unanswered, or worse, being unrealistically explored in the realm of mathematics, where qualitative, descriptive explanations of phenomena are more suitable, and often more illuminating?*
Which leads us to “evidence-based policies in the public interest,” an ideal of march advocates emphasized in the March for Science mission statement. Let’s set aside that defining the public interest is no small feat and break down what ‘evidence-based policy’ is and its role in current policy-making. Most people would agree that evidence-based policy is valuable and desirable. Most can agree that we should govern ourselves in some empirical reality. But a focus on science as the sole arbiter of evidence can be counter productive, particularly when dominant governance structures for science-related issues (e.g., environmental regulation, health) emphasize a ‘knowledge-first’ approach. A knowledge-first approach emphasizes understanding a problem before proposing solutions. This is problematic for two reasons: First, it demands absolute knowledge of a problem, making dispute over evidence the site of political negotiations, in turn leading to lengthy and expensive litigation, little improvement in the situation, and corrosion of the very notion of objective evidence. Second, we as humans tend not to stop doing something until we have something that does the job better (even with scientific theories!). Sarewitz and colleagues lay out why a knowledge-first approach was (and continues to be) detrimental in environmental policy. They also detail ways we might restructure policy to focus on solutions, including an innovative program in Massachusetts that emphasizes finding substitutes for commercially important but harmful chemicals, rather than an outright ban of them. Recognizing 1) that science can tell us about the world but not what we ought to do, 2) that a knowledge-first approach to policy is misguided, and 3) that the role of science in policy can be more than simply establishing understanding of a problem should lead us to think critically about calls for evidence-based policies or reframe them in terms of a search for better alternatives.
This all sounds very academic at this point and perhaps, like academics often do, we’ve lost sight of the decision tied to our analysis: should we participate in the March for Science? What is the potential for positive or negative impacts of the march? This is not a simple choice, and we have no prescription for action. We just ask that one reflects on the nuances; can you justify your decision in light of constructive criticism?
After muddling through, we are set on the political long game, namely making science a contributor to policy, and not an alternative venue for politics (if you accept our rationale). Scientists voicing their values are critical to the institutions of science and our democracy, but we ought to reflect on where such advocacy happens and on what scales. We will not participate though we share concern about the Trump administration’s approach to science policy. To be completely honest, we do feel guilty for not marching–we would just feel guiltier if we did.
*As a corollary, what about capital-‘P,’ Policy? Also fantasy. Laws are layered, decision-makers are ideologically and culturally diverse, and our government is designed as a heterodoxy. No single idea or ideology can continuously prevail, leading to diversity and competition for resources across time, even in science policy.
Some extra resources:
http://theconversation.com/to-tackle-the-post-truth-world-science-must-reform-itself-70455
http://www.latimes.com/science/sciencenow/la-sci-scientists-politics-trump-20170209-story.html
http://www.nature.com/news/researchers-should-reach-beyond-the-science-bubble-1.21514
Muddling Through Science, Policy, and Politics 