Effective synthesis is necessary for innovation and scientific progress
Authored By:: Joel Chan
The advanced understanding from an effective synthesis can be a powerful force multiplier for choosing effective studies and operationalizations,1 and may be especially necessary for problems where it is difficult or impossible to construct decisive experimental tests. The issue of mask efficacy for reducing community transmission is a powerful example of this; as Face Masks Against COVID-19 put it,
“The standard RCT paradigm is well-suited to medical interventions in which a treatment has a measurable effect at the individual level and furthermore, interventions and their outcomes are independent across persons comprising a target population. By contrast, the effect of masks on a pandemic is a population-level outcome where individual-level interventions have an aggregate effect on their community as a system. Consider, for instance, the impact of source control — its effect occurs to other individuals in the population, not the individual who implements the intervention by wearing a mask…Even then, ethical issues prevent the availability of an unmasked control arm (27). The lack of direct causal identifiability requires a more integrative systems view of efficacy. We need to consider first principles — transmission properties of the disease, controlled biophysical characterizations alongside observational data, partially informative RCTs (primarily with respect to PPE), natural experiments (28), and policy implementation considerations — a discursive synthesis of interdisciplinary lines of evidence which are disparate by necessity.” (p. 3, emphasis ours)
To illustrate the power of synthesis for accelerating scientific progress, consider the example of Esther Duflo, who attributed her Nobel-Prize-winning work to the detailed synthesis of problems in developmental economics she obtained from a handbook chapter in How to Find the Right Questions. Indeed, scientific progress may not even be tractable without adequate synthesis (as theory), even with advanced methods and data:2 as Allen Newell famously said, “You can’t play twenty questions with nature and win.”3