Interventions are to the social sciences what inventions are to the physical sciences – an application of science as technology. Behavioural science has emerged as a powerful toolkit for developing public policy interventions for changing behaviour. However, the translation from principles to practice is often moderated by contextual factors – such as culture – that thwart attempts to generalize past successes. Here, we discuss cultural evolution as a framework for addressing this contextual gap. We describe the history of behavioural science and the role that cultural evolution plays as a natural next step. We review research that may be considered cultural evolutionary behavioural science in public policy, and the promise and challenges to designing cultural evolution informed interventions. Finally, we discuss the value of applied research as a crucial test of basic science: if theories, laboratory and field experiments do not work in the real world, they do not work at all.

Field experiments which test the application of behavioural insights to policy design have become popular to inform policy decisions. This study is the first to empirically examine who and what drives these experiments with public partners. Through a mixed-methods approach, based on a novel dataset of insights from academic researchers, behavioural insight team members and public servants, I derive three main results: First, public bodies have a considerable influence on study set-up and sample design. Second, high scientific standards are regularly not met in cooperative field experiments, mainly due to risk aversion in the public body. Third, transparency and quality control in collaborative research are low with respect to pre-analysis plans, the publication of results and medium or long-term effects. To remedy the current weaknesses, the study sketches out several promising ways forward, such as setting up a matchmaking platform for researchers and public bodies to facilitate cooperation, and using time-embargoed pre-analysis plans.

Surveys based on self-reported hygiene-relevant routine behaviors have played a crucial role in policy responses to the COVID-19 pandemic. In this article, using anchoring to test validity in a randomized controlled survey experiment during the COVID-19 pandemic, we demonstrate that asking people to self-report on the frequency of routine behaviors are prone to significant measurement error and systematic bias. Specifically, we find that participants across age, gender, and political allegiance report higher (lower) frequencies of COVID-19-relevant behaviors when provided with a higher (lower) anchor. The results confirm that such self-reports should not be regarded as behavioral data and should primarily be used to inform policy decisions if better alternatives are not available. To this end, we discuss the use of anchoring as a validity test relative to self-reported behaviors as well as viable alternatives to self-reports when seeking to behaviorally inform policy decisions.

Behavioural public policy (BPP) has come under fire by critics who claim that it is illiberal. Some authors recently suggest that there is a type of BPP – boosting – that is not as vulnerable to this normative critique. Our paper challenges this claim: there's no non-circular way to draw the distinction between nudge and boost that would make the normative difference required to infer the permissibility of a policy intervention from its type-membership. We consider two strategies: paradigmatic examples and causal mechanisms. We conclude by sketching some suggestions about the right way to approach the normative issues.