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The 2020 Covid-19 pandemic has forced science advisory institutions and processes into an unusually prominent role, and placed their decisions under intense public, political and media scrutiny. In the UK, a key controversy has centred on whether the government was too late in implementing its lockdown policy, resulting in thousands of unnecessary deaths, and the role of advice provided by the government’s Scientific Advisory Group for Emergencies (SAGE), a group of experts drawn from government, academia and industry (SAGE, 2020a ). In this article, I highlight how uncertainties in the virus doubling rate—an important input into lockdown decision-making—were downplayed in both the advice provided by SAGE and public comments by SAGE participants. Previous research has shown how knowledge producers perceive high uncertainty, whereas knowledge users perceive less uncertainty (MacKenzie, 1990 ), an issue particularly problematic for government science advice where differentiating between knowledge production and use may be challenging (Jasanoff, 2003 ). In the case of UK Covid-19 advice, the conflation of knowledge production and knowledge use has accompanied experts downplaying the uncertainty within their own models as they provided advice to decision makers. The consideration of policy options thus became anchored in a consensus that Covid-19 cases were doubling every five days, as opposed to the results of scientific modelling that showed doubling rates as low as three days were also credible. This failure to consider the full range of credible values for doubling rates projected an unwarranted sense of certainty to decision-makers and the public regarding the spread of the virus, and potentially helped to delay the implementation of a lockdown policy.
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