Understanding Epistemic Alignment in Uncertainty

: An ego-network analysis of public health influencers during the first wave of SARS-COV-2 in England

Abstract

Introduction: The focus of this research is on the factors that influence expert agreement and disagreement during periods of acute scientific and political uncertainty. This concerns theories and concepts that treat cognition as a socially conditioned process. To make sense of the world, scientists will routinely place their trust in others, but this is not predicated on agreement around specific facts. It relates to various attitudes, behaviours and identities that are anchored in epistemologies or preference systems. However, there is a paucity of studies focused on precisely how these behaviours affect epistemic alignment during emergencies. This research seeks to fill this gap by identifying the key characteristics that shaped epistemic alignment among scientists and public health experts during the early stages of the Covid-19 pandemic in England.

Theory and methods: Social network theory provides a set of concepts and methods with which one can seek to determine the tendency of individuals who possess specific characteristics to coalesce. Key topics during the first wave of Covid-19 in England were identified along with a seed sample of the individuals that mobilised around these. This seed sample was surveyed and asked to nominate scientists and public health experts who they had felt aligned and non-aligned with between January and July 2020. Further waves, based on their nominations, built the network.

Ego network quantitative analysis was conducted in UCINET to test the effects of a set of variables by looking at ego–alter similarity, or homophily, across a series of personal networks. These variables were: (1) insider–outsider status; (2) sex; (3) organisational type; and (4) scientific discipline. Through semi-structured interviews, coded in NVIVO utilising framework analysis, the meaning and content of the observed network ties was analysed from the perspective of the network members themselves.

Results and key findings: Network data collected between June 2021 and June 2022 produced alignment networks with 194 members. In total, 16 interviews were conducted between 22 March and 22 July 2022. The combined quantitative and qualitative analysis found that:
• insider-to-outsider status is a key factor that shapes epistemic alignment during emergencies;
• judging others based on perceptions of their motivations, values and integrity shapes epistemic alignment between individuals in science and public health communities;
• power dynamics in epistemic communities during a crisis are non-asymmetric given the high profiles and influence of both prominent insiders and rebel outsiders;
• peripheral insiders perform an important cognitive bridging role as they take into consideration different voices irrespective of their peers’ structural position.

Conclusions: We need to move beyond simple concepts of agreement on science to consider what really underpins epistemic alignment between scientists operating in highly uncertain environments. This will include their perceptions of their peers’ integrity, their motivations, and their styles of policy engagement. Future research opportunities include identifying suitable quantitative social network analysis methods for the interpretation of negative epistemic ties in fragmented personal networks.

Date of Award	25 Mar 2026
Original language	English
Awarding Institution	University of Bath
Supervisor	Graham Room (Supervisor), Jordan Tchilingirian (Supervisor), Harry Rutter (Supervisor) & Kathryn Oliver (Supervisor)