Risk Identification: A Corpus‐Assisted Study of Websites of Government Agencies

Abstract

Government agencies have a key role in the regulation, management, and communication of risk. This paper explores how seven Swedish government agencies in the policy fields of (i) chemicals, (ii) civil contingencies, (iii) energy, (iv) environmental protection, (v) food, (vi) housing and buildings, and (vii) traffic identify risks on their websites. The relational theory of risk is used as an analytical tool to unpack risk identification. An analytical distinction is made between “risk objects,” that is, potentially harmful objects, and “objects at risk,” that is values at stake. The articulation of risk objects and objects at risk on government agencies’ websites is explored by using corpus linguistic techniques that reveal lexical and grammatical patterns of the word “risk.” The agencies identify an extensive assembly of risk objects of various kinds. The sets of risks identified are rather idiosyncratic and there is limited overlap between agencies. The identification of objects at risk is less varied and idiosyncratic than the identification of risk objects, were the agencies appear to be more in agreement. The findings are discussed in relation to the scope of risk identification; institutional explanations, and in terms of conditions for inter‐agency collaboration, identified as a key feature of effective risk governance.