Abstract

In this case study, I address the procedural ethics of conversation analysis (CA) and the collection of naturally occurring mundane interactions. I draw from the challenges that emerged from the institutional ethics review of the HIV, health and interaction study (the H2I Study), a CA project that sought to identify the practices through which normative assumptions of HIV and other health conditions are produced in conversations. Consistent with CA’s preference for naturally occurring interactions, the H2I Study collected and analysed everyday telephone calls involving people living with HIV. This article offers practical strategies CA researchers might use to navigate two ethical concerns raised about the collection of naturally occurring mundane interactions. The first questions the merits of collecting naturally occurring mundane interactions. For those unfamiliar with CA, the specific advantages of analysing naturally occurring mundane interactions may not be self-evident. This places an evidentiary burden on CA researchers to warrant the collection of this type of data. To address this concern, I suggest demonstrating in ethics applications the analytic value of CA using publicly available interactions. The second concern questions the use of verbal consent necessary for the collection of naturally occurring mundane interactions. Like most CA research, the H2I Study required flexible informed consent protocols appropriate for spontaneous and unpredictable interactions. Drawing from within and outside the CA literature, I offer three rationales for the use of verbal consent. This article is written as a practical resource for conversation analysts seeking approval from their research ethics board (REB) and for REBs who might be unfamiliar with CA research. This article contributes to a small but growing body of literature that documents not only the kinds of challenges CA researchers encounter from institutional ethics review, but the specific procedural ethics they may employ to secure ethics approval.

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