Eliciting Interview Data Cleanly Through Minimising Leading Questions

Abstract

Chapter Summary

The purpose of this chapter is to enable interviewers to understand how they can elicit interviewee-generated data that are not ‘muddied’ by the researcher. The chapter has three main components. First, we discuss the authorship of data and illustrate how questions may unwittingly affect this authorship. Second, we outline the problem with ‘leading’ questions and introduce three features of leading questions that are relevant to researchers from different research epistemologies. Third, we introduce the ‘cleanness rating’, which is a way to categorise how questions are used in an interview according to the extent to which they are leading or ‘clean’. We conclude with the difference this can make for researchers, including enhancing the capacity for interviewers to reflect on their practice and making their role in the generation of interview data more transparent.

Citation

Cairns-Lee, H., Lawley, J. and Tosey, P. (2022), "Eliciting Interview Data Cleanly Through Minimising Leading Questions", Cairns-Lee, H., Lawley, J. and Tosey, P. (Ed.) Clean Language Interviewing, Emerald Publishing Limited, Leeds, pp. 17-30. https://doi.org/10.1108/978-1-80117-330-820221002