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Abstract:
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Pledging to protect study participants’ identities (aka disclosure avoidance or DA) is becoming more challenging given the relatively new threats brought about by the sheer volume of large publicly available datasets and powerful, affordable computing capabilities that enable data linkages and respondent re-identification. We summarize a range of conventional DA methods and then bring the focus to qualitative research specifically. We discuss the development of a novel approach to a systematic DA method for at least a subset of qualitative research products: typical research aimed at pretesting and evaluation of survey questions, data collection instruments, and related materials used for household surveys in the federal statistical system. We frame the discussion in terms of risk and mitigation. That is, we describe the nature of qualitative methods and data, the risks posed by the dissemination of qualitative information products and consider how these risks might reasonably be mitigated while maximizing utility. Finally, we pull back the lens and discuss how the method could be applied to research outside the context of the federal statistical system if certain criteria are met.
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