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Theoretical analysis reveals how software normalization enforces indexical coding in qualitative research, highlighting the need to safeguard interpretive agency against generative AI risks.
The entanglement between technology and methodology in qualitative research has largely been overlooked in management and organization studies (MOS). In this paper, we rectify this inattention, proposing that the way we analyze qualitative data be viewed as a socio-technical practice. Guided by social construction of technology (SCOT) theory, we identify the implications of the adoption and normalization of CAQDAS by the qualitative research community, including in MOS. We find that the rise of CAQDAS has been coupled with the legitimization and institutionalization of what we term indexical coding: the practice of ordering, labelling, and retrieving textual data segments. While indexical coding is often treated in MOS as methodologically authoritative and analytically indispensable, we problematize its dominance showing how it threatens interpretive agency and methodological pluralism. We propose ways forward that restore interpretive agency, reconnect data analysis to methodology, reclaim analytical pluralism and recognize the need for reflexivity in technology use - practices made more pressing with the advent of generative AI and its integration in CAQDAS.
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Nguyen et al. (2026) studied this question.
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