2026/03/30 by Elizabeth Green · 1 voice
Social Sciences · #Data Analysis and Archiving #Qualitative Research Methods and Ethics #Qualitative Research Methods and Applications
paper · pdf · doi:10.29173/iq1165
Qualitative data governance is increasingly formalised within infrastructures originally designed for quantitative research. These systems rely on tools such as suppression, generalisation and output checking, underpinned by epistemological assumptions that treat data as detachable, stable and decontextualisable. Such logics misalign with qualitative inquiry, where narrative meaning is relational, historically situated and co-constructed through interpretation. As a result, conventional governance practices risk enacting epistemic harms- flattening lived experience, distorting participant voice, and prioritising procedural defensibility over interpretive integrity. Drawing on hermeneutics, feminist epistemology and theories of epistemic injustice, this paper reframes qualitative data as meaning-bearing and relational rather than fragmentary or object-like. It critically examines how CARE, FAIR, the Five Safes and the Belmont principles offer valuable ethical resources but require reinterpretation to support qualitative epistemologies. In response, the paper develops the Interpretive and Relational Data Stewardship (IRDS) model, a framework grounded in interpretive awareness, relational accountability, epistemic justice and ethical stewardship. Through worked examples, it demonstrates how governance decisions actively reshape meaning and how over-abstraction can reproduce the very harms governance seeks to prevent. The paper argues that qualitative data governance must shift from logics of containment to practices that preserve the conditions under which meaning, dignity and justice can emerge.