Categorizing Human Identity in Writing Research: A Case for Participant Self-Identification in the Disaggregation of Data

Abstract

The disaggregation of data around human identities can act as a rich method, providing researchers with new ways of understanding community and workplace writing. However, demographic analysis can unknowingly perpetuate harmful stereotypes and constructions of human identity. This article examines common issues with disaggregation of identity-based data in research and details an empirical research project that drove the research team to reconsider new approaches to desegregated data. In response, I propose a participant self-identification method and offer a heuristic guiding researchers to critically interrogate demographic data collection, enabling more equitable, participant-centered approaches to understanding identity in writing research.

Keywords

Disaggregated Data Demographic Analysis Participant self-identification Equity-centered research

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