Coding Qualitative Data at Scale: Guidance for Large Coder Teams Based on 18 Studies

Author:

Beresford Melissa1ORCID,Wutich Amber2ORCID,du Bray Margaret V.3,Ruth Alissa2,Stotts Rhian2,SturtzSreetharan Cindi2,Brewis Alexandra2

Affiliation:

1. Department of Anthropology, San José State University, San Jose, CA, USA

2. School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA

3. Hollins University, Roanoke, VA, USA

Abstract

We outline a process for using large coder teams (10 + coders) to code large-scale qualitative data sets. The process reflects experience recruiting and managing large teams of novice and trainee coders for 18 projects in the last decade, each engaging a coding team of 12 (minimum) to 54 (maximum) coders. We identify four unique challenges to large coder teams that are not presently discussed in the methodological literature: (1) recruiting and training coders, (2) providing coder compensation and incentives, (3) maintaining data quality and ensuring coding reliability at scale, and (4) building team cohesion and morale. For each challenge, we provide associated guidance. We conclude with a discussion of advantages and disadvantages of large coder teams for qualitative research and provide notes of caution for anyone considering hiring and/or managing large coder teams for research (whether in academia, government and non-profit sectors, or industry).

Funder

Virginia G. Piper Charitable Trust

National Science Foundation

Publisher

SAGE Publications

Subject

Education

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