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

delete2022-04-01
delete14
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OA
AI
M
Melissa Beresford *
A
Amber Wutich
M
Margaret V. du Bray
A
Alissa Ruth
R
Rhian Stotts
C
Cindi SturtzSreetharan
A
Alexandra Brewis
DOI:10.1177/16094069221075860delete
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摘要

摘要

En 中文
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).
Keyword:
qualitative coding
team-based coding
qualitative data analysis
text analysis
intercoder reliability
intercoder agreement
collaborative research

期刊

I
International Journal of Qualitative Methods
IF:
3.8
论文数:
2.2K
被引数:
1.2W

机构

A
Arizona State University
学者数:
2.7W
论文数: 2.5W
被引数: 4.2W
S
San Jose State University
学者数:
1.3K
论文数: 1.0K
被引数: 15
California State University System 封面图
California State University System
学者数:
2.8W
论文数: 2.4W
被引数: 457
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