King2010

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King2010
BibType ARTICLE
Key King2010
Author(s) Andrew King
Title "Membership Matters": Applying Membership Categorisation Analysis (MCA) to Qualitative Data Using Computer-Assisted Qualitative Data Analysis (CAQDAS) Software
Editor(s)
Tag(s) EMCA, Membership Categorization Analysis, Qualitative methods, Computer-Assisted Qualitative Data Analysis
Publisher
Year 2010
Language
City
Month
Journal International Journal of Social Research Methodology
Volume 13
Number 1
Pages 1–16
URL Link
DOI 10.1080/13645570802576575
ISBN
Organization
Institution
School
Type
Edition
Series
Howpublished
Book title
Chapter

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Abstract

This paper introduces and outlines a methodology that may be unfamiliar to some qualitative researchers: Membership Categorisation Analysis (MCA). The first section of the paper explains the basic principles of MCA and why it is a valid method for exploring the power of categorisations in texts and talk. Additionally, it explains why MCA differs from other forms of qualitative data analysis. The second section begins with a discussion of why researchers might or might not use Computer‐Assisted Qualitative Data Analysis (CAQDAS) Software. Subsequently, a detailed description of how MCA was applied to qualitative data using the CAQDAS software package NVivo is outlined. To provide examples, this paper draws on a project that used MCA to analyse the interview accounts of 25 young people who had taken a Gap Year between leaving school and beginning university. The paper concludes that qualitative researchers should consider using MCA and that CAQDAS is a useful tool to aid its application.

Notes