King2010
| King2010 | |
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| 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 |
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| Tag(s) | EMCA, Membership Categorization Analysis, Qualitative methods, Computer-Assisted Qualitative Data Analysis |
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| Year | 2010 |
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| Journal | International Journal of Social Research Methodology |
| Volume | 13 |
| Number | 1 |
| Pages | 1–16 |
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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
