Revisiting Classic Qualitative Studies

Authors

  • Mike Savage University of Manchester

DOI:

https://doi.org/10.17169/fqs-6.1.502

Keywords:

qualitative data, secondary analysis, classic studies, social class, re-analysis

Abstract

This paper explores methodological issues regarding the revisiting of "classic" qualitative studies. Classic studies pose particular issues for secondary analysis. By virtue of being "classic", the findings and arguments of such studies define a subsequent "canon" of theoretical and methodological scholarship, and hence shape the thinking of subsequent researchers conducting secondary analysis. Secondary re-analysis therefore should be not only of the archived data itself, but of the published work itself, but this raises a host of complex methodological and ethical issues. Using my own reanalysis of Elizabeth BOTT's "Family and Social Network' archive, and John GOLDTHORPE and David LOCKWOOD's "Affluent Worker collection", I examine possible analytical strategies for re-analysis, including "debunking", the alternative of "sacralisation", and ways in which original data can be read "against the grain".

URN: urn:nbn:de:0114-fqs0501312

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Author Biography

Mike Savage, University of Manchester

Mike SAVAGE is currently a Professor of Sociology at the University of Manchester where he is Director of the ESRC Centre for Research on Socio-Cultural Change (CRESC). His research interests are in renewing concepts of social class and stratification; using social network analysis to understand consumption and political mobilization; writing a history of English popular identities, 1950-2000, based on a Leverhulme Major Research Fellowship, and forthcoming monograph; and empirically examining the contours of socio-cultural change.

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Published

2005-01-31

How to Cite

Savage, M. (2005). Revisiting Classic Qualitative Studies. Forum Qualitative Sozialforschung Forum: Qualitative Social Research, 6(1). https://doi.org/10.17169/fqs-6.1.502

Issue

Section

Approaches to Re-use: Asking New Questions of Old Data