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Abstract
This research replicates and expands upon the qualitative electoral research of Winters and Campbell by using data from focus groups conducted in Essex, England to coincide with three leadership debates during the 2010 British general election. The Qualitative Election Study of Britain (QES Britain) broadly replicated Winters and Campbell’s research design but includes innovations in data collection to more accurately capture assessments. This innovation means the data coding are based entirely on the evaluations of the participants. In our analysis we innovate in the way we display each leader’s unique evaluation structure. To capture the salience and direction of leadership assessments, we convey the dimensionality of popular perceptions for Brown, Cameron and Clegg using colour and scaling. Our results produce qualitatively informed evaluation structures for each party leader that contextualize quantitative survey findings. Although this case study is limited to a geographically specific group of participants, our results mirror the quantitative BES results. Such similarity in the qualitative and quantitative results increases our confidence that our results provide useful insights into the associations and evaluations ordinary people used in their assessments of the main political party leaders.
Keywords
Focus Groups, Leader Evaluations, Grounded Theory, Discourse Analysis, British Elections
Acknowledgements
We would like to thank Ms Amy Santee, our reviewer on this article for her insightful and helpful comments which have enriched and clarified the concepts discussed here.
Publication Date
11-4-2013
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.
DOI
10.46743/2160-3715/2013.1447
Recommended APA Citation
Winters, K., & Carvalho, E. (2013). 2010 British General Election Leader Evaluations: Replicating Electoral Focus Group Research. The Qualitative Report, 18(44), 1-21. https://doi.org/10.46743/2160-3715/2013.1447
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