Johnston, R.J., Hartman, T. orcid.org/0000-0001-9136-2784 and Pattie, C.J. orcid.org/0000-0003-4578-178X (2019) Predicting general election outcomes: campaigns and changing voter knowledge at the 2017 general election in England. Quality and Quantity, 53. pp. 1369-1389. ISSN 0033-5177
Abstract
There is a growing literature suggesting that the result for each constituency at British general elections can be predicted using ‘citizen forecasts’ obtained through voter surveys. This may be true for the majority of constituencies where the result at previous contests was a substantial majority for one party’s candidates: few ‘safe seats’ change hands. But is it true in the marginal constituencies, where elections are won and lost? Analysis of such ‘citizen forecast’ data for the Labour-Conservative marginal constituencies in 2017 indicates not. Although respondents were aware of the seats’ relative marginality and of general trends in party support during the campaign, they could not separate out those that were eventually lost by each party from those that were won again, even in seats where the elected party won comfortably.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Springer Nature B.V. This is an author produced version of a paper subsequently published in Quality & Quantity. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/s11135-018-0819-1. |
Keywords: | Forecasting; Wisdom of the Crowd; Constituencies; Marginality; England; 2017 |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Politics and International Relations (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Oct 2018 11:34 |
Last Modified: | 09 May 2024 09:00 |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s11135-018-0819-1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:136843 |