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Local Elections in England, 2015

Ekaterina Kolpinskaya Orcid Logo

UK Data Service

Swansea University Author: Ekaterina Kolpinskaya Orcid Logo

Abstract

The data collection was supported by the University of Exeter Q-Step Centre funded by the Nuffield Foundation and the Economic and Social Research Council (ESRC). The Electoral Reform Society (ERS), especially Jessica Garland and Chris Terry, provided invaluable feedback on the early versions of the...

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Published in: UK Data Service
Published: 2016
Online Access: https://discover.ukdataservice.ac.uk/catalogue/?sn=7926
URI: https://cronfa.swan.ac.uk/Record/cronfa31914
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first_indexed 2017-02-09T20:45:13Z
last_indexed 2018-02-09T05:19:16Z
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spelling 2017-03-07T15:13:40.0867022 v2 31914 2017-02-09 Local Elections in England, 2015 2e87b1d1463a69350e48657101392582 0000-0002-6973-3849 Ekaterina Kolpinskaya Ekaterina Kolpinskaya true false 2017-02-09 APC The data collection was supported by the University of Exeter Q-Step Centre funded by the Nuffield Foundation and the Economic and Social Research Council (ESRC). The Electoral Reform Society (ERS), especially Jessica Garland and Chris Terry, provided invaluable feedback on the early versions of the dataset, as well as the basis for the data coding frame. The ward- and council-level electoral results were collected from the local council web-sites listed on the BBC 2015 England Local Election results web-page and, in the instances when the reported data was incomplete, was obtained through direct contacts with the Returning Officers for the respective local authority. The initial data collection was completed by the University of Exeter Q-Step students, including Chris Curtis, Zofia Durkiewicz, James Harman, Josh Redmond, Samuel Shie Song Fa, Valeriya Titkova, Minh Tri Le and Edward Withers. Research data sets and databases UK Data Service Election and campaign studies - Politics Election returns - Politics Elites and leadership - Social stratification and groupings Government and political systems - Politics Political history - History Population censuses - Population, vital statistics and censuses 11 5 2016 2016-05-11 https://discover.ukdataservice.ac.uk/catalogue/?sn=7926 COLLEGE NANME Politics, Philosophy and International Relations COLLEGE CODE APC Swansea University 2017-03-07T15:13:40.0867022 2017-02-09T14:01:27.8235989 College of Arts and Humanities Political and Cultural Studies Ekaterina Kolpinskaya 0000-0002-6973-3849 1
title Local Elections in England, 2015
spellingShingle Local Elections in England, 2015
Ekaterina Kolpinskaya
title_short Local Elections in England, 2015
title_full Local Elections in England, 2015
title_fullStr Local Elections in England, 2015
title_full_unstemmed Local Elections in England, 2015
title_sort Local Elections in England, 2015
author_id_str_mv 2e87b1d1463a69350e48657101392582
author_id_fullname_str_mv 2e87b1d1463a69350e48657101392582_***_Ekaterina Kolpinskaya
author Ekaterina Kolpinskaya
author2 Ekaterina Kolpinskaya
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publishDate 2016
institution Swansea University
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department_str Political and Cultural Studies{{{_:::_}}}College of Arts and Humanities{{{_:::_}}}Political and Cultural Studies
url https://discover.ukdataservice.ac.uk/catalogue/?sn=7926
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description The data collection was supported by the University of Exeter Q-Step Centre funded by the Nuffield Foundation and the Economic and Social Research Council (ESRC). The Electoral Reform Society (ERS), especially Jessica Garland and Chris Terry, provided invaluable feedback on the early versions of the dataset, as well as the basis for the data coding frame. The ward- and council-level electoral results were collected from the local council web-sites listed on the BBC 2015 England Local Election results web-page and, in the instances when the reported data was incomplete, was obtained through direct contacts with the Returning Officers for the respective local authority. The initial data collection was completed by the University of Exeter Q-Step students, including Chris Curtis, Zofia Durkiewicz, James Harman, Josh Redmond, Samuel Shie Song Fa, Valeriya Titkova, Minh Tri Le and Edward Withers.
published_date 2016-05-11T03:54:46Z
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score 10.873106