Exploring constituency-level estimates for the 2017 British general election

Abstract

Most opinion polls conducted during British general election campaigns report on each party’s estimated national vote share. Although of considerable interest, these data do not put the spotlight on the marginal seats, the constituencies targeted by the parties for intensive canvassing; these are where the contest for a majority in the House of Commons is won and lost. There have been some polls covering those constituencies as a whole, but very few of individual constituencies so there was very little reporting of the outcome for each party in those individual constituencies. That changed with the 2017 general election, when three analysts published estimates on the Internet of each party’s vote share separately for each constituency and with those data predicted which party would win each seat. This paper explores the veracity of those estimates, finding that although in general terms they accurately represented the relative position of each constituency in the share of each party’s votes, nevertheless their estimates of which marginal seats would be won by each were not as accurate. The implications of such polls, especially as their predictive ability is improved, are discussed.

Exploring young voter engagement and journey mapping across political events

“…This understanding extends existing research on voters' engagement restricted to a single election campaign (Pich et al 2018;Pickard 2019) or a single engagement dimension (Barrett and Brunton-Smith 2014) and addresses explicit calls for further research on young voter engagement (Dermody and Hanmer-Lloyd 2004;Dermody et al 2010;Dermody et al 2010;Harrison 2020;Pickard 2019;Russell et al 2002;Sloam and Henn 2017). In addition, this study contributes to the literature on customer journeys by uncovering novel insights emerging in this political context (Johnston et al 2018 In addition, this study aimed to identify effective communication tactics as touchpoints in the young voter's journey to inform future political stakeholders' decisions. Our research tracked the engagement levels, reflections and experiences of the political process of the same generational cohort from the 2015 UK General Election, 2016 UK-EU Referendum, 2017 UK General Election and hypothetical future elections.…”

“…Based on our inductive themes and building on existing research (Johnston et al 2018;Lin 2017;Parackal et al 2018;Pich et al 2018 Strategists should determine whether voters will be classified as receptors of information, cofacilitators and/or co-creators in future political events. Appropriate touchpoints should be adopted to appeal and resonate with voters.…”

“…;Lees-Marshment, 2019;Lees-Marshment et al 2019;Lin 2017;Nunan and Domenico 2019; Parackal et al 2018;Walker et al 2019;Wilson and Paleologos 2018).This interdisciplinary study addresses explicit calls for further research on young voter engagement(Chakravorti 2010;Henn et al 2005;Johnston et al 2018;Nunan and Domenico 2019; Parackal et al 2018;Pich et al 2018;Sloam and Henn 2019;Wilson and Paleologos 2018. …”

Online Activism and Dyadic Representation: Evidence from the UK E‐Petition System

“…Locally disaggregated information allows legislators to respond to the specific preferences of their constituents, which may differ from those of the population at large. such information is likely to be especially valuable in the united Kingdom, where constituency-specific polls are rare (Johnston et al 2018;Wring, Mortimore, and atkinson 2016). Constituency signature counts for each petition are made available on a centralized website, and this information is easy for MPs to access both in terms of the raw data and in the form of an interactive online map.…”

Multilevel regression with poststratification for the national level Viber/Street poll on the 2020 presidential election in Belarus

“…After applying statistical methods similar to the ones we use in this paper, the authors obtained estimates of the outcome of the 2012 US presidential election, that, ex-post, turned out to be on the mark. According to Wikipedia contributors [2020b], similar statistical methods were also able to successfully predict outcomes of the 2016 US presidential election [Trangucci et al, 2018, Wyatt et al, 2016, and the 2017 general election in the UK [Johnston et al, 2018].…”