Immigration, political trust, and Brexit - Testing an aversion amplification hypothesis

Abrams, Dominic and Travaglino, Giovanni A. (2018) Immigration, political trust, and Brexit - Testing an aversion amplification hypothesis. British Journal of Social Psychology, 57 (2). pp. 310-326. ISSN 0144-6665. (doi:https://doi.org/10.1111/bjso.12233) (Full text available)

PDF - Publisher pdf

Creative Commons Licence
This work is licensed under a Creative Commons Attribution 4.0 International License.
Download (292kB) Preview
[img]
Preview
Official URL
https://doi.org/10.1111/bjso.12233

Abstract

A few weeks prior to the EU referendum (23rd June 2016) two broadly representative samples of the electorate were drawn in Kent (the south-east of England, N = 1,001) and Scotland (N = 1,088) for online surveys that measured their trust in politicians, concerns about acceptable levels of immigration, threat from immigration, European identification, and voting intention. We tested an aversion amplification hypothesis that the impact of immigration concerns on threat and identification would be amplified when political trust was low. We hypothesized that the effect of aversion amplification on voting intentions would be mediated first by perceived threat from immigration, and then by (dis) identification with Europe. Results in both samples were consistent with this hypothesis and suggest that voters were most likely to reject the political status quo (choose Brexit) when concerns that immigration levels were too high were combined with a low level of trust in politicians.

Item Type: Article
Divisions: Faculties > Social Sciences > School of Psychology
Depositing User: Dominic Abrams
Date Deposited: 08 Feb 2018 09:36 UTC
Last Modified: 30 May 2018 14:19 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65968 (The current URI for this page, for reference purposes)
Abrams, Dominic: https://orcid.org/0000-0002-2113-4572
Travaglino, Giovanni A.: https://orcid.org/0000-0003-4091-0634
  • Depositors only (login required):

Downloads

Downloads per month over past year