Individual Differences in Group Loyalty Predict Partisan Strength

Individual Differences in Group Loyalty Predict Partisan Strength The strength of an individual’s identification with their political party is a powerful predictor of their engagement with politics, voting behavior, and polarization. Partisanship is often characterized as primarily a social identity, rather than an expression of instrumental goals. Yet, it is unclear why some people develop strong partisan attachments while others do not. I argue that the moral foundation of Loyalty, which represents an individual difference in the tendency to hold strong group attachments, facilitates stronger partisan identification. Across two samples, including a national panel and a convenience sample, as well as multiple measures of the moral foundations, I demonstrate that the Loyalty foundation is a robust predictor of partisan strength. Moreover, I show that these effects cannot be explained by patriotism, ideological extremity, or directional effects on partisanship. Overall, the results provide further evidence for partisanship as a social identity, as well as insight into the sources of partisan strength. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Political Behavior Springer Journals

Individual Differences in Group Loyalty Predict Partisan Strength

Loading next page...
 
/lp/springer_journal/individual-differences-in-group-loyalty-predict-partisan-strength-H7116oCV74
Publisher
Springer US
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Political Science and International Relations; Political Science; Sociology, general
ISSN
0190-9320
eISSN
1573-6687
D.O.I.
10.1007/s11109-016-9367-3
Publisher site
See Article on Publisher Site

Abstract

The strength of an individual’s identification with their political party is a powerful predictor of their engagement with politics, voting behavior, and polarization. Partisanship is often characterized as primarily a social identity, rather than an expression of instrumental goals. Yet, it is unclear why some people develop strong partisan attachments while others do not. I argue that the moral foundation of Loyalty, which represents an individual difference in the tendency to hold strong group attachments, facilitates stronger partisan identification. Across two samples, including a national panel and a convenience sample, as well as multiple measures of the moral foundations, I demonstrate that the Loyalty foundation is a robust predictor of partisan strength. Moreover, I show that these effects cannot be explained by patriotism, ideological extremity, or directional effects on partisanship. Overall, the results provide further evidence for partisanship as a social identity, as well as insight into the sources of partisan strength.

Journal

Political BehaviorSpringer Journals

Published: Oct 8, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off