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Lookup NU author(s): Professor Daniel Nettle
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2020 The Authors. Many human societies feature institutions for redistributing resources from some individuals to others, but preferred levels of redistribution vary greatly within and between populations. We postulate that support for redistribution is the output of a structured cognitive system that is sensitive to features of the social situation. We developed an experimental approach in which participants prescribe appropriate redistribution for hypothetical villages whose features vary. Over seven experiments involving 2400 adults from the UK, we show that participants shift their redistribution preferences systematically as situational features change. Higher levels of redistribution are favoured when luck is more important in the initial distribution of resources; when social groups are more homogeneous; when the group is at war; and when resources are abundant rather than scarce. Judgements about the right level of redistribution carry moderate or high levels of moral conviction. Participants have systematic intuitions about when the implementation of redistribution will prove problematic, distinct from their intuitions about when it is desirable. Individuals are only weakly consistent in the level of redistribution they prefer, and political orientation explains rather little variation in preferred redistribution for a given situation. We argue that people have divergent views on redistribution at least in part because they have different appraisals of the features of their societies. Understanding the operating principles of the psychology of redistribution may help explain variation and change in support for, and hence existence of, redistributive institutions across societies and over time.
Author(s): Nettle D, Saxe R
Publication type: Article
Publication status: Published
Journal: Cognition
Year: 2020
Volume: 198
Print publication date: 01/05/2020
Online publication date: 13/02/2020
Acceptance date: 07/02/2020
Date deposited: 24/02/2020
ISSN (print): 0010-0277
ISSN (electronic): 1873-7838
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.cognition.2020.104234
DOI: 10.1016/j.cognition.2020.104234
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