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Other literature type . 2020
License: CC BY
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Research . 2020
License: CC BY
Data sources: Datacite
ZENODO
Research . 2020
License: CC BY
Data sources: Datacite
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R.I.C.E. – An Integrated Model of Welfare Deservingness Perceptions 2020

Working Paper #26
Authors: Knotz, Carlo; Gandenberger, Mia; Bonoli, Giuliano; Fossati, Flavia;

R.I.C.E. – An Integrated Model of Welfare Deservingness Perceptions 2020

Abstract

Research on deservingness perceptions is currently one of the most vibrant areas in the field of welfare state analysis. In this manuscript, we critically assess the state-of-the-art in this field of research and, in particular, the two dominant theoretical approaches, the C.A.R.I.N. framework and the ‘deservingness heuristics’ model. In doing so, we identify some important problems, including conceptual ambiguities and an insufficient explicit integration of the two theoretical models. We suggest a revised and integrated theoretical framework, which we believe provides a way to resolve these issues. Our model suggests four criteria to inform deservingness perceptions: Reciprocity, Identity, Control, and Effort (R.I.C.E.). We provide evidence for our model in the form of vignette experiments administered to online panels in the US and Germany.

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Keywords

Attitudes, C.A.R.I.N, Welfare state, Deservingness heuristic

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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