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Replication of Experiments Evaluating Impact of Psychological Distance on Moral Judgment : (Eyal, Liberman & Trope, 2008; Gong & Medin, 2012)

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Social Psychology

Hogrefe Publishing Group

10.1027/1864-9335/a000188

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The emotional dog and its rational tail: a social intuitionist approach to moral judgment.

J Haidt (2001)
Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent that rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.
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Back-Translation for Cross-Cultural Research

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Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs

Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists themselves, effect sizes are most useful because they facilitate cumulative science. Effect sizes can be used to determine the sample size for follow-up studies, or examining effects across studies. This article aims to provide a practical primer on how to calculate and report effect sizes for t-tests and ANOVA's such that effect sizes can be used in a-priori power analyses and meta-analyses. Whereas many articles about effect sizes focus on between-subjects designs and address within-subjects designs only briefly, I provide a detailed overview of the similarities and differences between within- and between-subjects designs. I suggest that some research questions in experimental psychology examine inherently intra-individual effects, which makes effect sizes that incorporate the correlation between measures the best summary of the results. Finally, a supplementary spreadsheet is provided to make it as easy as possible for researchers to incorporate effect size calculations into their workflow.

Author and article information

Journal
Social Psychology
Social Psychology
Hogrefe Publishing Group
1864-9335
2151-2590
May 2014
May 2014
: 45
: 3
: 223-231
© 2014

The Hogrefe OpenMind License is based on and identical to the Creative Commons Attribution-Noncommercial License Version 3.0. (The full Hogrefe OpenMind license has also been published as an open access article.)

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