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Fairness heuristic theory is an empirical framework: A reply to Árnadóttir.

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Title: Fairness heuristic theory is an empirical framework: A reply to Árnadóttir.
Authors: BOS, KEES VAN DEN (AUTHOR), ALLAN LIND, E. (AUTHOR)
Source: Scandinavian Journal of Psychology. Jul2004, Vol. 45 Issue 3, p265-268. 4p.
Subjects: Psychology, Fairness, Justice, Heuristic, Reasoning
Abstract: In this article on fairness heuristic theory, we point out some important flaws in Árnadóttir's (2002) claim that fairness heuristic theory is “not empirical,” by which Árnadóttir meant that theory's predictions are knowable a priori, and are not contingent upon circumstances. To this end, we demonstrate that empirically testing effects predicted by fairness heuristic theory was and is important because this showed that the theory's propositions are not necessarily knowable a priori and are contingent upon circumstances. This implies that, according to Árnadóttir's definition, fairness heuristic theory clearly is an empirical framework. It would have been helpful if Árnadóttir had studied the fairness literature more thoroughly (as this would have easily revealed fairness heuristic theory to be not knowable a priori and to be contingent upon circumstances) and also if she had pointed out which of our studies fail to follow her line of reasoning. Our reply was written not as an attempt to defend fairness heuristic theory as we applaud, indeed are honored by, attempts to scrutinize our work in progress. Our only aim here was to point at some important flaws in the Árnadóttir article, because we think these will hamper rather than advance the science of psychology of justice. Van den Bos, K. & Lind, E. A. (2004). Fairness heuristic theory is an empirical framework: A reply to Árnadóttir. Scandinavian Journal of Psychology, 45, 265–268. [ABSTRACT FROM AUTHOR]
Copyright of Scandinavian Journal of Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: In this article on fairness heuristic theory, we point out some important flaws in Árnadóttir's (2002) claim that fairness heuristic theory is “not empirical,” by which Árnadóttir meant that theory's predictions are knowable a priori, and are not contingent upon circumstances. To this end, we demonstrate that empirically testing effects predicted by fairness heuristic theory was and is important because this showed that the theory's propositions are not necessarily knowable a priori and are contingent upon circumstances. This implies that, according to Árnadóttir's definition, fairness heuristic theory clearly is an empirical framework. It would have been helpful if Árnadóttir had studied the fairness literature more thoroughly (as this would have easily revealed fairness heuristic theory to be not knowable a priori and to be contingent upon circumstances) and also if she had pointed out which of our studies fail to follow her line of reasoning. Our reply was written not as an attempt to defend fairness heuristic theory as we applaud, indeed are honored by, attempts to scrutinize our work in progress. Our only aim here was to point at some important flaws in the Árnadóttir article, because we think these will hamper rather than advance the science of psychology of justice. Van den Bos, K. & Lind, E. A. (2004). Fairness heuristic theory is an empirical framework: A reply to Árnadóttir. Scandinavian Journal of Psychology, 45, 265–268. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Scandinavian Journal of Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/j.1467-9450.2004.00404.x
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        Text: English
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