A quantum theory account of order effects and conjunction fallacies in political judgments

Yearsley, J. & Trueblood, J. S. (2017). A quantum theory account of order effects and conjunction fallacies in political judgments. Psychonomic Bulletin & Review, doi: 10.3758/s13423-017-1371-z

[img] Text - Accepted Version
Restricted to Repository staff only until 6 September 2018.

Download (4MB) | Request a copy


Are our everyday judgments about the world around us normative? Decades of research in the judgment and decision-making literature suggest the answer is no. If people's judgments do not follow normative rules, then what rules if any do they follow? Quantum probability theory is a promising new approach to modeling human behavior that is at odds with normative, classical rules. One key advantage of using quantum theory is that it explains multiple types of judgment errors using the same basic machinery, unifying what have previously been thought of as disparate phenomena. In this article, we test predictions from quantum theory related to the co-occurrence of two classic judgment phenomena, order effects and conjunction fallacies, using judgments about real-world events (related to the U.S. presidential primaries). We also show that our data obeys two a priori and parameter free constraints derived from quantum theory. Further, we examine two factors that moderate the effects, cognitive thinking style (as measured by the Cognitive Reflection Test) and political ideology.

Item Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in Psychonomic Bulletin and Review. The final authenticated version is available online at: https://doi.org/10.3758/s13423-017-1371-z.
Uncontrolled Keywords: Quantum probability theory, Order effects, Conjunction fallacy, Individual differences, Rationality
Divisions: School of Social Sciences > Department of Psychology
Related URLs:
URI: http://openaccess.city.ac.uk/id/eprint/18712

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics