Abstract
The aggregation of individual judgments on logically connected issues often leads to collective inconsistency. This study examines two collective decision-making procedures designed to avoid such inconsistency—one premise-based and the other conclusion-based. While the relative desirability of the two procedures has been studied extensively from a theoretical perspective, the preference of individuals regarding the two procedures has been less studied empirically. In the present study, a scenario-based questionnaire survey of participant preferences for the two procedures was conducted, taking into consideration prevailing social norms in the society to which the participants belong and the heterogeneity of the participants’ past experiences. Results show that a minority opinion not matching a prevailing social norm is more likely to be supported when the conclusion-based procedure is used. This can be explained by a basic property of the conclusion-based procedure: The procedure does not require voters to reveal their reasons for reaching a particular conclusion. This property proves appealing for participants who have a minority opinion. Such a finding is highly relevant to future studies on strategic behaviors in choosing a collective decision-making procedure.
Similar content being viewed by others
References
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Bonnefon, J. F. (2007). How do individuals solve the doctrinal paradox in collective decisions? An empirical investigation. Psychological Science, 18, 753–755.
Bonnefon, J. F. (2010). Behavioral evidence for framing effects in the resolution of the doctrinal paradox. Social Choice and Welfare, 34, 631–641.
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Converting among effect sizes. In M. Borenstein, L. V. Hedges, J. P. T. Higgins, & H. R. Rothstein (Eds.), Introduction to meta-analysis (pp. 45–49). Chichester, UK: Wiley.
Bovens, L. (2006). The doctrinal paradox and the mixed-motivation problem. Analysis, 66, 35–39.
Bovens, L., & Rabinowicz, W. (2006). Democratic answers to complex questions—an epistemic perspective. Synthese, 150, 131–153.
Chow, S. L. (1988). Significance test or effect size? Psychological Bulletin, 103, 105–110.
Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York: Academic Press.
Dietrich, F., & List, C. (2007a). Arrow’s theorem in judgment aggregation. Social Choice and Welfare, 29, 19–33.
Dietrich, F., & List, C. (2007b). Strategy-proof judgment aggregation. Economics and Philosophy, 23, 269–300.
Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27, 861–874.
Ganzach, Y., & Schul, Y. (1995). The influence of quantity of information and goal framing on decision. Acta Psychologica, 89, 23–36.
Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences of the United State of America, 101, 5228–5235.
Grofman, B. (1985). The accuracy of group majorities for disjunctive and conjunctive decision tasks. Organizational Behavior and Human Decision Processes, 35, 119–123.
Grossi, D., & Pigozzi, G. (2014). Judgment aggregation: A primer. Synthesis Lectures on Artificial Intelligence and Machine Learning, 8, 1–151.
Grün, B., & Hornik, K. (2011). topicmodels: An R package for fitting topic models. Journal of Statistical Software, 40, 1–30.
Ishida, M. (2017). RMeCab: Interface to MeCab. R Package version 0.99997.
Kameda, T. (1991). Procedural influence in small-group decision making: Deliberation style and assigned decision rule. Journal of Personality and Social Psychology, 61, 245.
List, C. (2005). The probability of inconsistencies in complex collective decisions. Social Choice and Welfare, 24, 3–32.
List, C. (2006). The discursive dilemma and public reason. Ethics, 116, 362–402.
List, C., & Pettit, P. (2002). Aggregating sets of judgments: An impossibility result. Economics and Philosophy, 18, 89–110.
List, C., & Puppe, C. (2009). Judgment aggregation: A survey. In P. Anand, C. Puppe, & P. Pattanaik (Eds.), Oxford handbook of rational and social choice. Oxford: Oxford University Press.
Spiekermann, K. (2013). Judgment aggregation and distributed thinking. In S. J. Cowley & F. Vallee-Tourangeau (Eds.), Cognition beyond the brain (pp. 31–51). London: Springer.
Stanovich, K. E., & West, R. F. (2007). Natural myside bias is independent of cognitive ability. Thinking & Reasoning, 13, 225–247.
Stanovich, K. E., West, R. F., & Toplak, M. E. (2013). Myside bias, rational thinking, and intelligence. Current Directions in Psychological Science, 22, 259–264.
Wolff, J. (1994). Democratic voting and the mixed-motivation problem. Analysis, 54, 193–196.
Acknowledgements
This work was supported by the Grant-in-Aid for Japan Society for the Promotion of Science Fellows Grant number 13J05358.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics statement
This experiment was conducted when the author belonged to Japan Society of the Promotion of Science, and Department of Evolutionary Studies of Biosystems, School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies). This experiment was approved by the Research Ethics Committee of The Graduate University for Advanced Studies with the receipt number 2015008.
Rights and permissions
About this article
Cite this article
Sekiguchi, T. Preferences over procedures and outcomes in judgment aggregation: an experimental study. Theory Decis 86, 239–258 (2019). https://doi.org/10.1007/s11238-018-9678-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11238-018-9678-4