The robust beauty of majority rules in group decisions.

By Reid Hastie, Tatsuya Kameda. 2005

395 citations recorded by the source corpus.

Subfields: General Decision Sciences, Safety Research, Sociology and Political Science

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Decision Sciences

In Safety Research

In Sociology and Political Science

Citations in the corpus

The accuracy, fairness, and limits of predicting recidivism (2018, methodology): “To determine whether there is “wisdom in the crowd” (8) (in our case, a small crowd of 20 per subset), participant responses were pooled within each subset using a majority rules criterion.”
The social psychology of the wisdom of crowds. (2012, methodology): “When choosing among options, ―majority rule‖ performs well compared to more complex approaches (Hastie & Kameda, 2005; Sorkin, Luan, & Itzkowitz, 2004).”
A User's Guide to Debiasing (2014, background): “When judgments are provided by many people, an extremely effective way to combine them is to weight them equally, such as by taking the simple average or applying majority rule (e.g., Clemen, 1989; Hastie & Kameda, 2005).”
Swarm cognition in honey bees (2007, background): “Such discoveries could significantly deepen our understanding of human collective intelligence and enable us to more effectively structure groups to enhance their performance in business, economics, law, and politics (Steiner 1966; Laughlin and Ellis 1986; Laughlin 1999; Kerr and Tindale 2004; Hasti”
Recommendation to Groups (2007, background): “7 Hastie and Kameda [16] show how aggregation procedures can be compared in terms of their”
Group Decision Making Under Conditions of Distributed Knowledge: The Information Asymmetries Model. (2007, background): “For example, the renowned social decision schemes (SDS) approach (cf. Davis, 1973; Hastie & Kameda, 2005; Parks & Kerr, 1999) predicts group decisions with high degree of certainty on the basis of the distribution of individual prediscussion preferences and a small set of decision-making rules…”
When do people rely on algorithms (2016, methodology): “When attempting to accurately forecast future events, aggregation of individual forecasts can outperform forecasts made by individuals (Hastie & Kameda, 2005; Larrick & Soll, 2006).”
How Gullible are We? A Review of the Evidence from Psychology and Social Science (2017, background): “Finally, it should be stressed that, in the absence of sounder cues, majority is a robust cue to accuracy, so that it is far from unreasonable to follow it (Hastie & Kameda, 2005; Ladha, 1992).”
Advancing the Science of Collaborative Problem Solving (2018, background): “…psychological science research on teams has typically focused on learning in groups (Slavin, 2017), group decision making (Gigone & Hastie, 1997; Hastie & Kameda, 2005; Mesmer-Magnus & DeChurch, 2009), or team training (Mathieu, Hollenbeck, van Knippenberg, & Ilgen, 2017), rather than group…”
Identifying Expertise to Extract the Wisdom of Crowds (2015, background): “The principles of WOC have been applied to many cases ranging from prediction markets to informed policy making (Hastie and Kameda 2005).”