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Proc Natl Acad Sci USA. Distributions of observed death tolls govern sensitivity to human fatalities

Giuseppe

Emeritus
Distributions of observed death tolls govern sensitivity to human fatalities (Proc Natl Acad Sci USA, abstract, edited)

Distributions of observed death tolls govern sensitivity to human fatalities

1. Christopher Y. Olivola a,b,1 and 2. Namika Sagara c,d,e

Author Affiliations
1. aDepartment of Cognitive, Perceptual, and Brain Sciences, University College London, London WC1H 0AP, United Kingdom;
2. bEconomic and Social Research Council, Centre for Economic Learning and Social Evolution, London WC1H 0AN, United Kingdom;
3. cLundquist College of Business and
4. dDepartment of Psychology, University of Oregon, Eugene, OR 97403; and
5. eDecision Research, Eugene, OR 97401

1. Edited by Dale Purves, Duke University Medical Center, Durham, NC, and approved October 28, 2009 (received for review August 7, 2009)


Abstract

How we react to humanitarian crises, epidemics, and other tragic events involving the loss of human lives depends largely on the extent to which we are moved by the size of their associated death tolls. Many studies have demonstrated that people generally exhibit a diminishing sensitivity to the number of human fatalities and, equivalently, a preference for risky (vs. sure) alternatives in decisions under risk involving human losses. However, the reason for this tendency remains unknown. Here we show that the distributions of event-related death tolls that people observe govern their evaluations of, and risk preferences concerning, human fatalities. In particular, we show that our diminishing sensitivity to human fatalities follows from the fact that these death tolls are approximately power-law distributed. We further show that, by manipulating the distribution of mortality-related events that people observe, we can alter their risk preferences in decisions involving fatalities. Finally, we show that the tendency to be risk-seeking in mortality-related decisions is lower in countries in which high-mortality events are more frequently observed. Our results support a model of magnitude evaluation based on memory sampling and relative judgment. This model departs from the utility-based approaches typically encountered in psychology and economics in that it does not rely on stable, underlying value representations to explain valuation and choice, or on choice behavior to derive value functions. Instead, preferences concerning human fatalities emerge spontaneously from the distributions of sampled events and the relative nature of the evaluation process.

* decision-making
* psychophysics
* risk preferences
* value of human lives
* decision by sampling


Footnotes
* 1To whom correspondence should be addressed. Email: c.olivola@ucl.ac.uk
* Author contributions: C.Y.O. designed research; C.Y.O. and N.S. performed research; C.Y.O. analyzed data; and C.Y.O. wrote the paper.
* The authors declare no conflict of interest.
* This article is a PNAS Direct Submission.
* This article contains supporting information online at www.pnas.org/cgi/content/full/0908980106/DCSupplemental.
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<cite cite="http://www.pnas.org/content/106/52/22151.short?rss=1">Distributions of observed death tolls govern sensitivity to human fatalities ? PNAS</cite>
 
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