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Bias and ignorance in demographic perception

Overview of attention for article published in Psychonomic Bulletin & Review, August 2017
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Title
Bias and ignorance in demographic perception
Published in
Psychonomic Bulletin & Review, August 2017
DOI 10.3758/s13423-017-1360-2
Pubmed ID
Authors

D. Landy, B. Guay, T. Marghetis

Abstract

When it comes to knowledge of demographic facts, misinformation appears to be the norm. Americans massively overestimate the proportions of their fellow citizens who are immigrants, Muslim, LGBTQ, and Latino, but underestimate those who are White or Christian. Previous explanations of these estimation errors have invoked topic-specific mechanisms such as xenophobia or media bias. We reconsidered this pattern of errors in the light of more than 30 years of research on the psychological processes involved in proportion estimation and decision-making under uncertainty. In two publicly available datasets featuring demographic estimates from 14 countries, we found that proportion estimates of national demographics correspond closely to what is found in laboratory studies of quantitative estimates more generally. Biases in demographic estimation, therefore, are part of a very general pattern of human psychology-independent of the particular topic or demographic under consideration-that explains most of the error in estimates of the size of politically salient populations. By situating demographic estimates within a broader understanding of general quantity estimation, these results demand reevaluation of both topic-specific misinformation about demographic facts and topic-specific explanations of demographic ignorance, such as media bias and xenophobia.

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Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 26%
Student > Master 8 12%
Researcher 7 11%
Student > Doctoral Student 6 9%
Other 6 9%
Other 9 14%
Unknown 12 18%
Readers by discipline Count As %
Social Sciences 14 22%
Psychology 13 20%
Business, Management and Accounting 3 5%
Medicine and Dentistry 3 5%
Computer Science 3 5%
Other 13 20%
Unknown 16 25%