Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10439883 | Organizational Behavior and Human Decision Processes | 2005 | 21 Pages |
Abstract
People often reason proportionally, perceiving fixed outcomes as larger or smaller depending upon the reference condition. Thus, for policies affecting individuals, presenting data as percentages rather than frequencies can alter perceived effects on high versus low base rate group members, even though identical numbers of individuals in each group are affected. Such numerical framing effects were explored through a case analysis of public debates over race-conscious selection policies and through experimental manipulations employing a race-conscious university admissions scenario. Undergraduates (NÂ =Â 193) received data reporting the expected impact on black and white student enrollment resulting from a university shift to race-neutral admissions. Compared to those encountering percentages or proportions, participants receiving identical information expressed as frequencies revealed a predicted greater preference for race-neutral or “race blind” admissions. Structural equation analysis supported a model in which perceived impact and fairness mediated the relationship between format and endorsement of race-neutral admissions.
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Authors
James Friedrich, Gale Lucas, Emily Hodell,