Age Bias in Laboratory and Field Settings: A Meta‐Analytic Investigation¹

Abstract

A meta-analytic review of age-discrimination research from laboratory and field settings revealed a significant, yet modest overall effect size with younger applicants and workers evaluated more positively than older applicants and workers. The present predictions and findings were compared with those from previous meta-analytic investigations by Kite and Johnson (1988) and by Finkelstein, Burke, and Raju (1995). A number of significant moderational relationships were revealed, including negative linear relationships between the relative generalizability of the research (in terms of participants, setting, and stimulus materials) and effect size. In addition, the type of design used (between-subjects vs. within-subject) and the specific type of dependent measures used to evaluate applicants and workers were found to significantly moderate effect size.'Portions of this research were presented at the May 2002 meeting of the Midwestern Psychological Association, Chicago, Illinois. The authors thank two anonymous reviewers for their helpful comments and suggestions; and Tara Hodges, Karen Sowada, and Christopher King for their assistance with the search process, coding, and the reliability assessment.2Correspondence concerning this article should be addressed to

One too many categories: an experimental test on the effectiveness of a dual-identity recategorization intervention on age-based bias

“…Negative stereotypes of younger workers by middle-aged and older individuals include the traits of tardiness, unreliability, laziness, immaturity, irresponsibility, arrogance, naiveté, selfishness, and undependability (Finkelstein et al 2012). Overall, however, evaluations remain, on average, more negatively valenced against older adults and workers (Bal et al 2011;Gordon and Arvey 2004;Finkelstein et al 1995;Kite et al 2005). Hence, age-based prejudice may be construed to be a special case within the larger family of group-based prejudices such that the dominant group, younger adults, may in fact experience prejudice, given the configuration of variables investigated at hand.…”

“…TMT has special application where older adults are concerned because older adults bring to mind our own mortality, thereby causing the threat of death and the fear of our own mortality to become salient; these fears lead to prejudice and discrimination against older adults (Greenberg et al 2004;Martens, Goldenberg and Greenberg 2005). In line with themes of decay and deterioration, a number of literature reviews on age stereotyping show that older workers are stereotyped as being less adaptable, creative, competent, flexible, ambitious, productive, competent, physically strong, interested in technological change, trainable, energetic, and active (e.g., Gordon and Arvey 2004;Kite et al 2005;McCann andGiles 2002/ 2004;Posthuma and Campion 2009). The most commonly identified of these negative stereotypes are incompetence and resistance to change, or inadaptability.…”

“…It was also found that rater age, amount of information presented, study design, and setting were all found to moderate this relation, such that greater bias was found in lab studies, by younger raters, when less information was presented, and in within-subject designs (Bal et al 2011;Gordon and Arvey 2004. ) This overall effect size is on par with that which has been found for in-group bias in general, ρ=.35 (Mullen, Brown and Smith 1992).…”

“…Although perceivably incompetent, then, older adults are simultaneously viewed to be "dear", or warm and friendly (Cuddy and Fiske 20022004). Meta-analytic reviews of the literature on age-based stereotypes buttress these notions, with older adults and workers being stereotyped as friendly, warm, and dependable (Gordon and Arvey 2004;Posthuma and Campion 2009).…”

An Investigation of the Underlying Mechanism of Discrimination: The Prototype Matching Model

“…On the other hand, personnel decisions are often influenced by characteristics that are jobirrelevant; for example, by the employee or applicant's sex (e.g., Ryan & Haslam, 2008;Turnage & Muchinsky, 1984), race (e.g., Dean, Roth, & Bobko, 2008;Roth, Bobko, McFarland, & Buster, 2008), age (e.g., Gordon & Arvey, 2004), weight (e.g., Roehling, Pichler, & Bruce, 2013;Rudolph, Weller, Wells, & Baltes, 2009), or sexual orientation (e.g., Croteau, 1996). Discrimination based on these characteristics creates a number of negative consequences for individuals, organizations, and society (Cox, 2001;Kane, 2003).…”