1. How Does Multiple Group Membership Affect Face Recognition in Asian Participants? Sarah Pearson, Jane Farrell, Christopher Poirier, and Lincoln Craton INTRODUCTION ABSTRACT Hugenberg, K., Young, S. G., Bernstein, M. J., & Sacco, D. F. (2010). The categorization-individuation model: An integrative account of the other-race recognition deficit. Psychological Review, 117, 1168-1187. doi:10.1037/ a0020463 Minear, M., & Park, D. C. (2004). A lifespan database of adult facial stimuli. Behavior Research Methods, Instruments, & Computers, 36, 630-633. doi:10.3758/BF03206543 Rhodes, M. G., & Anastasi, J. S. (2012). The own-age bias in face recognition: A meta- analytic and theoretical review. Psychological Bulletin, 138, 146-174. doi: 10.1037/a0025750 Wallis, J., Lipp, O. V., & Vanman, E. J. (2012) Face age and sex modulate the other-race effect in face recognition. Attention, Perception, & Psychophysics, 74, 1712-1721. doi:10.3758/s13414-012-0359-z Wiese, H. (2012). The role of age and ethnic group in face recognition memory: ERP evidence from a combined own-age and own-race bias study. Biological Psychology, 89, 137-147. doi:10.1016/j.biopsycho.2011.10.002 A 2 (target race: White, Asian) x 2 (target age: Young, Old) repeated- measures ANOVA was computed comparing the recognition accuracy (d’) across the four categories of faces. The results revealed significant main effects of target race, F(1,16) = 10.18, p =.006, and target age, F(1,16) = 10.81, p =.005. The interaction between target race and target age was not significant. A series of paired samples t-tests (one-tailed) revealed that significant differences existed between: young Asian and young White t(16) = -1.82, p =.044 young Asian and old Asian t(16) = 1.70, p =.055 young Asian and old White t(16) = -4.11, p <.001 Overall, our findings supported our hypothesis. Individuals exhibited both ORB and OAB effects, resulting in better recognition for young Asian faces than for the other three categories. The pattern of results exhibited by the Asian participants resembled those exhibited by White participants in both Wallis et al. (2012) and Wiese (2012). We found an ORB only for same-age faces, and we found an OAB only for same-race faces. HYPOTHESIS Research has demonstrated that people are skilled at recognizing faces; however, there is also evidence that people display biases that hinder recognition. For example, individuals display an own-race bias (ORB; see Hugenberg, Young, Bernstein, & Sacco, 2010), a tendency to better recognize faces of their own race. In addition, individuals display an own-age bias (OAB; see Rhodes & Anastasi, 2012), which means that they better recognize faces of their own age. Faces belong to multiple categories (e.g., age, race), and when observing a face, one may take into account all category memberships. Thus, it is essential to consider how recognition is affected by the interaction between multiple categories. To examine how the ORB and OAB interact, Wiese (2012) crossed target race and target age and found both an OAB and an ORB, but only for same- race and same-age faces, respectively. In a related study, Wallis, Lipp, and Vanman (2012) combined target race and target age and found an ORB, but only for same-age faces. Participants consisted of 17 Asian high school students visiting the United States as part of an academic enrichment program. Participants completed the experiment at a desktop computer using SuperLab software. Face stimuli consisted of 80 neutral faces divided evenly amongst four categories: young White, young Asian, old White, and old Asian (Minear & Park, 2004; Wallis et al., 2012). Participants completed an encoding phase in which they viewed 40 faces and rated each face as either “pleasant” or “unpleasant” by pressing the corresponding button on the keyboard. After encoding, participants completed a short filler questionnaire. They were not aware that the second phase would consist of a recognition task. During recognition, participants viewed the 40 faces from the encoding phase along with 40 new faces and identified each as either “seen” or “unseen.” Participants then completed a questionnaire about their demographics and prior experience with the four categories of faces. The current study further examined the relationship between target race and target age by testing Asian participants. We predicted that young Asian participants would more accurately recognize young Asian faces than any other category of faces. We examined the own-age and own-race biases in facial recognition. Young Asian participants viewed faces from four categories: young White, young Asian, old White, and old Asian. We assessed participants’ recognition accuracy (d’) for each category, which revealed better recognition for young Asian faces than for all other categories. METHOD DISCUSSION RESULTS REFERENCES