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Researchers have used eye-tracking measures to explore the relationship between face encoding and recognition, including the impact of ethnicity on this relationship. Previous studies offer a variety of conflicting conclusions. This confusion may stem from misestimation of the relationship between encoding and recognition. First, most previous models fail to account for the structure of eye-tracking data, potentially falling prey to Simpson’s paradox. Second, previous models assume a linear relationship between attention (e.g., the number of fixations to a to-be-remembered face) and recognition accuracy. Two eye-tracking studies (Ns = 41, 59), one online experiment that manipulates exposure (N = 150), and a mega-analysis examine the effects of ethnicity using what we believe to be more appropriate analytical models. Across studies and measures, we document a novel, critical pattern: The relationship between attention and recognition is nonlinear and negatively accelerating. At low levels of baseline attention, a small increment in attention improves recognition. However, as attention increases further, increments yield smaller and smaller benefits. This finding parallels work in learning and memory. In models that allow for nonlinearity, we find evidence that central features (eyes, nose, and mouth) generally contribute to recognition accuracy, potentially resolving disagreements in the field. We also find that the effects of attention on recognition are similar for ingroup and outgroup faces, which have important implications for theories of perceptual expertise. 

Face individuation involves sensitivity to physical characteristics that provide information about identity. We examined whether Black and White American faces differ in terms of individuating information, and whether Black and White perceivers differentially weight information when judging same-race and cross-race faces. Study 1 analyzed 20 structural metrics (e.g., eye width, nose length) of 158 Black and White faces to determine which differentiate faces within each group. High-utility metrics (e.g., nose length, eye height, chin length) differentiated faces of both groups, low-utility metrics (e.g., face width, eye width, face length) offered less individuating information. Study 2 ( N = 4,510) explored Black and White participants’ sensitivity to variation on structural metrics using similarity ratings. High-utility metrics affected perceived dissimilarity more than low-utility metrics. This relationship was non-significantly stronger for same-race faces rather than cross-race faces. Perceivers also relied more on features that were racially stereotypic of the faces they were rating. 

Contact with racial outgroups is thought to reduce the cross-race recognition deficit (CRD), the tendency for people to recognize same-race (i.e., ingroup) faces more accurately than cross-race (i.e., outgroup) faces. In 2001, Meissner and Brigham conducted a meta-analysis in which they examined this question and found a meta-analytic effect of r = −.13. We conduct a new meta-analysis based on 20 years of additional data to update the estimate of this relationship and examine theoretical and methodological moderators of the effect. We find a meta-analytic effect of r = −.15. In line with theoretical predictions, we find some evidence that the magnitude of this relationship is stronger when contact occurs during childhood rather than adulthood. We find no evidence that the relationship differs for measures of holistic/configural processing compared with normal processing. Finally, we find that the magnitude of the relationship depends on the operationalization of contact and that it is strongest when contact is manipulated. We consider recommendations for further research on this topic.