Deciding on race: A diffusion model analysis of race-categorisation

It has long been known that a person's race can affect their decisions about people of another race; an observation that clearly taps into some deep societal issues. However, in order to behave differently in response to someone else's race, you must first categorise that person as other-race. The current study investigates the process of race-categorisation. Two groups of participants, Asian and Caucasian, rapidly classified facial images that varied from strongly Asian, through racially intermediate, to strongly Caucasian. In agreement with previous findings, there was a difference in category boundary between the two groups. Asian participants more frequently judged intermediate images as Caucasian and vice versa. We fitted a decision model, the Ratcliff diffusion model, to our two choice reaction time data. This model provides an account of the processes thought to underlie binary choice decisions. Within its architecture it has two components that could reasonably lead to a difference in race category boundary, these being evidence accumulation rate and a priori bias. The latter is the expectation or prior belief that a participant brings to the task, whilst the former indexes sensitivity to race-dependent perceptual cues. Whilst we find no good evidence for a difference in a priori bias between our two groups, we do find evidence for a difference in evidence accumulation rate. Our Asian participants were more sensitive to Caucasian cues within the images than were our Caucasian participants (and vice versa). These results support the idea that differences in perceptual sensitivity to race-defining visual characteristics drive differences in race categorisation. We propose that our findings fit with a wider view in which perceptual adaptation plays a central role in the visual processing of own and other race.