Overcoming the other-race effect in face recognition
Creators: name: Guilbert, Daniel
name: curby, kim
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Social Psychology
subject: Cognitive Psychology
subject: Social and Behavioral Sciences
subject: Psychology
subject: FOS: Psychology
subject: face recognition
subject: other-race effect

description: This pre-registration is to document our analysis plan for a study in which data collection is currently underway. These data have not been viewed and analysed in any way. Study Overview The other-race effect is a well-established phenomenon whereby people perform poorly when attempting to recognise faces that belong to a race different from their own, such as when a Caucasian person tries to recognise the face of a black person). According to social-cognitive accounts, this phenomenon occurs because Caucasians tend to individuate own-race faces (e.g. “That man looks like Jack”) but categorise other-race faces (e.g. “That man is black”). We aim to investigate whether allocating a name to a face encourages individuation and enhances face recognition, and whether it can reduce the other-race effect by improving recognition of other-race faces more than own-race faces. We are currently collecting data for a study involving an old/new face recognition paradigm. Participants will complete four separate face recognition tests within a single 45-minute online session. Each test will contain three phases. In Phase 1 (“learning phase”), participants will view 30 faces. This set will include 15 black faces and 15 white faces. Within each of these two race categories, five faces will be presented with a name directly above it (“named”), five faces will be presented with a number directly above it (“numbered”), and 5 faces will be presented without any accompanying name or number (“baseline”). During Phase 2 (“test phase”), participants will view 60 faces, consisting of 30 old faces (i.e. faces that were presented during the learning phase) and 30 new faces (i.e. faces that were not presented during the learning phase). Participants will be asked to indicate whether each face is ‘old’ or ‘new’ by pressing keys on a keyboard. Finally, in Phase 3 (“labelling phase”), the named and numbered faces from the learning phase will appear again one at a time, and participants will be asked to select which of five names or numbers had previously accompanied the face during the learning phase. This study is being conducted entirely online because of restrictions to in-lab testing of human participants due to the COVID-19 pandemic. Participants We are aiming to collect meaningful data from 75 Caucasian participants. To do this, we will need to recruit a larger number of participants, so that we can remove data belonging to: (i) participants who complete the study but do not identify as Caucasian; and (ii) participants who fail to perform at an adequate level, where an adequate level is defined as at least 60% accuracy in the test phase. The predicted sample size of 75 participants was determined following a power analysis conducted in G*Power, assuming 95% power for a 2 x 2 repeated measures ANOVA and a small-medium effect size. Planned Analyses A 2 (race: white faces, black faces) x 2 (condition: named, numbered) repeated measures ANOVA will be performed on the final dataset. As mentioned above, data from some participants will be removed because they are not Caucasian, or because they performed below the 60% cut-off point, meaning we cannot be sure that they properly engaged with the online task. We predict a significant main effect of race, whereby participants will recognise white (same race) faces better than black (other race) faces. We predict a significant main effect of condition, whereby participants will recognise named faces better than numbered faces. Finally, we predict a significant interaction, whereby the named faces will improve recognition more for black faces than for white faces. In other words, the named faces will reduce the other-race effect. If named faces are recognised more accurately than numbered faces, this could occur because naming improves face recognition, or because numbering weakens face recognition (perhaps due to de-individuation). Therefore, if there is a significant main effect of condition, or a significant interaction, these effects will be unpacked using the baseline condition, where faces were neither named nor numbered. This will tell us whether significant effects were caused by face recognition improving in the named condition, or face recognition deteriorating in the numbered condition. We will also conduct separate analyses using the data from the labelling phase to determine whether: (i) participants label white faces more accurately than black faces; (ii) participants label named faces more accurately than numbered faces; (iii) the discrepancy between named and numbered faces is greater for black faces than white faces; and (iv) performance on the labelling phase correlates significantly (and positively) with performance on the test phase.