Other-race categorisation advantage in a binary- vs. ternary-response race categorisation task^*

* The data of the current study are available by emailing Yongna Li at: [email protected].

ABSTRACT

When categorising a face based on race, people respond faster to other-race faces than own-race faces [Other-Race Categorisation Advantage (ORCA)]. Five experiments were conducted to examine the ORCA in Chinese participants in race categorisation tasks. Participants classified a face either as Chinese vs. non-Chinese (binary response) or as Caucasian, Indian, or Chinese (ternary response). Experiments 1A and 1B replicated the ORCA with Chinese vs. Caucasian and Chinese vs. Indian faces, respectively, in a binary-response task. Experiments 2A/2B and 3 presented faces of all three races in the ternary- and binary-response tasks. Task type was manipulated between and within participants in Experiments 2A/2B and 3, respectively. The typical ORCA occurred in the binary-response task, but did not consistently so in the ternary-response task. These results indicate that neither the race-feature hypothesis [Levin, D. T. 1996. Classifying faces by race: The structure of face categories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(6), 1364–1382] nor the differential processing hypothesis [Zhao, L., & Bentin, S. 2011. The role of features and configural processing in face-race classification. Vision Research, 51(23-24), 2462–2470] could fully account for the ORCA observed in the ternary-response task.

KEYWORDS:

• ORCA
• race categorisation
• face perception
• face processing

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

* The data of the current study are available by emailing Yongna Li at: [email protected].

1 We first conducted a 2 (Face Gender: male vs. female) × 2 (Face Race: Chinese vs. Caucasian) × 2 (Participant Gender) repeated-measures ANOVA for mean RTs of Experiment 1A. The main effects of face gender was significant, F(1,18) = 14.02, MSE = 167.82, p = .001, = .42. The main effects of face race was also significant, F(1,18) = 13.68, MSE = 305.94, p = .002, = .43. However, there was a significant interaction of face gender and face race, F(1,18) = 5.56, MSE = 107.57, p = .03, = .23. The main effect of participant gender was not significant, F(1,18) = .75, MSE = 14431.43, p = .398, = .04. The interactions of participant gender and other factors failed to reach the significance level: the interaction of face gender and participant gender, F(1,18) = .46, MSE = 167.82, p = .50, = .02; the interaction of face race and participant gender, F(1,18) = .33, MSE = 305.94, p = .56, = .01; the interaction of face gender, face race, and participant gender, F(1,18) = .02, MSE = 107.57, p = .89, = .001.

2 We first conducted a 2 (Face Gender: male vs. female) × 2 (Face Race: Chinese vs. Indian) × 2 (Participant Gender) repeated-measures ANOVA for mean RTs of Experiment 1B. The main effects of face gender was significant, F(1,17) = 8.30, MSE = 118.59, p = .01, = .33. The main effects of face race was also significant, F(1,17) = 47.69, MSE = 286.08, p < .001, = .74. However, there was a significant interaction of face gender and face race, F(1,17) = 10.83, MSE = 62.58, p = .004, = .39. The main effect of participant gender was not significant, F(1,17) = 1.15, MSE = 7995.25, p = .298, = .06. The interactions of participant gender and other factors failed to reach the significance level: the interaction of face gender and participant gender, F(1,17) = .62, MSE = 167.82, p = .44, = .03; the interaction of face race and participant gender, F(1,17) = 1.13, MSE = 305.94, p = .30, = .06; the interaction of face gender, face race, and participant gender, F(1,17) = 3.27, MSE = 107.57, p = .08, = .16.

3 We first conducted a 2 (Face Gender: male vs. female) × 3 (Face Race: Chinese, Caucasian, and Indian) × 2 (Participant Gender) repeated-measures ANOVA for mean RTs of Experiment 2A. The main effects of face gender was significant, F(1,21) = 130.84, MSE = 135.18, p < .001, = .86. The main effects of face race was also significant, F(2,42) = 22.16, MSE = 531.97, p < .001, = .51. However, there was a significant interaction of face gender and face race, F(2, 42) = 17.47, MSE = 117.07, p < .001, = .45. The main effect of participant gender was not significant, F(1,21) = 1.24, MSE = 5079.47, p = .27, = .05. Participant gender did not significantly interacted with face gender, F(1,21) = .26, MSE = 135.18, p = .62, = .01. The interaction of participant gender and face race was significant, F(2,42) = 5.19, MSE = 531.97, p = .011, = .19. The interaction of participant gender, face gender, and face race was also significant, F(2,42) = 3.97, MSE = 117.07, p = .026, = .16. Two separate 2 (Face Gender: male vs. female) × 3 (Face Race: Chinese, Caucasian, and Indian) ANOVAs were conducted for female and male participants. For female participants, there was a significant main effect of face gender [F(1,11) = 93.76, MSE = 90.02, p < .001, = .89] and a significant main effect of face race [F(2, 22) = 26.38, MSE = 533.33, p < .001, = .70]. The interaction of face gender and face race was also significant, F(2, 22) = 13.93, MSE = 160.65, p < .001, = .56. For male participants, the main effect of face gender was significant, F(1,10) = 50.02, MSE = 184.86, p < .001, = .83. The interaction of face gender and face race was also significant, F(2, 20) = 5.71, MSE = 83.92, p = .014, = .36. No significant main effect of face race was observed, F(2, 20) = 2.79, MSE = 820.35, p = .113, = .22.

4 We first conducted a 2 (Face Gender: male vs. female) × 3 (Face Race: Chinese, Caucasian, and Indian) × 2 (Participant Gender) repeated-measures ANOVA for mean RTs of Experiment 2B. The main effects of face gender was significant, F(1,20) = 70.25, MSE = 76.15, p < .001, = .78. The main effects of face race was also significant, F(2,40) = 35.82, MSE = 1538.94, p < .001, = .64. However, there was a significant interaction of face gender and face race, F(2, 40) = 3.97, MSE = 181.02, p = .03, = .16. The main effect of participant gender was not significant, F(1,20) = .05, MSE = 11893.09, p = .82, = .003. Participant gender did not significantly interacted with face gender, F(1,20) = 3.22, MSE = 76.15, p = .08, = .14. The interaction of participant gender and face race was not significant, F(2,40) = .35, MSE = 1538.94, p = .58, = .01. The interaction of participant gender, face gender, and face race was significant, F(2,40) = 3.76, MSE = 181.02, p = .037, = .16. Two separate 2 (Face Gender: male vs. female) × 3 (Face Race: Chinese, Caucasian, and Indian) ANOVAs were conducted for female and male participants. For female participants, there was a significant main effect of face gender [F(1,10) = 143.16, MSE = 27.55, p < .001, = .93] and a significant main effect of face race [F(2, 20) = 13.99, MSE = 2541.63, p = .003, = .58]. The interaction of face gender and face race was also significant, F(2, 20) = 5.24, MSE = 249.29, p = .024, = .34. For male participants, the main effect of face gender was significant, F(1,10) = 13.23, MSE = 124.76, p = .005, = .57. There was also a significant main effect of face race, F(2, 20) = 31.94, MSE = 588.71, p < .001, = .76. The interaction of face gender and face race was not significant, F(2, 20) = 1.75, MSE = 140.39, p = .202, = .15.

5 We first conducted a 2 (Task: ternary vs. binary response) × 2 (Face Gender: male vs. female) × 3 (Face Race: Chinese, Caucasian, and Indian) × 2 (Participant Gender) repeated-measures ANOVA for mean RTs of Experiment 3. The main effects of task, face gender, and face race were significant, F(1,15) = 181.61, MSE = 2333.92, p < .001, = .92 for task; F(1,15) = 58.09, MSE = 230.19, p < .001, = .79 for face gender; F(2,30) = 36.23, MSE = 892.04, p < .001, = .70 for face race. Three two-way interactions were also significant, F(1,15) = 10.28, MSE = 122.35, p = .006, = .40 for task × face gender; F(2,30) = 21.85, MSE = 843.55, p < .001, = .59 for task × face race; F(2,30) = 53.45, MSE = 214.32, p < .001, = .78 for face gender × face race. However, the 3-way interaction of task, face gender, and face race was not significant, F(2, 30) = 2.20, MSE = 161.84, p = .13, = .12. The main effect of participant gender was not significant, F(1,15) = 1.43, MSE = 23939.30, p = .25, = .08. The interaction of participant gender and task was significant, F(1,15) = 6.18, MSE = 2333.92, p = .025, = .29. Participant gender did not significantly interact with other factors: F(1,15) = .005, MSE = 230.19, p = .94, = .00 for face gender × participant gender; F(2,30) = .48, MSE = 892.04, p = .58, = .03 for face race × participant gender; F(1,15) = 1.23, MSE = 122.35, p = .28, = .07 for task × face gender × participant gender; F(2,30) = .24, MSE = 843.55, p = .74, = .016 for task × face race × participant gender; F(2,30) = 2.65, MSE = 214.32, p = .095, = .15 for face gender × face race × participant gender; F(2,30) = .966, MSE = 161.84, p = .38, = .06 for task × face gender × face race × participant gender.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China [grant number 15XNLQ05].