Thanks to everyone who took part in this project. In this task, you viewed 20 initial images of Chinese faces, and were asked to decide whether you thought they were of the same person or not in the subsequent 40 images. If you have your e-mail with your scores on this project on hand you should be able to compare them with the full list of participants who competed this research at the bottom of this report. We have added your scores in a list below in Table 3. The main aim of this project was to pilot test a 40 Trial Chinese Face Recognition Test for a Singapore project, and to see how scores compared with those on the Cambridge Face Memory Test: Extended (CFMT+) (Russell, Duchaine, & Nakayama, 2009) and the Glasgow Face Matching Test (GFMT) (Burton, White, & McNeill, 2010). This gives us better insight into the other-race effect in face recognition, which suggests that “identifying a person from a different ethnic group results in even poorer performance [compared to identifying a person within one’s own ethnic group]” (Robertson Black, Chamberlain, Megreya, & Davis, 2020, p. 206). A summary of this research can be found in this article by David Robertson, Ahmed Megreya, and Josh Davis in the Conversation (Robertson, Megreya, & Davis, 2020).
In total, 371 volunteers completed the test (aged 18-65 years, M = 38.6, SD = 10.1, male = 137, female = 231, non-disclosed gender = 3, White-Caucasian = 294, other = 76). We were able to match all of those participants with their original scores on the CFMT+ and the GFMT stored on our database. Therefore, data from 371 participants are reported here. Table 1 displays median and mean scores on each test.
To see how you scored against the other participants, Figure 1 displays the frequency of total scores for the 40 Trial Chinese Face Recognition Test. Table 2 displays the Spearman’s correlation coefficients between total scores on each test, while scatter diagrams in Figure 2 and 3 visually display the relationships between each test.
As indicated by the correlations, people who achieve high scores on the GFMT, also do very well on the CFMT+. There is, however, there is also a weak significant correlation between the GFMT and 40 Trial Chinese Face Recognition Test.
The scores – in participant code order can be found below for the Chinese Face Matching Test. Note – these are the codes entered into the system.
Table 3 Scores for the 40 Trial Chinese Face Recognition Test
Burton, A. M., White, D., & McNeill, A. (2010). The Glasgow face matching test. Behavior Research Methods, 42(1), 286-291. DOI: 10.3758/BRM.42.1.286
Robertson, D. J., Black, J., Chamberlain, B., Megreya, A. M., & Davis, J. P. (2020). Super‐recognisers show an advantage for other race face identification. Applied Cognitive Psychology, 34(1), 205-216. (pre-print here). DOI: 10.1002/acp.3608
Robertson, D. J., Megreya, A., & Davis, J.P. (2020, January 10). Facial recognition: research reveals new abilities of ‘super-recognisers’. The Conversation. Retrieved from https://theconversation.com/facial-recognition-research-reveals-new-abilities-of-super-recognisers-128414
Russell, R., Duchaine, B., & Nakayama, K. (2009). Super-recognizers: People with extraordinary face recognition ability. Psychonomic Bulletin & Review, 16(2), 252-257. DOI: 10.3758/PBR.16.2.252