2019
DOI: 10.1016/j.jrp.2019.02.002
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Recognising faces but not traits: Accurate personality judgment from faces is unrelated to superior face memory

Abstract: Author contributions were as follows: LS led study conceptualisation. Study methodology was designed by LS, JD, EJD, NT and PM. Extant face memory data collection was led by JD. Data collection for this study was conducted by LS, EJD and NT. Software for personality and self-selected photograph collection was designed by NT and PM. Data analysis was conducted by LS. First draft was written by LS. Substantial editing was contributed from JD, NT and EJD.

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Cited by 17 publications
(22 citation statements)
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References 85 publications
(103 reference statements)
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“…As with previous research investigating SRs, a disproportionately high number of participants in the current research achieved SR criteria (e.g., Belanova, Davis, & Thompson, 2018;Satchell, Davis, Julle-Danière, Tupper, & Marshman, 2019). Many more scored slightly below our SR threshold.…”
Section: The Current Researchsupporting
confidence: 73%
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“…As with previous research investigating SRs, a disproportionately high number of participants in the current research achieved SR criteria (e.g., Belanova, Davis, & Thompson, 2018;Satchell, Davis, Julle-Danière, Tupper, & Marshman, 2019). Many more scored slightly below our SR threshold.…”
Section: The Current Researchsupporting
confidence: 73%
“…5 Some authors argue that to rigorously allocate SRs to groups, two or more tests are required. Following Satchell et al (2019), these three ANOVAs were therefore repeated with the exclusion of SRs (n = 41) achieving less than maximum on the GFMT (GFMT = 40), and controls (n = 89) scoring more than 1 SD outside the typical population mean on the GFMT (GFMT = 28-36 out of 40). These ANOVAs generated virtually identical effects as the main analyses reported above, albeit with larger between-group effect sizes for hits, F(1, 120) = 18.11, p < .001, η 2 = .131, foil IDs, F(1, 120) = 41.38, p < .001, η 2 = .256, and misses, F(1, 120) = 7.29, p = .008, η 2 = .057.…”
Section: Conflict Of Interestmentioning
confidence: 99%
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“…However, it is not clear that the accuracy observed for these highly controlled images would generalise to the variable conditions in which we see faces in everyday life, that is, faces that vary in expression, pose, lighting, and so forth. Ambient images may therefore provide a more ecologically valid estimate of impression accuracy than standardised images, although very few accuracy studies have used these stimuli (for exceptions; Back et al, 2010; Reiss & Tsvetkova, 2020; Satchell et al, 2019). Furthermore, it is important to show that accuracy can generalise to these sorts of naturalistic images because this context reflects people’s normal experience with faces.…”
Section: Measuring Accuracy Using Multiple Ambient Imagesmentioning
confidence: 99%
“…As with other online face recognition research that tends to attract far greater numbers of superior performers than in student-participant-dominated laboratory-typical (e.g., Belanova, Davis, & Thompson, 2018;Satchell, Davis, Julle-Danière, Tupper, & Marshman, 2019), a large proportion of participants in the current research achieved SR criteria. Many more scored slightly below our SR threshold, while only a few scored below the typical CFMT+ (Russell et al, 2009) control mean in research.…”
Section: The Current Researchmentioning
confidence: 52%