Another explanation for the other-race effect is known as the social-motivational approach (e.g., Hehman, Mania, & Gaertner, 2010; Hugenberg et al., 2007; MacLin & Malpass, 2001; Meissner, Brigham, & Butz, 2005; Pauker et al., 2009; Sporer, 2001). This approach proposes that observers tend to process other-race faces at a race- or group-level, which requires less effort and fewer cognitive resources as compared to applying the individuation processes used on own-race faces. This means that without motivation, observers generally do not apply the individuation process to tell apart individuals of other races.
So how can we explain the phenomenon of other-race effect in face recognition – specifically, why are people able to perceptually individuate own-race faces from one to another but fail to individuate other-race faces? Following the social-motivational approach, research has been done that assumes that individuals have a well-developed ability to recognise and discriminate between faces, regardless of whether those faces are own- or other-race, but that people generally do not apply this ability to process other-race faces. In contrast, perceptual expertise theories suggest that it is not that people have not developed an ability to discriminate between other-race faces, but rather that people only obtain the ability to process own-race faces during their lifetime.
2.2.2.1 Some popular social-motivational approaches
Social-motivational approaches share an idea that, at an individual’s processing core, there exists a means for differential social categorisation of own- and other-race faces; however, the categorisation plays out differently on own- and other-race faces during the face encoding. Different social-motivational approaches emphasise different aspects of face processing. Levin (1996, 2000) proposed a feature-selection model that highlights feature-coding differences between own- and other-race faces. This
hypothesis assumed that other-race effect occurs due to individuals searching for category-specific features in other-race faces as they search for the individuating features that can help them discriminate between own-race faces. Similarly, Sporer (2001) proposed the ingroup/outgroup model (IOM) of face processing to account for outgroup recognition deficit – when people are less able to recognise individuals of an outgroup than those of an ingroup. Other-race faces are processed as outgroup
people tend to undertake relatively deep processing of configural information of faces from the ingroup, but prefer to process specific facial features (e.g., skin colour) or other salient clues (e.g. hairstyle) of the outgroup. This model can also account for other-age effect (Wright & Stroud, 2002) and other-gender effect (Slone, Brigham, & Meissner, 2000) in face memory literature. Meissner et al. (2005) proposed a dual- process approach, arguing that perceivers rely on a low-effort "feeling of familiarity" when processing and remembering other-race faces, while applying a more effortful "recollection" strategy when processing own-race faces.
With these perspectives in mind, I review the findings of studies testing these proposals in following section.
2.2.2.2 Evidence for social-motivational account: Motivation-to-individuate
instructions
Theories aside, several empirical findings support social-motivational
approaches when examined in multiple ways. The method of most direct relevance to this thesis is motivation-to-individuate instruction, which is used in Chapter 3.
Hugenberg et al. (2007) introduced an approach of motivation-to-individuate instruction to examine the other-race effect in face recognition, in which participants were told to “…pay close attention to what differentiates one particular face from another face of the same race, especially when the face is not an own-race face.” In the instructions, the other-race effect was explained and participants were encouraged to try their hardest to individuate the faces when encoding, particularly those of another race. The results indicated that the other-race effect could be eliminated by improving other- race face recognition through motivation-to-individuate instructions. The findings suggested that instructions could elicit observers’ motivation to process other-race faces at an individual level, which normally would only be applied to own-race faces. This approach was employed in a series of studies in Hugenberg’s laboratory, as well as by other researchers, all of whom have consistently shown that motivation instructions can reduce the other-race effect (e.g., Rhodes et al. 2009; Young, Bernstein, & Hugenberg, 2010; Young & Hugenberg, 2012).
Young et al. (2010) also found thatmotivation instructions could eliminate the other-race effect by improving observers’ recognition of other-race faces when
memory for other-race faces in participants with higher levels of other-race exposure than in participants with a lower level of such exposure (Young & Hugenberg, 2012). Likewise, another study which took place in the United States with White participants used similar motivation instructions, telling participants that “…people who are prejudiced tend to exclude biracial individuals from their group,” and asking them to pay close attention as they categorise the biracial faces to avoid prejudice (Pauker et al., 2009). They found that memory of ambiguous-race morphed faces increased with motivation instructions. Rhodes et al. (2009) tested Australian Caucasians in an Australian setting with Caucasian and Jamaican faces, and found that the robust other- race effect was removed when motivation instructions were given.
All the above findings provide consistent support that social-motivational accounts – in particular motivation-to-individuate instructions – can affect the magnitude of other-race effect in face recognition. Note that the above studies only tested Caucasian participants on White and Black faces in majority-Caucasian cultural settings (United States or Australia) rather than involving both races of participants. One question, then, is whether this is truly other-race effect due to research only involving a particular race of participants, and whether the findings can be generalised to different cultural settings.
Also, a recent study testing Caucasian and Asian faces with motivation
instruction (Tullis et al., 2014) found that motivation instructions did not affect the level of other-race effect on Caucasian participants, suggesting that in a cultural setting of “Caucasian versus Asian”, motivation instructions might not an origin of other-race effect. Thus, in Chapter 3, I will examine the other-race effect on both Caucasian and Asian faces for both Caucasian and Asian participants in an Australia setting.
2.2.2.3 Other ways of manipulating motivation-to-individuate
Other types of manipulations that have also been used to increase motivation to individuate other-race faces include: eliciting positive emotions prior to the recognition task (Johnson & Fredrickson, 2005), presenting the facial images with angry
expressions to increase observers’ attention to the other-race faces (Ackerman et al., 2006), and grouping other-race faces with university affiliation labels (Hehman, Mania, & Gaertner, 2010). Although some studies have shown supporting evidence for
motivation manipulation, others have not. Johnson & Fredrickson (2005) found that elicited positive emotion rather than negative or neutral emotion either before learning
or before testing could reduce the size of the other-race effect and increasing observers’ recognition of other-race faces. This finding is in line with the proposal that positive emotion could facilitate holistic perception (Basso, Schefft, Ris, & Dember, 1996; Derryberry & Tucker, 1994). Another manipulation used to elicit motivation for other- race face recognition involved asking participants to rate the attractiveness of own- and other-race faces, which presumed that the samples’ attractiveness rating would improve the depth of processing other-race faces, leading to an increase in other-race face recognition (Rhodes et al., 2009). Unexpectedly, findings indicated that manipulation via attractiveness only improved own-race face recognition, but had little effect on other-race face recognition, and resulted in no change to the other-race effect. This finding did not support the social-motivationalapproaches, but is in line with the perceptual expertise hypothesis of poor perceptual processing of other-race faces leading to a difficulty in processing other-race faces in depth.
More mixed findings have come from the manipulation of using angry facial expression images that could elicit individuals to pay more attention to other-race faces and increase other-race face recognition to overcome the other-race effect. A number of studies support the argument that angry expressions can reduce the other-race effect; for example, other-race effect was found when using White and Black neutral facial images with Caucasian participants, while other-race effect disappeared when using Black and White angry facial images, though Black angry faces were recognised better than neutral (Ackerman et al., 2006). Young and Hugenberg (2012) found similar results when using angry expressions. Krumhuber and Manstead (2011) found a reversed other-race effect with White observers when using White and Black angry expression stimuli. However, Gwinn, Barden and Judd (2015) noticed a weakness in the
previously-mentioned studies: in the pilot study, one particular facial stimuli that Ackerman et al. (2006) used – the Black angry faces – were found to be more
distinctive than Black neutral faces. In comparison, the difference between White angry and neutral faces was not as pronounced. Also, in the previous studies (Ackerman et al., 2006; Young & Hugenberg, 2012), the Black angry faces did not use the same
individual as the one used for Black neutral expressions – the identities were not counterbalanced across the expression condition.
Gwinn, Barden and Judd (2015) intentionally created a better test design using both White and Black participants with facial stimuli displaying both neutral and angry expressions. Their results showed that not only White but also Black participants were very poor at recognising Black angry faces. Their results suggested that the findings of
the previous studies could be explained by the flaws in design and stimuli choices rather than the elicited motivation to individuate other-race faces with negative emotions.
Another manipulation which has been used to increase motivation to individuate other-race faces has been to encourage participants to categorise other-race faces as ingroup rather than outgroup. The thought was that recognition of other-race faces could be improved if attached to own- rather than other-university labels, since other-race faces would then be considered as being ingroup, thus becoming processed at a deeper level. This typical paradigm was first used in an investigation of own-race faces
categorised as belonging to an outgroup, labelled as being from a competing university (Bernstein et al. 2007). Results indicated that faces with the participants’ own university labels (ingroup) were better remembered than faces labelled with competing university identification (outgroup), suggesting that ingroup/outgroup social categorisation is in line with the social-categorisation accounts on the other-race effect. Hehman, Mania, and Gaertner (2010) later used this method to explore the other-race effect in the United States. They found that other-race effect was eliminated, since recognition of other-race faces was increased to be at a similar level as the recognition of own-race faces when labelled as being from the participant’s own university. However, using exactly the same manipulation of university affiliation, Kloth, Shields, and Rhodes (2014) applied a crossover design in a Caucasian-Asian Australia context. The results showed no
influence of university affiliation on the strength of the other-race effect. Kloth et al. (2014) argued that previous differences could have been caused by facial stimuli differences between their own study and that of Hehman et al. (2010) – as unlike Hehman et al., Kloth et al. excluded hair and clothing in their facial images, and consistently used a black background rather than a variation of colour, to avoid participants using external cues to improve their memory of individual images. In addition to the stimuli differences, cultural difference could also be another reason for differences in the effect; university affiliation might not be as effective in eliciting ingroup/outgroup differentiations in Australian participants as compared to Americans. Kloth et al. concluded that their results were not supportive of social categorisation, but were still in line with perceptual expertise accounts. In sum, the empirical findings of using university affiliation are mixed, and do not solve the conflict of social-motivation approachesand percept expertise accounts. The multiple methods of increasing
participants’ motivation to tell apart other-race faces do not always reduce the other- race effect. Sometime this ability appears to depend on the races of participants as well
as the cultural setting, with consideration of socio-economic status; this is tested in Chapter 3.
2.2.2.4 Implications for overcoming the other-race effect
Social-motivational approaches suggest that the other-race effect can be easy to overcome if motivation is increased to shift processing to the individual level instead of simply the category level. For example, for customs officers, if they were informed of what other-race effect is and were encouraged to try harder to match passport photos of other-race individuals, it should then be easy to improve their recognition of other-race individuals. Similarly, improving the motivation to individuate suspects in an
eyewitness situation should lower misidentifications and consequent wrongful
convictions and incarcerations. However, the perceptual expertise hypothesis suggests that the other-race effect can only be overcome by many years of experience with other- race individuals.
2.2.3 The Categorization-Individuation Model; combining aspects of perceptual