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Characteristics of social categorization based on variations in gender and age.

Psychologists generally believe that perceivers process a target automatically and rapidly according to age, gender, race, occupation, and other social categories (Maner, Miller, Moss, Leo, & Plant, 2012). We questioned if it is possible that the combined information from multiple social categories could trigger an automatic processing. Considerable controversy exists with regard to whether the processing triggered by each subcategory of multiple social categories is fully automated, conditionally regulated, or even inhibited. Some researchers hold that social categorization occurs automatically and unconditionally (Devine, 1989). However, others indicate that it is restricted by certain factors, such as cognitive resources (Casper, Rothermund, & Wentura, 2010) and social contexts (Barden, Maddux, Petty, & Brewer, 2004).

In previous studies, scholars have found that perceivers might activate one or more subcategories and inhibit other competing subcategories. For example, Sinclair and Kunda (1999) found when the instruction was "The black doctor gives positive feedback," participants activated the occupation category (doctor) and inhibited the race category (black) while being faced with black faces. However, if participants got negative feedback, they would activate the race category (black) and inhibit the occupation category (doctor). Rydell, McConnell, and Beilock (2009) also asserted that different social categories could be activated or inhibited in different contexts. When presented with a female's poor performance in mathematics, the gender category (female) was activated and the educational background category (university student) was inhibited. Conversely, presented with a female's good performance in mathematics, the category of educational background (university student) was activated and the gender category (female) was inhibited.

As mentioned above, numerous researchers have confirmed the existence of an effect of selective priority processing, or inhibition, when perceivers process multiple social categories embodied in faces. This is presumed to result from the different automatic processing levels among the multiple social subcategories. In order to further clarify the characteristics of multiple social categorization, we selected gender and age as two primordial social subcategories that are seen daily in faces. Wiese, Schweinberger, and Neumann (2008) argue that, as primordial social categories, age categorization and gender categorization are both processed automatically.

Notably, participants in previous studies were almost exclusively university students, and older people were rarely analyzed. Hills and Lewis (2011) found that the perceiver's age plays a vital role in face cognition, and Ebner and Johnson (2009) demonstrated that older people were less capable of judging facial expressions than younger people were. Voelkle, Ebner, Lindenberger, and Riediger (2012) indicated that younger persons were more accurate than older ones were in assessing the age of faces. Similarly, the perceiver's gender also has an important significance in face cognition. Megreya, Bindemann, and Havard (2011) found that females had some advantage in face recognition. However, in some studies, researchers indicated that males also had certain advantages in recognizing male faces (Ino, Nakai, Azuma, Kimura, & Fukuyama, 2010).

Few researchers have explored what happens to categorization when the subcategories vary and that, therefore, is what motivated our study. We employed Garner's (1974) selective attention paradigm to determine which properties of some simple nonsocial categories, such as shape and color, independently occupy their own processing dimension. If selective attention is effective in the presence of irrelevant variation, the categories can be considered independent; otherwise, the categories follow a pattern of integrality. We focused on investigating whether or not perceivers concentrated on a specific target's social subcategory while ignoring variation in the other, irrelevant, target's social subcategory. We used the following two different task conditions in our experiment: a) baseline and b) orthogonal. In the baseline condition, only the target category varies in the same block and the other irrelevant category holds constant. In the orthogonal condition, both the gender and age categories vary simultaneously in the same block. If perceivers concentrate on the irrelevant social subcategory, it is assumed that the categorization of that social subcategory is automatic and uncontrollable.

In light of the literature, our hypotheses are as follows:

Hypothesis 1: The response time in the baseline conditions will be shorter than that in the orthogonal condition.

Hypothesis 2: There will be an age effect between the younger and the older participants, such that younger, compared to older, participants will exhibit a higher level of automatic processing.

Hypothesis 3: There will be a gender effect of categorization between male and female faces, such that females will process female faces more quickly and accurately than males will, while males will process male faces more quickly and accurately than females will.



Our study sample comprised 38 younger participants (20 of whom were women) recruited from Shanghai Normal University (aged 19-26 years, M = 22 years, SD = 2.98), and 40 older participants (19 of whom were women) recruited from Shanghai Elderly University (aged 58-88 years, M = 64.75 years, SD = 4.87). All participants were right-handed and had normal or corrected-to-normal vision. They received monetary rewards of RMB20 (US$3.30) after the experiment.

Stimulus Materials

The task stimuli were taken from a database of Chinese faces (Bai, Ma, & Huang, 2005) and had unified treatment in which all of the photos were edited using Photoshop 8.0 in order to remove interference from hair, clothing, and background information. The files were standardized to 350 x 590 pixels and gray tone. Face stimuli differed on the two orthogonal dimensions of gender (female vs. male) and age (old vs. young). We selected 120 faces (30 young men, 30 young women, 30 old men, 30 old women) that had no significant difference in attraction. As a pretest, 20 university students from Shanghai Normal University, who did not participate in the formal experiment, were asked to judge the gender and age of these faces and then rate the faces' attractiveness on a 5-point scale ranging from 1 (not attractive at all) to 5 (extremely attractive), with lower scores indicating lower attractiveness. All of their category judgments were correct and all of the faces had no significant difference in attractiveness. Among these faces, there were 60 target faces with a mole (15 young men, 15 young women, 15 old men, 15 old women). Further, as a second pretest, 20 university students from Shanghai Normal University, who did not participate in the formal experiment, were asked to judge the gender and age of these faces and then rate the faces' attractiveness on a 5-point scale ranging from 1 (not attractive at all) to 5 (extremely attractive). All of their category judgments were correct and all of the faces had no significant difference in attractiveness.


We programmed the experiment using E-Prime 2.0 software. After being seated, facing the computer screen, participants were told that they would see a series of facial photographs and that they were to judge whether or not there was a mole on each face, pressing the corresponding key as accurately and quickly as possible. If the face had a mole, they were to press "F," if not, they were to press "J" (the response key mappings were counterbalanced across participants). For each trial of the experiment a fixation point "+" was presented for 500 ms at the center of the screen, followed by the face stimulus presented for 1,500 ms. The next fixation was not presented on the monitor until the participant pressed one of the keys. There were two blocks in each of the two baseline conditions. For example, in the age baseline condition, in each block, participants saw 20 faces of the same age (young faces or old faces) with random variation in gender. In the orthogonal condition, participants saw 40 faces with random variations in both age and gender.


The analysis yielded a significant main effect of participant age, F(1, 74) = 19.19, p < .001, [[eta].sup.2] = .21. Younger participants reacted faster than older participants and a main effect of target age was also significant, F(1, 74) = 7.06, p < .01, p2 = .09. This result supports Hypothesis 2 and suggests that it took participants a longer time to judge the old faces compared with the young faces.

There was a significant interaction between the condition and target age, F(2, 73) = 4.8, p < .01, [[eta].sub.2] = .06. Simple effects analysis revealed that in the gender baseline condition, the simple main effect of target age was significant, F(1, 77) = 27.47, p < .001. That is to say, perceivers' response to old faces was much slower than to that of young faces. The simple main effect of the condition was significant when judging the old faces, F(1, 77) = 5.14, p = .007. The response to the old faces in both baseline conditions was slower than that in the orthogonal condition. This result did not support Hypothesis 1.

There was a significant interactive effect between the condition and target gender, F(2, 73) = 4.32, p = .015, [[eta].sub.2] = .06. The simple main effect of the target gender was significant in the gender baseline condition, F(1, 77) = 5.68, p = .02. Specifically, participants reacted more quickly to male faces than to female faces. The simple main effect of the condition was significant when judging female faces, F(1, 77) = 3.58, p = .03. That is, participants reacted slowest in the gender baseline condition compared with the other conditions. This result did not support Hypothesis 1.

Finally, the interactive effect between target gender and target age was significant, F(1, 74) = 10.84, p = .002, [[eta].sub.2] = .13. In terms of the female faces, the simple main effect of face age was significant, F(1, 77) = 23.54, p < .001, such that participants reacted more quickly to young female faces than to old female faces. The simple main effect of target gender was significant with old faces, F(1, 77) = 9.04, p = .004, such that perceivers reacted slower to the old female faces than to the old male faces. These results were related to Hypothesis 3, but did not fully support it.


In this study, we manipulated variations in age and gender to explore the characteristics of multiple social categorization. We found evidence of conditionally automatic processing in which perceivers tend to process important categories at different times and in different situations.

The response times in gender or age baseline conditions were longer than those in the orthogonal condition. This demonstrates that synchronous variations in both age and gender subcategories can weaken the level of automatic processing of each subcategory. To some extent, these results are consistent with the findings of Vescio, Judd, and Kwan (2004), who used the 'Who Said What Paradigm' and found that the processing of categorization was weaker in the orthogonal condition (Asian female/Asian male/White female/White male) than in the simple conditions (Asian/White or Female/Male). In the baseline condition, the capacity for unconscious attention could, perhaps, accommodate the variations. Nevertheless, in the orthogonal condition, the capacity for unconscious attention could not accommodate all the variations, and this led to a decrease in the encoding level of unrelated clues and a stronger focus on the explicit task.

We also found an age effect on multiple social categorization, in that the younger participants reacted more quickly than the older participants did, and this is consistent with previous literature (Voelkle et al., 2012). This may be due to older individuals' reduced working memory capacity (Finkel, Reynolds, McArdle, & Pedersen, 2007), decreased inhibiting ability of irrelevant stimuli (Gottlob, Fillmore, & Abroms, 2007), or reduced facial processing abilities (Daniel & Bentin, 2012). Furthermore, participants reacted more quickly to the young faces than to the old faces. Along with age and aging come visible facial clues, such as wrinkles and age spots, so the processing of the older facial features requires more cognitive resources than those required to judge the younger facial features. These factors mean that it is more difficult and takes more time for perceivers to judge whether or not there is a mole on aged faces.

We found that perceivers paid more attention to the variation in female age. Specifically, it took the shortest time to judge the young female faces, but the longest time to judge the old female faces. Compared with male or young female faces, perceivers had the most negative attitudes towards the old female faces. Foos and Clark (2011) also found that old female faces were judged the most unattractive compared with other types of faces. This phenomenon may also have something to do with the Chinese male-centered ideology, deeply influenced by the Confucian culture (Jiang, 2009) in which the role of women is to reproduce. Since the age of women represents the level of health and fertility, people pay much more attention to female age than they do to male age (Lau, 2011).

Although our results in this study suggest that synchronous variations in both age and gender subcategories can weaken the other subcategory's level of automatic processing, this does not mean that variations in the other subcategories would afford the same results, which may limit the generalizability of our conclusions. As primordial social categories, there is no doubt that age and gender categories have great theoretical value. However, there are subtle differences between primordial social categories and acquired social categories (e.g., occupation and political party affiliation). Thus, future researchers may wish to investigate acquired social categories in order to provide deeper understanding of social categorization.


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Shanghai Normal University

Pei Wang, Qin Zhang, and Yan-Hong Zhang, Department of Psychology, Shanghai Normal University.

Correspondence concerning this article should be addressed to: Pei Wang, Department of Psychology, Shanghai Normal University, 100 Guilin Road, Xuhui District, Shanghai 200234, People's Republic of China. Email:
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Author:Wang, Pei; Zhang, Qin; Zhang, Yan-Hong
Publication:Social Behavior and Personality: An International Journal
Article Type:Report
Geographic Code:9CHIN
Date:Apr 1, 2015
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