JUDGING THE BOOK BY ITS COVER: A STUDY ON NAÏVE FACIAL INFERENCES OF LEADERSHIP TRAITS AND HORMONES

BY ALLISON K. MURRAY

BACKGROUNDResearch has demonstrated that our rapid judgments of human faces can be predictive of a number of objective outcomes – from election results, to sexual orientation, to the personal gains of Fortune 500 CEOs. Ballew and Todorov (2007) found that first

impressions of competence accurately predicted outcomes for gubernatorial elections.

KEY FINDINGS• Subjective judgments correlate with objective outcome

measures 1,2,3,4

• “Snap” judgments can accurately detect even the most implicit or subtle traits – length of exposure does not improve accuracy in these judgments 3,4,6

• Instructing to deliberate and reflect on a decision before making it actually reduces accuracy 3,6

• There are differences in how people judge faces of the opposite sex and the same sex 2,5

1 Rule, N. O., & Ambady, N. (2008). The face of success: Inferences from chief executive officers’ appearance predict company profits. Psychological Science, 19(2): 109-111. 2 Rule, N. O., & Ambady, N. (2009). She’s got the look: Inferences from female chief executive officers’ faces predict their success. Sex Roles, 61: 644-652. 3 Rule, N. O., Ambady, N., & Hallett, K. C. (2009). Female sexual orientation is perceived accurately, rapidly, and automatically from the face and its features. Journal of Experimental Social Psychology, 45: 1245-1251. 4

Todorov, A., Mandisodza, V. F., Goren, A., & Hall, C. C. (2005). Inferences of competence from faces predict election outcomes. Science, 308: 1623-1626. 5 Chiao, J. Y., Bowman, N. E., & Gill, H. (2008). The political gender gap: Gender bias in facial inferences that predict voting behavior. PLoS ONE, 3(10): e3666. 6 Ballew, C. C., & Todorov, A. (2007). Predicting political elections from rapid and unreflective face judgments. PNAS, 104(46): 17948-17953.

QUESTIONS & PROJECT DESCRIPTION

FIRST, my project looked at the interaction between a perceiver’s sex and the target’s sex in a trait-rating task.

SECOND, my project assessed whether or not perceivers can accurately infer a target’s levels of cortisol and testosterone from a first impression of their face.

This study contributes a new area of insight into whether or not naïve facial inferences are predictive of a person’s

hormone levels, an objective biological measure.

HYPOTHESES

1. There is an interaction between the sex of the perceiver and the sex of the target in the perceivers’ judgments of leadership traits. Male and female perceivers will differ in their average judgments of either male or female targets on any given trait.

2. There is a significant correlation between naïve perceivers’ judgments of targets’ “masculinity” and “stress” and the targets’ actual hormonal baselines.

METHODS

Participants

• Recruited from the UO Human Subjects Pool or volunteered

• Received 1-1.5 class credits for participating

• Total participants = 46 (female = 33, male = 13)

• Participants were not selected for based on any other criteria

Stimuli

• Photos used in the rating task were taken in a prior experiment

• These past participants gave consent to have their images used in future research

• 83 target faces (41 females, 42 males)

• Photos are standardized in size, cropped, and converted to grey scale

METHODS cont’d.

Procedures

• Questionnaires: a standard demographics survey, the Big Five Inventory (John et al., 1991), the Psychology Research Form-Dominance Scale (Jackson, 1967), the Social Dominance Orientation Scale (Sidanius & Pratto, 2001), and the Positive and Negative Affect Schedule (Crawford & Henry, 2004).

• Rating Task: Each participant was randomly assigned to an either all-female or all-male rating task.

• In the task, they were presented with either all the female facial images (n = 41) or all the male facial images (n = 42) across several dimensions of rating.

• The faces were randomized within each trait, and the order of traits presented was also randomized.

THE RATING TASK

Participants rated either all-male or all-female target faces on 8 dimensions:

Personality Traits• Leadership• Competence• Dominance• Facial Maturity• Likeability• Trustworthiness

Hormones• Masculinity*• Stress**

* Testosterone was judged by asking participants to rate the target faces for “masculinity” – the most prevalent effect. ** Cortisol was judged by asking about “stress”

EXAMPLE INSTRUCTIONAL SLIDE

In the next section of the experiment, you will see a series of faces. Please rate each

face on a scale from 1 to 7 for how TRUSTWORTHY you perceive that face to

be. On this scale, 1 = “Not At All Trustworthy,” and 7 = “Very Trustworthy.”

Please try to answer as quickly as you can!

Press SPACE when you’re ready to begin.

EXAMPLE FACE-RATING SLIDE

1 - - - 3 - - - 5 - - - 7

Not at all Very

FACIAL STIMULI

The target facial images used in this study represented a wide range of affective expression:

RESULTS: Perceiver x Target Sex Differences

1. Ratings for each target face on each of the 8 dimensions were averaged across all participants – each face then had 8 mean scores associated with it.

2. Male and female perceiver ratings were separately averaged for each target face on each of the 8 dimensions – now each face had 16 mean scores associated with it.

3. These scores were submitted to a within-subjects repeated measures ANOVA:

1. IV = perceiver’s sex

2. DV1 = male aggregate ratings

3. DV2 = female aggregate ratings

RESULTS cont’d We found a significant interaction between perceiver sex and target sex for ratings of likeability [p = .003], facial maturity [p < .001], and masculinity [p = .012]:

LIKEABILITY

• Male perceivers rated female faces as significantly more likeable than females rated those same faces.

• There was also a difference between male perceivers’ ratings of female faces and their much lower ratings of male faces.

FACIAL MATURITY

• Female perceivers rated female faces as significantly less mature than male faces.

• They also rated male faces as significantly more mature than male perceivers rated those same faces.

MASCULINITY

• Male perceivers rated male faces as significantly less masculine than female perceivers rated those same faces.

• Male perceivers also rated female faces as significantly more masculine than they rated male faces.

RESULTS: Hormone Correlations

1. We factored in whether or not target faces were smiling in their photos.

2. Each target’s basal testosterone and cortisol scores were standardized and positively converted to create a T/C ratio for each target.

3. These ratios along with the mean ratings for each face on each of the 8 dimensions (collapsed across sex) were then submitted to a correlation test.

RESULTS cont’d

The ratio of testosterone over cortisol (T/C) in males was significantly correlated to perceptions of trustworthiness [r = .34], likeability [r = .37], and stress [r = -.28]. The ratio was also correlated to more smiling [p < .05].

Men with high testosterone and low cortisol were more likely to be smiling in

their photos.

DISCUSSION: Sex Differences

• Male perceivers’ ratings of other male faces as less masculine than female perceivers’ ratings could indicate a same-sex competition effect.

• Female perceivers’ ratings of female faces as significantly less facially mature than male faces might be a product of the relatively young sample.

• The difference in ratings of likeability – with female faces rated as significantly more likeable by male perceivers – might be due to females expressing more affect (e.g. smiling) and males being more attuned to and influenced by this opposite-sex affect.

DISCUSSION: Hormones

• The T/C ratio was associated with male targets’ smiling. They were rated as significantly more trustworthy, more likeable, and less stressed.

• Males with high testosterone and low cortisol – the hormonal profile that has been linked to social dominance – were more likely to smile in their photos.

• These smiling faces were then rated higher on trustworthiness and likeability, and lower on stress.

LIMITATIONS

• Low sample size of perceivers: to study the sex interaction, each condition would need at least 30 subjects.

• Lack of control over facial stimuli

FUTURE STEPS

• Future work might focus on the degree to which facial affect influences perceivers’ ratings of faces across these traits.

• “Valence,” as Todorov and Engell (2008) found, is key in the amygdala’s varied responses to faces.

• Along these lines, assessing the faces in the dataset for attractiveness might help explain the significant differences between male and female perceivers’ ratings.

THANK YOU!