1. JUDGING THE
BOOK BY ITS
COVER: A STUDY ON
NAÏVE FACIAL INFERENCES OF
LEADERSHIP TRAITS AND
HORMONES
BY ALLISON K. MURRAY

2. BACKGROUND
Research 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.

3. 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.

4. 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.

5. 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.

6. 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

7. 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.

8. 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”

9. 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.

10. EXAMPLE FACE-
RATING SLIDE
1 - - - 3 - - - 5 - - - 7
Not at all Very

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

12. 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

13. 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]:

14. 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.

15. 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.

16. 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.

17. 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.

18. 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.

19. 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.

20. 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.

21. 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

22. 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.

23. THANK YOU!