When the Party Decides: The Effects of Facial Competence and Dominance on Internal Nominations of Political Candidates



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S.I.1. Candidate sex and facial competence


Below we report the full model when further testing if candidate sex moderates the effect of facial competence on ballot position (cf. footnote 6 in main text). As can be seen in Table S.I.1, the interaction between candidate sex and facial competence is insignificant (b = -0.74, p = 0.812), which means that facial competence exerts the same effect on ballot position for female and male candidates.
Table S.I.1: Prediction of candidate ballot position from facial traits. Model 1 reports the potential interaction between facial competence and candidate gender. Unstandardized logit regression coefficients with standard errors in parentheses.




Model 1




top20 percent

Incumbency

2.52***




(0.36)

Municipality

  • Frederikshavn

-0.40





(0.34)

  • Mariager Fjord

-0.59**




(0.18)

Perceived age

  • 30 – 60 years

-0.08





(1.01)

  • above 60 years

-0.36




(0.86)

Sex

  • Female

0.64





(2.09)

Facial Competence

2.60***




(0.53)

Ideology

  • Conservative

-1.25





(0.76)

Facial Comp. X Sex

-0.74





(3.10)

Facial Dominance

-5.07**




(1.71)

Facial Domi. X Ideology

5.79**






(1.68)

Constant

-2.56**




(0.97)

N

257

Pseudo R2

0.253

Note: p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001

S.I.2. Candidate sex and facial dominance


Below we report the full models when testing if candidate sex moderates the effect of facial dominance on ballot position (cf. footnote 7 in main text). As can be seen in Table S.I.2 below, neither the interaction between candidate sex and facial dominance in Model 1 (b = 0.25, p = 0.918), nor the three-way interaction between facial dominance, ideology and candidate sex in Model 2 is significant (b = 6.50, p = 0.255). That is, candidate sex does not moderate the effect of facial dominance nor does it further moderate the interactive relationship between facial dominance and ideology.

Table S.I.2: Prediction of candidate ballot position from facial traits. Model 1 reports the potential interaction between facial dominance and candidate sex, while model 2 tests the potential three-way interaction between facial dominance, ideology and candidate sex. Unstandardized logit regression coefficients with standard errors in parentheses.




Model 1

Model 2




top20 percent

top20 percent

Incumbency

2.58***

2.58***




(0.34)

(0.41)

Municipality

  • Frederikshavn

-0.42

-0.39





(0.34)

(0.39)

  • Mariager Fjord

-0.65***

-0.62***




(0.17)

(0.17)

Perceived age

  • 30 – 60 years

-0.15

0.01





(1.00)

(1.08)

  • above 60 years

-0.60

-0.28




(0.86)

(0.96)

Sex

  • Female

0.18

0.72





(0.73)

(1.74)

Facial Competence

2.37**

2.51**




(0.71)

(0.74)

Ideology

  • Conservative

0.77*


-1.10





(0.39)

(1.23)

Facial Dominance

-1.66

-4.76




(1.22)

(2.84)

Facial Domi. X Ideology

  • Facial Domi. X Conservative

-

4.99





(-)

(2.86)

Facial Domi. X Sex

0.25


(2.46)

-4.33


(5.88)

Ideology X Sex







  • Conservative X Female

-

(-)


-1.05

(1.56)


Facial Domi. X Ideology X Sex

  • Facial Domi. X Cons. X Female

-



6.50




(-)

(5.71)

Constant

-3.41***

-2.63*




(0.71)

(1.29)

N

257

257

Pseudo R2

0.228

0.260

Note: p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
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