Children's Understanding of Villains and Evil Craig E. Smith1, Felix Warneken2

, Susan Gelman1, & Henry Wellman1

Introduction

1University of Michigan, 2Harvard University

Results

Results

Method

When reasoning about personality traits, young children often express views that are quite positive, sometimes overly so (Boseovski, 2010). This positivity bias has been observed even when young children are led to expect the worst in others (e.g., Boseovski & Lee, 2008; Rholes and Ruble, 1986). However, young children are captivated by characters with negative traits. Taking advantage of this interest in villains, we explored when a firm understanding of evil emerges in development.

Pilot Testing for Fictional Character Selection • Children (n = 123) rated familiarity with 27 fictional

heroes and villains. • Heroes Selected for Main Study:

• Woody (Toy Story) • Spiderman • Merida (Brave) • Jessie (Toy Story)

• Villains Selected for Main Study : • Captain Hook (Peter Pan) • Darth Maul (Star Wars) • Mother Gothel (Tangled) • Ursula (Little Mermaid)

• Gender of characters matched to participant gender Main Study Participants. • Study run at Hands-On Museum in Ann Arbor, MI • Range of ethnic and socio-economic backgrounds;

predominantly White, middle-class. • Sample included:

• 157 children aged 3-12 years (M = 7.53, SD = 2.06) • 93 girls, 64 boys

Procedure. Children randomly assigned to answer questions about one of following character types:

• Familiar Villain (e.g., Captain Hook, Ursula) • Novel Villain (visually matched to familiar villains) • Familiar Hero (e.g., Spiderman, Merida) • Novel Hero (visually matched to familiar heroes)

Conclusions

Method

Figure 1. Familiar and novel villains: Will character throw rock at stranger, or throw it to other side?

Figure 2. Familiar and novel villains: Will character push to get computer, or ask for a turn?

Young children exhibit a positivity bias when thinking about traits. Given this, we ask what

young children understand about evil, and how this changes with development.

Gender and specific story character not sig. factors. Evil Scale. Scoring of items listed above: 0 = less evil prediction, 1 = more evil prediction. Eight-point scale (range: 0-7) computed using the seven items. Scale analyzed with multiple regression (Table 1 and Figure 3).

Figure 3. The association between attribution of evil and age as a function of character type

Age-Related Differences. Analyses conducted to identify items on which there were age differences. Some key differences: Villain Characters -- Older children more likely to:

• predict violent revenge, p = .002 • predict lack of sharing, p = .02 • predict lack of remorse following use of aggression to obtain

desired object (i.e., a ‘happy victimizer’ reaction), p = .10 • predict lack of comforting behavior, p = .08

Hero Characters -- Younger children more likely to:

• predict violent revenge, p = .002 • predict no guilt (i.e., a ‘happy victimizer’ reaction), p = .08

Soft Spot? Villains viewed as capable of being kind to a pet (e.g., sharing with pet snake, Figure 4).

• Although young children show positivity bias when reasoning about traits, they do have some grasp of sinister side of trait spectrum

• E.g., Readily predict sadistic and instrumental aggression, lack of helping and comforting, etc.

• Younger children also expect some negativity in heroes (e.g., happy victimizer response, violent revenge)

• By middle childhood, more systematic understanding of evil and goodness is in place

Children made binary predictions about evil behaviors: -sadistic aggression -violent revenge -instrumental agg. -lack of remorse

Children also made predictions about prosocial acts: -sharing -comforting -helping

0

1

2

3

4

5

6

7

4 5 6 7 8 9 10 11 12

Mea

n Sc

ore

on E

vil S

cale

Age

Villain Hero

Table 1. Regression analysis of children's attributions of evil

Independent Variables B (SE) β

Child Age -.18 (.087) -.14*

Character Type (Villain vs. Hero) 1.142 (.94) .22

Character Novelty (Existing vs. Novel) .31 (.25) .06

Age × Character Type .40 (.12) .62***

Note. R2 for model = .81. Character type: villains = 1, heroes = 0. Character novelty: existing characters = 1, novel characters = 0. *p < .05. **p < .01. ***p < .001.

Young children did anticipate evil in villains. This expectancy became stronger with increasing age. Heroes were firmly viewed as non-evil, but this view became even stronger with increasing age.

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3-5yrs 6-7yrs 8-12yrs 3-5yrs 6-7yrs 8-12yrs

Villain Hero

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f Foo

d Ite

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Shar

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f 4)

Stranger Pet Snake Other Villain/Hero

even split

Figure 4. Mean number of food items children predicted characters would share as a function of character type, recipient type, and age group

Recipient: