Lecture 18 - Cultural Variation in Stereotyping etc Flashcards

1
Q

Definitions

A

Stereotypes: often-biased heuristics used to make inferences about others’ minds based on cultural beliefs about their identity

Prejudice: attitudinal preferences for some individuals over other
individuals based on cultural beliefs about their identity

Discrimination: behavioral preferences for some individuals over other individuals based on cultural beliefs about their identity

Person perception: the various mental processes used to form first impressions of others

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2
Q

History of prejudice research in psychology

A

The Nature of Prejudice

Seminal book in the study of intergroup conflict and prejudice (Allport, 1954)

Large discussion of various themes

\What is an ingroup?

How is prejudice acquired?

Does contact with outgroup members reduce prejudice?

How do personality and religious belief relate to prejudice?

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3
Q

Shift toward two-dimensional models

A

Not new, but gained
prominence:

Stereotype content model
(Fiske, Cuddy, Glick, & Xu,
2002)

Valence-dominance model of face perception (Oosterhof & Todorov, 2008)

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4
Q

Stereotype Content Model

A

Organizes stereotype onto two axes

Warmth: tolerant, warm,
good natured, sincere

Competence: competent,
confident, independent,
competitive, intelligent

Warmth predicts “If 
members of this group get 
special breaks, this is likely 
to make things more 
difficult for people like me”

Competence predicts “How
well educated?” and “How
economically successful?

They looked at the clusters in the axes and designed words that suited them

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5
Q

Stereotype Content Model

Associated stereotypes

(4)

A

Low competence, low warmth
=Contemptuous (disgust/anger)
e.g. homeless

High warmth/low competence
Paternalistic = sympathy/pity
e.g. elderly/homeless

High competence/low warmth
Envious = jealousy
e.g. rich, Jews

High competence/high warmth
Admiration = pride
e.g. Christians Whites

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6
Q

Valence-Dominance Model of Face Perception

A

Based on the idea that face
perception has a functional
basis

Humans have adaptations to
guess other people’s
intentions and figure out
whether people are dangerous

Valence/trustworthiness and
dominance judgments of faces
emerge from these functions

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7
Q

Why two dimensions?

A

It is parsimonious and simple to work with. Might not be accurate

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8
Q

Warmth = Sociability + Morality

A

Study on what makes people warm

Ptps asked:

“Imagine that you have a 30-year-old daughter who brings home a new boyfriend she is quite serious about. In one case, your daughter’s new boyfriend is warm, charming, and charismatic, but he also gives the impression of being dishonest and untrustworthy.
In another case, he is aloof, quiet, and introverted, but appears to be honest and trustworthy.

In which of these two cases do you expect you would form a more positive impression of your daughter’s suitor?”

There is an effect of being sociable that makes people warm

There is a much larger effect of being moral

Even being unsociable, moral people are viewed as more favorable

Illustrates the construct “warmth” has more parts to it

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9
Q

Valence-Dominance-Attractiveness

A

Analysis shows there are 3 parts to facial judgement, not just valence dominance

Valence/Trustworthiness: ~35%
Youthful-Attractiveness: ~20%
Dominance: ~17%

and each account for a part of the variance

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10
Q

Are stereotypes really universal

Basics

A

Most research done on WEIRD ptps

Western
Educated
Industrialized
Rich
Democratic

But this is only 10-15% of the world

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11
Q

Are stereotypes really universal

correlation between warmth and competence

A

In the USA these two things are orthogonal

In Denmark, there is a moderate correlation

In Pakistan they are strongly correlated

Research shows the number of factors varies across the world

The two factor model only was the best fit in the original study

Three factors was the best fit for most places

Some showed four

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12
Q

Takeaways for number of factor models

A

Two-dimensional models of stereotyping parsimonious and intuitive

Sometimes, two dimensions not accurate or sufficient

Also not as “universal” as authors originally claimed

“Not universal” versus

“universal” is not a binary choice, but a spectrum

New focus: why do cultures vary? Shared characteristics?

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13
Q

Intersectionality in stops by police in the USA

A

Black men were disproportionately stopped

Just saying black ppl not enough, need to see the intersection of race and sex

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14
Q

The intersectional lense can be used to

A

make better theories by adding nuance to ideas

has expanded from race/class/gender to many other areas

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15
Q

What does an intersectional lens allow us to do

A
  1. REVEAL intersectional stereotypes
  2. REVISE psychological constructs to add nuance
    Are femininity and masculinity two ends of one dimension or two distinct dimensions?
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16
Q

Does being tall impact first impressions differently for Black versus White men?

A

Being tall though of as good

Is it always?

Check records of stops in the USA. Use drivers license to check height.

No. If you are a black man, you are more threatening the taller you are and police will stop you more.

If you are a white man it is a good thing

Study 2 - Manipulating grace and height

Photograph of white and black men

Looking straight ahead 
Looking down (makes look tall)

Black men in look down taller condition were perceived as more threatening than in look ahead condition

In terms of competence, no difference for blacks, look down (taller) white men were more competent

Replication with Text Manipulations

Use photos with a vignette:

Imagine meeting this man.
As you approach each other, you can see that he is quite [tall/short].

As you move toward each other, he looks [down/up] at you; he’s very [tall/short].

As you walk toward each other, you notice that he is a lot [taller/shorter] than you.

As you near each other, you realize that he is much [taller/shorter] than you.

Find the same thing as before

17
Q

Is there a masculine-feminine spectrum or is it two discreet characteristics (that can both be present at once)

A

597 neutrally
-posed faces, USA
Subjective coding for: feminine, masculine, attractive, dominant,
trustworthy, threatening

264 neutrally
-posed faces, Turkey
Subjective coding for: feminine, masculine, attractive, dominant,
trustworthy

Masculinity of face accounts for 50%

Femininity accounts for 30% ADDITIONALLY

SO they are distinct because each adds info independently

If you add “androgenous” you get even more

For face perception, better to treat them as separate things