Stereotypes vs. Prejudice vs. Discrimination

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In this video, we'll differentiate

between stereotypes, prejudice,
and discrimination;

and we'll discuss several important
social psychological concepts

and hypotheses related to each,

including what causes them
to arise in the first place.

Let's go over a bit of
terminology to kick things off.

A stereotype is a belief
(which can be positive or negative )

about the characteristics
of members of a group

that is applied generally
to most members of that group.

Believing that Asians are good
at math, for example, is positive;

it's not necessarily derogatory,

but it's nonetheless a stereotype
that you have about Asians.

Now, stereotypes (these beliefs) can
lead to prejudice, which in contrast,

can only ever be negative.

Prejudice involves drawing
negative conclusions about

a person, a group of people,

or a situation prior to
evaluating the evidence.

These baseless conclusions are typically

the result of those stereotypes
that you hold about that group.

Also, in contrast to stereotypes,

prejudice involves emotion;
it’s an attitude.

Being prejudiced against a person
or a group of people involves

feeling negatively toward them.

Now, because of these negative emotions

and these negative conclusions
that you're coming to,

prejudice often leads to discrimination,

which is negative behavior
towards members of an out-group.

And by the way, an out-group is a group

that we don't belong to or one that we
view as fundamentally different from us;

whereas an in-group, in contrast,

refers to a group that we DO identify
with or see ourselves as belonging to.

So I might be using that
terminology quite a bit–

important to know.

So just to summarize,

stereotypes are beliefs,
prejudice is an attitude,

and discrimination is a behavior.

Let's go over an example
that puts all of this together.

Let's say, for example, that you
believe older adults are incompetent,

and that's a stereotype that
you have about older adults.

(And I'll note that I'm not endorsing
this stereotype or any other stereotype

that I use as an example in this video,

but we have to have some kind
of an example to work with here.)

So let's say you work at,
I don't know, a tech company

and you're looking to hire an assistant.

If an elderly gentleman applies,

you might walk into that interview
with the gentleman,

assuming he won't be a good fit
or that he'd be difficult to train.

Now, we would call this
premature conclusion;

this negative attitude toward
this gentleman [is] prejudice.

Finally, you may decide not
to hire the gentleman at all

because of your stereotype,
because of your prejudice.

In this case, the behavior
of not hiring him

would be discrimination.

Now, stereotypes and prejudice
can be either explicit

(meaning, we're consciously
aware of having this bias)

or implicit (meaning, it's there,
but we aren't aware of it).

Research shows that explicit prejudice
is in decline, which is encouraging;

however, implicit prejudice
really isn't much.

That is, people report being
very anti-bias nowadays,

but their behavior still
tells us a different story.

Let's take a look at a few
examples to illustrate.

Starting with the realm of gender,
we can look to some of my own data.

In one study, I searched through

the language used by students
evaluating their teachers

in over 14 million reviews posted to
a popular instructor evaluation website,

RateMyProfessors.com,
which you've perhaps used in the past.

I was specifically interested in
stereotypes about intelligence,

so I searched through uses of
the words “genius” and “brilliant.”

So let's take a look at the results.
There's a lot of information here.

Let me help you interpret these graphs.

These are graphs for uses of

the words “genius” on the left
and “brilliant” on the right.

The x-axis on both of these graphs

represents uses per millions
of words of text,

which might sound a little
complicated, but really isn't.

There's a ton of text here,

so to keep the numbers on the
x-axis from being enormous

and just visually unappealing,

I used this uses per millions of words of text,
but the interpretation is basically the same.

The further to the right
you go on the x-axis

(the higher the number),
the more this word was used.

So that's how you can interpret that.

The y-axis here displays all of the
different fields such as philosophy,

music, mathematics, psychology;

so you can look for your own field

or just pause the video and look through
them in general, if you're curious,

And fields that are higher up
on the y-axis were the ones

in which the words were used the most often.

The blue dots here on the slide
represent reviews of male professors,

whereas the orange dots represent
reviews of female professors.

Before I give you the punch line,
what do you notice here?

Well, what I found is that every
field for which we have data,

students describe their male
professors as genius and brilliant

significantly more often than
they do their female professors.

And in no field was this effect reversed,

even for fields where women
were the statistical majority.

And this points to a stereotype
in favor of men's intelligence

and against women's intelligence.

You might be wondering:

Does this reflect an overall
bias against women,

or is the stereotype specific
to intellectual ability?

Well, I was curious about this as well,

but if you look at the data for
the terms “excellent” and “amazing,”

the gender bias goes away entirely.

It appears that students believe

that their female professors
can be excellent and amazing,

but they believe it's mainly the male
professors who are genius and brilliant.

Again, this is evidence of implicit bias

because students are likely

not consciously aware
of this discrepancy.

They're simply going on line
to review their professors

and they're not giving their
stereotypes any thought.

So explicitly, students would
likely say they don't hold a bias,

yet implicitly, they respond in this way.

This is a common theme

in modern research on stereotypes,
prejudice, and discrimination.

Now that's gender.
What about race?

One study found that doctors
were only 60% as likely to suggest

a top-rated diagnostic test
for Black heart patients

than for White heart patients.

There's also evidence to suggest

that White men are offered
greater financial opportunities.

As one example, a study found
that White men were offered

the best deals at used car dealerships.

White men paid $109 on average
less than White women,

$318 less than Black women,

and a whopping $935 less for a
used car on average than Black men.

Now, these are just two examples out
of thousands that I could tell you about,

but again, it's likely the case

that these doctors and car salesmen
aren't EXPLICITLY biased,

but their behavior provides
evidence of IMPLICIT bias.

Okay, so let's finish
with a brief discussion

of what leads to the development and
perpetuation of some of these things

(stereotypes, prejudice,
and discrimination),

starting with stereotypes.

A factor that we've learned about
before is confirmation bias,

the tendency to seek out evidence
that supports our beliefs

and to deny, dismiss, or distort
evidence that contradicts them.

Say, for example that you believe
women to be bad drivers.

If you're out driving for an hour,

you might encounter several bad
drivers, some male, some female.

If you don't have a stereotype
against male drivers, though,

you might not think much of them
when they speed or make dangerous moves.

But the second a female driver
cuts you off, for example,

you feel vindicated as though
you've found additional evidence

or proof for your belief.

And this reinforces your stereotype

even though, in truth, many people are
bad drivers regardless of their gender.

Now, if we used System 2 thinking

(which we've learned
about in a previous video)

to evaluate these kinds of assumptions
and the data that we base them on,

we might realize that those assumptions
are erroneous, but we usually don't.

This is because we are cognitive misers.

That is, we seek to use only
minimal cognitive resources

when explaining the world around us.

Evaluating our stereotypes takes effort,

and because we generally
don't go to more effort

than we deem absolutely necessary,

we don't evaluate or re-evaluate them at all.

Now, what causes prejudice?

First, we have in-group bias,
which refers to the tendency

to favor individuals from within our
group over those from outside our group.

Evidence from developmental
psychology suggests that this bias

is innate, with young infants showing
strong preferences, for example,

for others who share their preferences
(such as their favorite snack)

and infants disliking others who
do not share their preferences

(for example, if the other person shows
that they like a different snack more).

Think of the implications
for racism, sexism, and so on.

Another factor is called
the ultimate attribution error,

which refers to the assumption

that behaviors among
individual members of a group

are due to their internal dispositions.

Out-group members’ flaws
are due to internal factors

such as their personality or their race,
whereas in-group members flaws aren't.

This might sound a lot like
the fundamental attribution error,

which we've learned about before,
but it is a bit different.

Think of the ultimate attribution error

as more of a narrow case of
the fundamental attribution error

applied specifically to attributions

about an individual in relation to
the group to which they belong.

Along similar lines,

out-group homogeneity
refers to the tendency to view

all individuals outside our group
as highly similar to one another.

Here, think of the implications

for identifying a suspect in
a police lineup, for example,

but also consider this bias in relation
to the ultimate attribution error.

It's a very bad combination to assume

that out-group members flaws
are due to inherent factors

such as their personalities or their race,

and to simultaneously assume

that out-group members are all
highly similar to one another.

Finally, scapegoating refers to
the act of blaming an out-group

when the in-group experiences frustration or
is blocked from obtaining some kind of a goal.

People scapegoat because it preserves
a positive self-concept.

If you believe the reason you can't get a job
is because immigrants are taking them all,

well, then you don't have to
come to terms with the reality

that you simply aren't qualified or
competent enough for that line of work.

Now, this list of causes here
is by no means all-inclusive

but should give you a good idea of
the general psychological phenomena

that lead to the formation and
perpetuation of stereotypes,

prejudice, and discrimination. [END]