Stereotyping and Prejudice Flashcards
stereotypes
- schemas applied to groups
- can be race, gender, other groups (ie. Cat lovers)
- Generalizations of how members think or act
- Content can be positive or negative
explicit bias
- Attitudes and beliefs that people endorse
- Measured with self-report scales
- includes positive stereotypes (ex. Asians are good at math -> can still be problematic)
- includes sexism in media (used to be more overt, but still exists today)
- includes hostile and benevolent sexism
- strong social norms against explicit prejudice (especially in its hostile/extreme forms)
hostile vs. benevolent sexism
- hostile: negative (ex. “women seek to gain power by controlling men”)
- benevolent: seemingly-positive (ex. “women should be cherished and protected by men”)
implicit bias
- Automatic, nonconscious
- Often associated with reaction time measures
- When 2 things are more closely associated, it’s easier to group them, and therefore people respond faster (ex. Chocolate/strawberries vs. Chocolate/cars)
- Can exist even in people who don’t endorse stereotypes and prejudice explicitly
measures of implicit bias
- IAT (most widely used measure)
- Shoot/Don’t Shoot task
IAT
Computer association task (Black/White Bad/Good) measuring implicit prejudice
Implicit prejudice = Black/Bad speed minus Black/good speed
critiques of IAT (and responses)
- Order effects? (not really -> counterbalancing used)
- Just shared cultural knowledge/awareness? (no -> predicts individual behaviour -> Ex. People with higher implicit bias (as measured by IAT) less likely to say they would vote for Obama)
Shoot/Don’t Shoot Task
- Photos of young black and white men holding gun or non-threatening objects (ie. Wallet, phone), have to decide whether to shoot or not shoot them
- Most errors: shooting unarmed black men
implicit bias in the workplace
Recruiters who score higher on Anti-Arab implicit bias are less likely to invite a Muslim-Arab person for an interview (explicit bias didn’t predict this)
why is implicit prejudice so persistent?
- Forming associations and creating categories is natural and largely outside our control
- A basic characteristic of human cognition
- We are surrounded by stereotypes
is bias inevitable?
- Dependent on social situation
- College students’ ratings of profs:
- Equal for male/female profs if good grade given
- Female profs harshly criticized if bad grade given, male profs only slightly so…
- KEY POINT: People shift whatever stereotypes they’re using to fit the situation
Parental differential treatment of members of stigmatized groups
- Overweight women less likely to receive support from parents for college education (even when controlling for income, ethnicity, family size, # of kids, etc.)
- But no effect for male students
differential treatment and stereotypes
- Differential treatment can make stereotypes come true (self-fufilling prophecy)
- Because you’re treated in line with a stereotype, you end up fufilling the stereotype
- Others’ expectation about you -> influences their behaviour toward you -> influences your behaviour (you act consistently with their expectations)
- Ex. Parents think fat people are stupid -> don’t help her go to college and get better education -> confirms initial bias
differential treatment study: ugly vs. beautiful girl
- male participants shown fake picture of girl they’ll be talking to (either beautiful or ugly), then talk to her though a headset (don’t actually ever see her)
- Men who saw beautiful picture believed that the “hot” women would have more social skills
- Other students asked to listen to tape of woman speaking (without knowing about the picture stuff) to rate her social skills
- Women who were believed to be “hot” actually were the more socially skilled, because the men who interacted with them treated them in a way that elicited socially skilled behaviour
reducing stereotypes and prejudice
- awareness and genuine desire to change
- harness power of peer pressure
- intergroup contact
awareness and genuine desire to change
- Has to be genuine (internally motivated)
- Being told to suppress stereotypes can backfire
- Little evidence for effectiveness of corporate diversity education
- Can help to focus on feelings
- Ex. Study showed focusing on feelings (vs. Thoughts) while watching a video about discrimination against black people increased desire to interact with black people
power of peer pressure
- Poluck’s field experiment: picked high school students to serve as peer trainers for fellow high school students (influential students from all different ‘cliques’; got intensive training in prejudice & prejudice reduction)
- At end of training, students completed an “unrelated survey” and are invited to sign a petition for gay rights
- Results: peer trainers changed their attitudes in a positive way, friends & peers of peer trainers didn’t change their attitudes, but did change their actions (were more likely to sign the petition)
intergroup contact
- Simple hypothesis: create contact between members of different groups -> reduce prejudice
- Reality: contact between groups only reduces prejudice when it occurs under optimal circumstances:
- Equal status between groups
- Intimate & varied contact so people really get to know each other
- Cooperation to achieve a shared goal
- Institutional support: contact approved by culture/authorities
- Ex. Jigsaw Classroom
Plant et al: IAT and Obama studies
Plant et. Al did IAT studies and saw implicit prejudice against black people decrease when Obama ran for president -> instead of associating black with bad, they now associated it with someone good (ie. Obama)
Nosek and Greenwald math stereotype study: how did they come up with study?
In an earlier IAT studying something else, a negative bias was found towards numbers, whereas a positive one was found towards letters by female participants -> led to this study
Nosek and Greenwald math stereotype study: what did they find?
- Female college students demonstrated implicit negative attitudes towards math and science (which is not demonstrated in explicit self-report measures)
- Even females in math-intensive majors still held more negative attitudes than male counterparts
Nosek and Greenwald math stereotype study: why did they find what they did
- Implicit attitudes are related to group membership (being female), group identity (self = female), and gender stereotypes (math = male)
- Membership in the category “female” strongly related to negative attitudes
- Stronger your identification with “female”, stronger your negative attitudes
- Stereotype of math = male is strong
