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Lecture Outline

Lecture Outline. Extra Credit experiment Stereotypes defined Diagnostic ratio revisited Origins of stereotypes Models of stereotype change/maintenance Prejudice defined. Ashmore & Del Boca (1981) A stereotypes is…... “A set of beliefs about the personal attributes of a group of people”.

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Lecture Outline

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  1. Lecture Outline • Extra Credit experiment • Stereotypes defined • Diagnostic ratio revisited • Origins of stereotypes • Models of stereotype change/maintenance • Prejudice defined

  2. Ashmore & Del Boca (1981) A stereotypes is…... “A set of beliefs about the personal attributes of a group of people”

  3. Ashmore & Del Boca (1981) Limitation: Many attributes are perceived as typical of a group and yet are not part of people’s stereotypes

  4. Stereotypes include attributes that are perceived as: TYPICAL and DISTINGUISH BETWEEN GROUPS

  5. Diagnostic Ratio DR = % of group (with attribute) % of reference (with attribute)

  6. Diagnostic Ratio When DR = 1 (or close to 1), attribute does not distinguish between groups • attribute not part of stereotype

  7. Diagnostic Ratio When DR substantially > than 1 • attribute distinguishes between groups • attribute is stereotypic of group

  8. Diagnostic Ratio When DR substantially < than 1 • attribute distinguishes between groups • attribute is counterstereotypic of group

  9. McCauley & Stitt (1978) Purpose: 1. Show utility of DR 2. Measure (in)accuracy of stereotype about African Americans

  10. McCauley & Stitt (1978) • Sampled five groups • Created DR’s based on perceptions of African Americans and Americans • Created criterion DR’s based on census information

  11. Results: McCauley & Stitt (1978) Attribute Criteria HS College Union Choir SW HS .65(.68) (.73) (.67) (.68) (.60) Illegitimate 3.10(1.80) (1.70) (2.10) (1.90) (2.30) Unemployed 1.90 (1.90) (1.60) (1.80) (2.60) (2.30) Victims 1.50 .83 (1.80) (2.00) 1.50 2.30 Welfare 4.60 (2.30) (1.90) (1.60) (1.80)1.40 Kids 1.90 (1.60) (1.40)1.60(1.30) (1.30) Female head 2.80 (1.70) (1.90) (1.70) (1.50) (1.70) (Green) DR’s: different from 1 (p < .05); n = 30 Black DR’s not different from 1 (p > .05); n = 5 Underlined DR’s = different from criteria (p < .05); n = 16 76

  12. Results: McCauley & Stitt (1978) Attribute Criteria HS College Union Choir SW HS .65(.68) (.73) (.67) (.68) (.60) Illegitimate 3.10(1.80) (1.70) (2.10) (1.90) (2.30) Unemployed 1.90 (1.90) (1.60) (1.80) (2.60) (2.30) Victims 1.50 .83 (1.80) (2.00) 1.50 2.30 Welfare 4.60 (2.30) (1.90) (1.60) (1.80)1.40 Kids 1.90 (1.60) (1.40)1.60(1.30) (1.30) Female head 2.80 (1.70) (1.90) (1.70) (1.50) (1.70) Most DR’s different from one (green): People held stereotype of African Americans 77

  13. Results: McCauley & Stitt (1978) Attribute Criteria HS College Union Choir SW HS .65(.68) (.73) (.67) (.68) (.60) Illegitimate 3.10(1.80) (1.70) (2.10) (1.90) (2.30) Unemployed 1.90 (1.90) (1.60) (1.80) (2.60) (2.30) Victims 1.50 .83 (1.80) (2.00) 1.50 2.30 Welfare 4.60 (2.30) (1.90) (1.60) (1.80)1.40 Kids 1.90 (1.60) (1.40)1.60(1.30) (1.30) Female head 2.80 (1.70) (1.90) (1.70) (1.50) (1.70) Some DR’s different from criteria [underlined]. Other DR’s not different from criteria [not underlined]: People’s stereotypes were both inaccurate [underlined] and accurate [not underlined] 78

  14. Results: McCauley & Stitt (1978) Attribute Criteria HS College Union Choir SW HS .65(.68) (.73) (.67) (.68) (.60) Illegitimate 3.10(1.80) (1.70) (2.10) (1.90) (2.30) Unemployed 1.90 (1.90) (1.60) (1.80) (2.60) (2.30) Victims 1.50 .83 (1.80) (2.00) 1.50 2.30 Welfare 4.60 (2.30) (1.90) (1.60) (1.80)1.40 Kids 1.90 (1.60) (1.40)1.60(1.30) (1.30) Female head 2.80 (1.70) (1.90) (1.70) (1.50) (1.70) When DR’s indicated inaccurate stereotype [underlined], difference was smaller than criteria: People’s stereotypes underestimated real differences. They did not exaggerate real differences 79

  15. McCauley & Stitt (1978): Summary • People endorsed a stereotype of AA • most DR’s different than 1 • AA stereotype was accurate & inaccurate • some DR’s different from criteria (inaccurate) • other DR’s not different from criteria (accurate) • AA stereotype underestimated real difference • when DR different from criteria, it was smaller

  16. Origin of Stereotypes:Where do they come from? • Socio-cultural perspective • Kernel of Truth hypothesis • Illusory correlations

  17. Socio-Cultural Perspective • Premise: Individuals are socialized into a particular culture (e.g., media or significant others)

  18. Socio-Cultural Perspective 1. People are born into a culture 2. People are rewarded/punished for their beliefs, values, behaviors 3. People act in accord with norms 4. People internalize norms 5. Internalization perpetuates the norms

  19. Socio-Cultural Perspective Two versions of socio-cultural view • Structuralist-Functionalist • Conflict theory

  20. Structuralist-Functionalist Version • A single culture accepted throughout a society i.e., individuals in a society are similar in their beliefs, values and behaviors

  21. Structuralist-Functionalist Version Function of stereotypes: • stereotypes communicate expected behavior • stereotypes communicate how different people should be treated

  22. Structuralist-Functionalist Version More evident in more homogeneous and collectivist societies

  23. Conflict Theory Version • Multiple subcultures within society • People accept norms of their subculture

  24. Conflict Theory Version • People within a subculture are similar in their beliefs, values, behaviors • People in different subcultures are different in their beliefs, values, behaviors • The more different two subcultures, the greater the conflict in their beliefs, values, behaviors

  25. Conflict Theory Version Function of stereotypes: • stereotypes justify prejudice • incompetence justifies lower pay • laziness justifies poverty

  26. Conflict Theory Version More evident in more heterogeneous societies

  27. Kernel of Truth Hypothesis • Premise: Stereotypes are exaggerations that exist in some measure in a group

  28. Kernel of Truth Hypothesis 1. The larger a real difference between groups, the more likely the attribute will be in the stereotype • Example: Circumscribing and non-circumscribing tribes

  29. Kernel of Truth Hypothesis 2. Stereotypes become more accurate as contact between groups increases • Example: women/men v.s. African Americans/Whites

  30. Kernel of Truth Hypothesis 3. Behaviors punished in one group, but not in another, tend to be in a stereotype • Example: nudity and bathroom practices

  31. Kernel of Truth Hypothesis 4. Similar behaviors that groups perform in different situations tend to be in stereotypes, but connote different valences. Example……...

  32. We are loyal. We are brave and progressive. We are thrifty. They are clannish. They are aggressive and expansionistic. They are cheap. Kernel of Truth Hypothesis

  33. Kernel of Truth Cautionary Statements • Perceived differences are not veridical • Perceived differences are exaggerated • Perceived differences reflect social factors, not genetic differences

  34. Illusory Correlations • Definition: People overestimate how strongly two things are related (e.g., arthritis pain and changes in the weather)

  35. Illusory correlations & stereotype formation • People associate a group with an attribute (African Americans & crime) • Cognitive biases “corroborate” the perceived association • confirmation biases in hypothesis testing • remember consistent information better

  36. Illusory Correlation • People most susceptible to illusory correlations when: • group is relatively small • attribute is rare in population

  37. Illusory CorrelationExample • African Americans are a minority in the US. Whites are the majority • Being a media superstar is rare • Illusory correlation likely…… • More AA (small group) superstars (rare event) than White (large group) superstars (rare event)

  38. Illusory Correlation Negative behavior more rare than positive behavior Implication: • Negative behavior by minority more memorable and salient than same behavior by majority • Negative behavior becomes part of stereotype of minority

  39. Stereotype Change Consensual stereotypes change over time, across individuals. Very little known about stereotype change over time, within individuals (see Weber & Crocker, 1983, for an exception)

  40. Models of Stereotype Change • Bookkeeping Model • Conversion Model • Subtyping Model Focus on stereotype-inconsistent information

  41. Bookkeeping Model • Stereotype change is incremental • Each instance of inconsistent information modifies the stereotype • Single instance = small change • Accumulation = large change

  42. Bookkeeping Model • Implication: Stereotype change will be similar regardless of whether inconsistent information is concentrated or dispersed. Amount (not dispersion) matters.

  43. Conversion Model • Stereotype change is dramatic • Stereotypes change in response to large and salient inconsistent info. • Stereotypes remain unchanged by minor inconsistent information

  44. Conversion Model • Implication: Stereotype change will be greater when inconsistent information is concentrated v.s. dispersed

  45. Subtyping Model • Stereotypes hierarchically structured • Rare, inconsistent instances lead to creation of subtypes. • Instances regarded as “exceptions” • Stereotype protected from change • Common, inconsistent instances result in stereotype change

  46. Subtyping Model • Implication: Stereotype change will be greater when inconsistent information is dispersed v.s. concentrated

  47. Weber & Crocker (1983) Purpose: • Tested the three models of stereotype change

  48. Weber & Crocker (1983) Procedure: • Given information about corporate lawyers • Rated each lawyer on stereotypic traits

  49. Weber & Crocker (1983) Manipulations: • Dispersion of Inconsistent info: • Dispersed across all members • Concentrated in 1/3 of members • Group size: • 6 members v.s. 30 members • Amount of inconsistent info higher in larger group

  50. Weber & Crocker (1983) Predictions Dispersion has no effect on stereotype change, but amount does (bookkeeping) Stereotype change greater when inconsistent info concentrated (conversion) Stereotype change greater when when inconsistent info dispersed (subtyping)

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