Evaluating Others: How Our Beliefs Become Reality

Transcription

1 Evaluating Others: How Our Beliefs Become Reality Business Summer, 2008 Well, we needed the rain.

2 2 Why?

3 Levy & Langer (1994): Beliefs create aging reality? Two Independent Variables: 1. Age: Young (15-30 yrs.) vs. Old (59-91) 2. Culture: Chinese vs. Americans Culture groups matched on education, SES, and age Measure Memory Performance (known for age differences): Pattern recall test (see pattern of dots, asked to redraw from memory) Obtain immediate, intermediate, and delayed recall Photo-association task Photographs of people paired with sentences. Asked to recall pairings of photos with sentences. Measure attitudes towards aging: 3 Multiple measures aggregated into composite.

4 Memory Performance: Chinese American Young Old Attitudes towards aging (range -1.5 to 7.5): Chinese Americans 2.32

5 Levy (1996) Activating Divergent Beliefs about Elderly Prime (or activate): positive vs. negative elderly stereotypes (Americans, only) Subliminally presented with relevant words: Positive guidance, wise, alert, sage, accomplished, learned, improving, advise, creative, enlightened, insightful, astute. Negative Alzheimer s, decline, dependent, senile, misplaces, dementia, dying, forgets, confused, decrepit, incompetent, diseased. Two groups: Young (18-35 yrs.) vs. Old (60+) Memory Performance: Pre-test vs. Post-test Pattern Recall (as before) Photo Association (as before) 5

6 Memory Performance: Change from Pre-test to Post-test 2 Negative (Senile) Positive(Wise) Old Young 6 Declines in cognitive functioning due to age, or age-related stereotypes?

7 Mean SAT Math & Verbal Test Scores, by race/ethnicity: : V / M Asian 508/575 White 529/534 Black 431/426 Why?

8 Steele & Aronson (1995): Stereotype Threat Black and White Stanford Undergraduates take a test: 30 difficult items from old GRE-verbal exams. Believed diagnostic of intellectual ability. Salience of Racial Stereotypes: Salient: Report race/ethnicity at top of test. Not Salient: Do not report 8

9 9 Test Performance:

10 10 Diagnostic vs. Nondiagnostic of Intellectual ability:

11 Similar Results: Men, Women, and Mathematics General empirical findings: Gender differences emerge at the top Difficult tests, representation in academia, professional scientists and mathematicians (not easy tests, H.S. grades) Spencer, Aronson, & Quinn (1999): Men & Women from Univ. of Michigan Completed at least one semester of Calculus, received B. 85th Percentile or better on SAT Math Agreed on a questionnaire that they were 1) good at math, and 2) it is important to me to be good at math. 11

12 Two conditions: All read: As you may know there has been some controversy about whether there are gender differences in math ability. Previous research has sometimes shown gender differences and sometimes shown no gender differences. Yet little of this research has been carried out with women and men who are very good in math. You were selected for this experiment because of your strong background in mathematics. 1. Gender Differences: The test you are taking is known to produce gender differences. 2. NO Gender Differences: The NEXT test you will take is known to produce gender differences. 12

13 Test Performance: 30 Number Solved Correctly Men Women 0 No Gender Gender Diffs. 13 Condition

14 Mixed identities (Shih, Pittinsky, & Ambady, 1999): Asian Women in U.S. Asian Cultural Stereotype Good at Math Female Cultural Stereotype Bad at Math % Answered Correctly Ethnicity Control Gender Report on Test 14 Challenging math problems similar to those on SAT

15 Sense-Making: How Beliefs Make Reality Two Ways: 1. Interpreting Reality: We see what we expect (or want) to see. Related to Confirmation Bias from yesterday. 2. Creating Reality: Self-fulfilling prophecies Our beliefs lead others to behave in ways that erroneously confirm our beliefs, even if those beliefs are completely false. 15

16 Backmasking : Judas Priest, Beyond Realms 1990 court trial Queen, and Another One Bites the Dust: Listen carefully for, It s fun to smoke marijuana 18

17 Evaluating Information Core principle Evaluations are constructed based on pre-existing attitudes, beliefs, expectations, preconceptions, etc. Construction process reduces ambiguity inherent in the stimulus. Construction process causes divergent perceptions of identical stimulus. e.g., Common association b/w color black and bad Black uniforms and aggression (Frank & Gilovich, 1989) 19

18 Frank & Gilovich, 1988: 20

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22 Manipulating Color 24

23 Evaluating Information Ambiguity especially pernicious in social events. The problem: Construction process works automatically (like vision) unconsciously, unintentionally, effortlessly, uncontrollably Construction process is invisible, output seem like an accurate reflection of reality. Creates Naïve Realism My perceptions are accurate and unbiased. If your perceptions differ from mine, you must be biased (distorted, crazy, unintelligent, unrealistic, misguided ) 25

24 Sense-Making: How Beliefs Make Reality Two Ways: 2. Beliefs create reality Self-fulfilling prophecies. A false belief that, because of the mere existence of the belief, elicits behavior consistent with the false belief. (Merton, 1957) a.k.a., The Pygmalion Effect 27 examples, attractiveness, intelligence, motivation, selfishness, race, gender, But, but, but Not all beliefs are self-fulfilling. Must be in a position of influence (such as a MANAGER!) Must be a mechanism of influence.

25 Sense-Making: How Beliefs Make Reality Three mechanisms for self-fulfilling prophecies: Selection: Hire those you believe are good, not those who are bad. Rarely test the actual validity of one s beliefs. Women and the orchestra Race, sexuality, religion, and hiring biases The cost of a name (Bertrand & Mullainathan, 2006) High quality resume callbacks White name (e.g., Emily) = 11.4% Black name (e.g., Lakisha) = 6.7%

26 Sense-Making: How Beliefs Make Reality Mechanisms for self-fulfilling prophecies: 1. Selection: 2.??? 30

27 31 The Quiz Bowl

28 Sense-Making: How Beliefs Make Reality Mechanisms for self-fulfilling prophecies: 1. Selection: 2. Our own actions elicit behavior from others: We are other people s situations. Can be completely blind to our own influence on others. Can be completely blind to others influence on us! 32

29 Ross, Amabile, & Steinmetz (1977): Intellectual Ability Contestant Rater Observer Questioner Contestant

30 The Quiz Bowl, Take Two 34

31 Sense-Making: How Beliefs Make Reality Mechanisms for self-fulfilling prophecies: 1. Selection: 2. Our own actions on others: Treat others in a manner consistent with our beliefs. Treatment elicits consistent behavior from others. Examples: Attractiveness (Snyder, Tanke, & Berscheid, 1977) Race and hiring (Word, Zanna, & Cooper, 1974) Intellectual ability (Rosenthal & Jacobson, 1968) White hostility towards blacks in competition (Chen & Bargh, 1999) The Set-Up-To-Fail Syndrome 35

32 Sense-Making: How Beliefs Make Reality Mechanisms for self-fulfilling prophecies: 1. Selection: 2. Our own actions on others. 3. Self-concept change: Internalization of others beliefs, awareness of others expectations, presence of stereotype. Remember the Quiz Bowl. Elderly stereotypes (Levy): decreases motivation, search for alternatives, overall effort Stereotype threat (Steele & Aronson): creates anxiety about confirming the stereotype. Attractiveness (Snyder): Leads recipients to view selves in way consistent with others beliefs Set-Up-To-Fail Syndrome 36

33 Sense-Making: How Beliefs Make Reality Mechanisms for self-fulfilling prophecies: 1. Selection. 2. Our own actions on others. 3. Self-concept change: Internalization of others beliefs, or awareness of others expectations. 37

34 Interpreting Reality Model of a Self-fulfilling Prophecy Perceiver Tentative Expectancy Expectancy strengthened Target Person Ambiguous Behavior 38 Expectancy-consistent Behavior Expectancy further strengthened Behavioral Reciprocation Self-Concept Change Interpreting Reality

35 Evaluating Others II: Knowing and Using our Expectations Business Summer, 2008

36 Evaluating Others II: Knowing Our Expectations Varieties of expectations: Explicit Consciously known, easy to articulate. It will rain tomorrow. Kim will work perfectly. 2. Implicit: Consciously inaccessible, unable to articulate, difficult to control, unaware of its influence. Often culture-specific. Common associations: Male Independent, Aggressive Female Nurturing, Compliant Old Rigid, Slow Cultural stereotypes (Black Athlete, White Intellectual) Generally no correlation b/w implicit & explicit

37 Evaluating Others II: Knowing Our Expectations A Riddle: A father and his son are out driving. They are involved in an accident. The father is killed, and the son is in critical condition. The son is rushed to the hospital and prepared for the operation. The doctor comes in, sees the patient, and exclaims, "I can't operate it's my son!" How could this be? 42

38 104 Evaluating Others II: Knowing Our Expectations Implicit Associations Test (Greenwald & Banaji): Measures cultural associations, stereotypes, commonly experienced base-rates. Does NOT measure explicit beliefs. For more information and different tests, go to: See How unethical are you handout reading. Implicit measures predict prejudicial behavior as well as explicit beliefs, sometimes better. Dovidio et al., (1999): Interview experiment Explicit predicts verbal behavior, doesn t vary. Implicit predicts nonverbal behavior. Only implicit measures matter here.

39 105 Ann Hopkins vs. Price Waterhouse

40 Evaluating Others II: Reigning in Unwanted Expectations Structural changes, NOT psychological changes: Concretely define evaluation criteria. Determine relative importance of criteria (e.e., assign weights). Obtain quantitative measures of criteria (even subjective evals.). Drop ambiguous evaluation procedures ( Short forms, strictly qualitative evaluations) Incorporate Multiple Perspectives (Employees, Employer, Clients) Avoid irrelevant information (e.g., photos from folders). Make decisions through calculations, not intuitions. 109