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The “false consensus” error Tendency to see one’s own attitudes as more common than they really are Why? Example: Legalization of pot (marijuana): Estimate.

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Presentation on theme: "The “false consensus” error Tendency to see one’s own attitudes as more common than they really are Why? Example: Legalization of pot (marijuana): Estimate."— Presentation transcript:

1 The “false consensus” error Tendency to see one’s own attitudes as more common than they really are Why? Example: Legalization of pot (marijuana): Estimate of others’ attitudes: What percentage of students in this class are “pro” vs. “anti”? Self: Is your own attitude “pro” or “anti”?

2 Favor of legalizing pot? 43% pro 57% anti 50% Actual distribution of attitudes in Spring 2004 class 60% pro 40% anti Perceived distribution of attitudes Perceptions by pro participants Perceptions by anti participants 44% pro 50% 56% anti

3 Probability estimates Again, judgments are biased by what comes to mind first – Flying vs. driving – Lotteries – Wildly inflated perceived risk of vivid events (e.g. getting struck by lightning) Guess which is more likely—earth getting hit by a “globally catastrophic” asteroid in the next hundred years, or you winning a typical national lottery? –The asteroid is much more likely—about 20 thousand times more likely –http://newton.dm.unipi.it/ – AIDS

4 Risk that woman will contract AIDS with one heterosexual contact with HIV positive male, no condom Approximate Statistics Participants’ estimates.2% (1/500) 50% w/condom.02% (1/5000) 5% BUT: Why important to wear a condom: Helps prevent: unwanted pregnancy, spread of other STDs (e.g. herpes; 20-30% U.S. population, no cure at current time) 8% of AIDS cases in the United States have been attributed to heterosexual contact.

5 Controlled processing Interplay between automatic and controlled processing: popular view – Automatic processes first, then control as potential “correction” – Similar to “Stroop” effect ORANGE BLUE – Diallo case – Key points: awareness, motivation and ability

6 Automatic process triggered Perceiver Aware of automatic process? Motivated to “correct”? Ability to “correct”? If yes… Potential for controlled processing If yes… Stimulus If yes… Automatic processing likely to dominate If no…

7 Automatic believing (acceptance) and controlled unbelieving Read assertion Understand assertion Initial acceptance of assertion as true Largely automatic “Unaccept” if motivation and ability high controlled Washington University professor found guilty of drinking beer during class Colleagues of Dr. Lambert are “shocked, just shocked” at the news.

8 Why this is important Similar social psychological phenomena – Social perception and attribution – Self and social comparison Applied issues – False/misleading advertising – Negative and misleading political campaigns – Legal issues Exposure to pre-trial press/rumor Juror instructions to disregard

9 Mental Correction and the self Self-relevant information varies in quality/meaningfulness Just because we receive it doesn’t mean we want to, or should, accept it – Motivated (enemies, bigots, subordinates) – Relevance (social comparisons) – Extenuating circumstances

10 Recent study by Hetts et al. on sarcasm All participants perform poorly 2 IVs Type of feedback after performance – Feedback only – Feedback + additional positive sarcastic remark Load vs. no load during feedback DV: performance SE (after feedback)

11 Models of interplay 1) Correction/regulation – C can override A 2) Multi-tasking – A & C may operate in parallel 3) Delegation – C may initiate A 4) Orienting – A may initiate C 5) Automatization – C can be transformed into A 6) Disruption - A can be transformed into C 7) Intrusion – A may interfere with C

12 Mental Undoing: Counterfactual thinking Generating alternative accounts of reality – If X hadn’t happened, then….. – If X had happened, then…. Implications for emotional reactions – Near-misses elicit more extreme reactions – E.g. grades Medvec, Madey, and Gilovich (1995)


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