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[Stereotype-based expectancy and social judgment: rethinking from a Bayesian perspective].

T Kameda

    Shinrigaku Kenkyu : the Japanese Journal of Psychology
    |April 1, 1986
    PubMed
    Summary
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    Prior stereotypes significantly influence social judgments, even with identical information. This "labeling effect" was strongest when information was less diagnostic, showing how group affiliation impacts perception.

    Area of Science:

    • Cognitive Psychology
    • Social Psychology
    • Decision Making

    Background:

    • Investigates the influence of prior stereotypical expectations on social judgment.
    • Examines how individuals process information when forming opinions about others.
    • Applies a Bayesian perspective to understand expectancy effects in social cognition.

    Purpose of the Study:

    • To determine the impact of prior stereotypical expectancy on social judgment.
    • To analyze how individuals use diagnostic and base-rate information in social inference.
    • To explore the 'labeling effect' in the context of political affiliation and attitude inference.

    Main Methods:

    • Undergraduate participants (N = 204) inferred a target's attitude toward atomic power.
    • Participants received either a pro-expectancy (Liberal Democratic Party) or con-expectancy (Japanese Socialist Party) label.

    Related Experiment Videos

  • Target's utterances with high or low diagnostic values were presented to assess inference accuracy.

    • Main Results:

    • A significant 'labeling effect' was observed: identical utterances led to different attitude estimations based on the label.
    • The labeling effect was more pronounced with low diagnostic utterances.
    • Participants underused base-rate information (prior expectancy) when presented with high diagnostic utterances, deviating from Bayesian norms.
    • Congruent utterances were recalled more effectively than incongruent ones.

    Conclusions:

    • Prior stereotypical expectancies strongly bias social judgments, overriding objective information.
    • The diagnosticity of information moderates the influence of prior beliefs on judgment.
    • Individuals may not optimally integrate prior and new information, as suggested by deviations from Bayesian models.