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Detecting gender before you know it: How implementation intentions control early gender categorization.

Sabine Hügelschäfer1, Alexander Jaudas2, Anja Achtziger2

  • 1Department of Economics, University of Cologne, Albertus-Magnus-Platz, D-50923 Köln, Germany.

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|August 25, 2016
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Summary

Automatic gender categorization, identified by early brain responses (N170), can be controlled by intentions. Goal and implementation intentions influence this automatic process, demonstrating effective conscious control over nonconscious bias.

Keywords:
AutomaticityControlERPsGender categorizationGoalsImplementation intentions

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Area of Science:

  • Cognitive Neuroscience
  • Social Psychology

Background:

  • Gender categorization from faces is a rapid, automatic cognitive process.
  • Event-related potentials (ERPs), specifically the N170 component, indicate gender categorization occurs around 130ms.
  • Previous research highlights the automatic nature of gender detection, even during other tasks.

Purpose of the Study:

  • To investigate if automatic gender categorization can be modulated by goal intentions and implementation intentions.
  • To examine the temporal dynamics of intention effects on early (N170) and later (P300) ERP components.
  • To explore the potential for conscious control over automatic gender bias.

Main Methods:

  • Replication of N170 modulation in response to gender-incongruent faces during a gender categorization task.
  • Comparison of ERPs across tasks where gender was relevant versus irrelevant (dot color task).
  • Manipulation of intention types (goal intention, implementation intention) to assess their impact on N170 and P300 components.

Main Results:

  • N170 modulation by gender incongruency was task-dependent, appearing only when gender was the target of categorization.
  • A goal intention to control gender bias altered the N170 effect, suggesting nonconscious goal pursuit.
  • Implementation intentions completely abolished the N170 modulation.
  • Later P300 component remained modulated by gender incongruency regardless of intention, confirming automatic gender detection.

Conclusions:

  • Automatic gender categorization, occurring at early processing stages (N170), is susceptible to control by intentions.
  • Implementation intentions provide a more effective mechanism for overriding automatic gender categorization than goal intentions alone.
  • Findings support the capacity for conscious intentions to regulate automatic social cognition processes.