| Summary: | How sensitive is pronoun processing to expectancies based on real-world knowledge and language usage? The current study links research on the integration of gender stereotypes and number-mismatch to explore this question. It focuses on the use of them to refer to antecedents of different levels of gender-expectancy (low–cyclist, high–mechanic, known–spokeswoman). In a rating task, them is considered increasingly unnatural with greater gender expectancy. However, participants might not be able to differentiate high-expectancy and gender-known antecedents online because they initially search for plural antecedents (e.g., Sanford & Filik), and they make all-or-nothing gender inferences. An eye-tracking study reveals early differences in the processing of them with antecedents of high gender-expectancy compared with gender-known antecedents. This suggests that participants have rapid access to the expected gender of the antecedent and the level of that expectancy.
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