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Article . 2020 . Peer-reviewed
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Article . 2020 . Peer-reviewed
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Journal of Personality and Social Psychology
Article . 2022 . Peer-reviewed
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Grammatical Gender and Anthropomorphism: “It” Depends on the Language

Authors: Alican Mecit; Tina M. Lowrey; L. J. Shrum;

Grammatical Gender and Anthropomorphism: “It” Depends on the Language

Abstract

Consumers often anthropomorphize non-human entities. In this research, we investigate a novel antecedent of anthropomorphism: language. Some languages (e.g., English) make a grammatical distinction between humans (he, she) and non-humans (it), whereas other languages (e.g., French) do not (all objects are gender-marked). We propose that such grammatical structures of languages influence the way individuals mentally represent non-human entities, and as a result, their generalized tendencies to anthropomorphize such entities. Across 10 studies, we provide evidence that speakers of languages that do not grammatically distinguish between humans and non-humans (it-less languages) anthropomorphize more than do speakers of languages that do make this distinction (non-it-less languages). We demonstrate the effects across natural languages (French, Turkish, English) and by manipulating grammatical gender. We show that the effects are observable in naturally occurring consumer contexts (e.g., secondary sales data), and that gender-marking in it-less languages influences consumers’ interactions with brands, even though the gender-markings are semantically arbitrary, and that these effects occur nonconsciously. Our findings have implications for the broader debate on the extent to which language influences thought, and also suggest ways in which managers can leverage nonconscious grammatical anthropomorphism to influence consumer perceptions, attitudes, and behavior.

Related Organizations
Keywords

Male, Cognitive Psychology, Animals, Gender Identity, Humans, Female, Linguistics, Social and Behavioral Sciences, Language

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    10
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Average
bronze