Dataset Information

What's in a Name? Sound Symbolism and Gender in First Names.

ABSTRACT: Although the arbitrariness of language has been considered one of its defining features, studies have demonstrated that certain phonemes tend to be associated with certain kinds of meaning. A well-known example is the Bouba/Kiki effect, in which nonwords like bouba are associated with round shapes while nonwords like kiki are associated with sharp shapes. These sound symbolic associations have thus far been limited to nonwords. Here we tested whether or not the Bouba/Kiki effect extends to existing lexical stimuli; in particular, real first names. We found that the roundness/sharpness of the phonemes in first names impacted whether the names were associated with round or sharp shapes in the form of character silhouettes (Experiments 1a and 1b). We also observed an association between femaleness and round shapes, and maleness and sharp shapes. We next investigated whether this association would extend to the features of language and found the proportion of round-sounding phonemes was related to name gender (Analysis of Category Norms). Finally, we investigated whether sound symbolic associations for first names would be observed for other abstract properties; in particular, personality traits (Experiment 2). We found that adjectives previously judged to be either descriptive of a figuratively 'round' or a 'sharp' personality were associated with names containing either round- or sharp-sounding phonemes, respectively. These results demonstrate that sound symbolic associations extend to existing lexical stimuli, providing a new example of non-arbitrary mappings between form and meaning.

SUBMITTER: Sidhu DM

PROVIDER: S-EPMC4446333 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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What's in a Name? Sound Symbolism and Gender in First Names.

Sidhu David M DM Pexman Penny M PM

PloS one 20150527 5

Although the arbitrariness of language has been considered one of its defining features, studies have demonstrated that certain phonemes tend to be associated with certain kinds of meaning. A well-known example is the Bouba/Kiki effect, in which nonwords like bouba are associated with round shapes while nonwords like kiki are associated with sharp shapes. These sound symbolic associations have thus far been limited to nonwords. Here we tested whether or not the Bouba/Kiki effect extends to exist ...[more]

PMID: 26016856

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Project description:BackgroundArtificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and professional ramifications, making the potential social biases in ChatGPT's underlying language model a serious concern.ObjectiveThree preregistered studies used the text analysis program Linguistic Inquiry and Word Count to investigate gender bias in recommendation letters written by ChatGPT in human-use sessions (N=1400 total letters).MethodsWe conducted analyses using 22 existing Linguistic Inquiry and Word Count dictionaries, as well as 6 newly created dictionaries based on systematic reviews of gender bias in recommendation letters, to compare recommendation letters generated for the 200 most historically popular "male" and "female" names in the United States. Study 1 used 3 different letter-writing prompts intended to accentuate professional accomplishments associated with male stereotypes, female stereotypes, or neither. Study 2 examined whether lengthening each of the 3 prompts while holding the between-prompt word count constant modified the extent of bias. Study 3 examined the variability within letters generated for the same name and prompts. We hypothesized that when prompted with gender-stereotyped professional accomplishments, ChatGPT would evidence gender-based language differences replicating those found in systematic reviews of human-written recommendation letters (eg, more affiliative, social, and communal language for female names; more agentic and skill-based language for male names).ResultsSignificant differences in language between letters generated for female versus male names were observed across all prompts, including the prompt hypothesized to be neutral, and across nearly all language categories tested. Historically female names received significantly more social referents (5/6, 83% of prompts), communal or doubt-raising language (4/6, 67% of prompts), personal pronouns (4/6, 67% of prompts), and clout language (5/6, 83% of prompts). Contradicting the study hypotheses, some gender differences (eg, achievement language and agentic language) were significant in both the hypothesized and nonhypothesized directions, depending on the prompt. Heteroscedasticity between male and female names was observed in multiple linguistic categories, with greater variance for historically female names than for historically male names.ConclusionsChatGPT reproduces many gender-based language biases that have been reliably identified in investigations of human-written reference letters, although these differences vary across prompts and language categories. Caution should be taken when using ChatGPT for tasks that have social consequences, such as reference letter writing. The methods developed in this study may be useful for ongoing bias testing among progressive generations of chatbots across a range of real-world scenarios.Trial registrationOSF Registries osf.io/ztv96; https://osf.io/ztv96.

Dataset Information

What's in a Name? Sound Symbolism and Gender in First Names.

Publications

What's in a Name? Sound Symbolism and Gender in First Names.

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