Demographic aspects of first names
By K. Tzioumis. 2018
126 citations recorded by the source corpus.
We introduce a list that offers information on the relation between first names and race or ethnicity. Drawing information from mortgage applications, the list includes 4,250 first names and information on their respective count and proportions across six mutually exclusive racial and Hispanic origin groups. These six categories are consistent with the categories used in the Census Bureau's list on surnames' demographic information. Also, just like the Census Bureau's list of surnames, the list of first names is highly aggregated, so as to not identify any specific individuals. Design Type(s) data integration objective Measurement Type(s) First Name Technology Type(s) digital curation Factor Type(s) ethnic group Sample Characteristic(s) United States of America Design Type(s) data integration objective Measurement Type(s) First Name Technology Type(s) digital curation Factor Type(s) ethnic group Sample Characteristic(s) United States of America Machine-accessible metadata file describing the reported data (ISA-Tab format)
Subfields: Gender Studies, Sociology and Political Science, Social Sciences & Humanities
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In Gender Studies
In Sociology and Political Science
- Adina Williams
- Eric Michael Smith
- Kawin Ethayarajh
- Christopher Potts
- Tristan Thrush
- Douwe Kiela
- February Friday
- Robin Jia
In Social Sciences & Humanities
- Kawin Ethayarajh
- Christopher Potts
- Tristan Thrush
- Douwe Kiela
- Rebecca Qian
- Jude Fernandes
- February Friday
- Eric Michael Smith
Citations in the corpus
- Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue models (2021, background): “Despite the existence of measurable statistical tendencies for names to refer to individuals with particular demographics—such gender and race (Tzioumis, 2018; Newman et al., 2018) or age (Lieberson, 2000; Twenge et al.”
- Perturbation Augmentation for Fairer NLP (2022, background): “However, most names can be and are held by people from various genders or racial/ethnic backgrounds, and these proportions are a field of study in themselves (Tzioumis, 2018).”
- Evaluating Large Language Models (2022, background): “Gender pronouns, names with strong statistical associations with particular races, and other such terms can be useful for specifying arguments: we provide several papers that provide such lists [4, 8, 12, 19, 5, 13].”
- Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking (2021, background): “, replacing “he” with “they” following [14, 13]) and (ii) by substituting names with others that are statistically predictive [70] of another race or ethnicity (e.”