Gendered cities: Studying urban gender bias through street names

Abstract

This paper uses text analysis to measure gender bias in cities through the use of street names. Focusing on the case of Spain, we collect data on 15 million street names to analyze gender inequality in urban toponyms. We calculate for each Spanish municipality and each year from 2001 to 2020 a variable measuring the percentage of streets with female names over the total number of streets with male and female names. Our results reveal a strong gender imbalance in Spanish cities: the percentage of streets named after women is only 12% in 2020. We also observe substantial intra-urban differences, with female named streets being relatively scarcer in town centers. Concerning new streets, gender bias is lower but still far from parity. The second part of the paper analyzes the correlation of our indicator of gender bias in street names with variables related to gender attitudes and values, with the results suggesting that it constitutes a useful cultural measure of gender equality at the city level. This study thus helps to measure a relevant phenomenon, given the strong symbolic power attributed to street names, which has been elusive to quantify so far.

Embroidering the city map

“… 1 Previous linguistic landscape studies have pointed out a lack of visibility of women in public spaces, with a female share of rarely over 10% in European cities 2 and female streets more frequent in areas far from the city center. 3 While assigning genders based on names and gender markers is problematic because it relies on a binary understanding of gender and therefore perpetuates cissexism, “the lack of gender representation in many aspects of society is a reality,” 4 which makes the investigation of gender imbalances necessary. This creation therefore aims to make visible the strong gender imbalance that is present in the German city of Frankfurt (Oder).…”

Tabulating and visualizing street-name data in the US and Europe

“…Similarly, people in Scotland living in areas with street names commemorating Great Britain are less likely to identify themselves as Scottish only (Oto-Peralías, 2017). Regarding gender equality, Gutiérrez-Mora and Oto-Peralías (2022) collect data on 15 million street names in Spain to document that only 12% of streets named after a person refer to women. Other examples (among many others) of recent research papers using street-name data in quantitative analysis include Fałkowski and Kurek (2020), Rusu (2020), Villamil and Balcells (2021), and Ruipérez and Dinas (2023).…”

“…3.A shortcoming of this data source is that, as the information comes from an electoral census, it only includes streets where there are electors registered. Oto-Peralías and Gutiérrez-Mora (2022) show that the practical implications arising from this are of minor importance.…”

Featured graphics: Migrating from EP-A to EP-B

“…Increasingly, EP-B articles exceed the word limit set by the journal and authors resort to providing even more graphics as supplemental material; for example, see the recent article by Gutiérrez-Mora and Oto-Peralías (2022) analysing and visualising urban gender bias by looking at 15 million street names of Spanish cities. There is increasing demand for disseminating our scholarship through non-traditional forms, beyond the words and tables in our articles.…”