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Mapping Linguistic Diversity in a Globalizing World through Open Source Digital Tools
COVID-19 Research Area(s): Culture, Politics, Governance & Law, Social Impacts
The United Nations has proclaimed 2019 the International Year of Indigenous Languages, but linguistic diversity remains under extreme stress. Today, communities who speak increasingly endangered languages are profoundly mobile, often out of necessity. Because languages move with people, language mapping is difficult, whether in print or digital form. Techniques that locate languages as dots on a map are flawed (where would you locate the dot for English?), while polygons don’t accurately represent plurilingual realities. A failure to understand linguistic diversity can manifest in unsuccessful public service delivery and civic engagement, particularly in marginalized communities. Embracing this challenge, the New York-based Endangered Language Alliance is producing popular printed maps of the world’s most linguistically diverse city. Municipal leadership in New York are using this knowledge to shape public policy. Our project will transform these maps into generalizable, interactive digital tools that support community-based language mapping anywhere in the world.
Since late March, New York City has been the global epicenter of the COVID-19/coronavirus pandemic, with 134,874 confirmed cases and almost 10,000 confirmed deaths as of April 21. Nearly every New Yorker has been affected, but the effects have not been evenly distributed. While there is emerging evidence in city data of serious disparities by race, it is also becoming clear, as this map indicates, that multilingual immigrant communities have been among the hardest hit.
Our map combines the number of confirmed COVID-19 cases by ZIP Code (as of April 21) from the New York City Department of Health with the Endangered Language Alliance’s recently released NYC Language Map, which emphasizes linguistic diversity by representing over 600 languages at approximately 1,000 significant sites across the city, based on years of collaboration and data-gathering with the city’s language communities.
Despite significant nuances and challenges — such as how to represent languages (especially the more widely-spoken) at individual locations, major variation in population per ZIP Code, different levels of testing for COVID-19 — some overall patterns are clear:
The Central Queens neighborhoods of Corona, Elmhurst, and Jackson Heights, where hundreds of minority and Indigenous languages are spoken from across Latin America and Asia, has become the “epicenter of the epicenter”, with approximately 9,000 cases and hundreds of fatalities.
The most linguistically diverse stretch of neighborhoods in Brooklyn, from Borough Park to Canarsie and including major Jewish, Caribbean, and post-Soviet diaspora communities, has the highest number of cases in the borough.
Major immigrant neighborhoods that are home to speakers of smaller languages from across Latin America, the Caribbean, and West Africa are bearing the brunt of the outbreak in Harlem and the Bronx, with high mortality rates.
These patterns are confirmed in stories from the communities themselves. Immigrant workers on the frontlines, such as essential care workers, food workers, and transit workers are at greater risk. Disparities around housing, income, health, and immigration status also play a role. A lack of timely, widely disseminated information in community languages, despite efforts, is another critical factor. Language is just one important indicator — note, for example, the affluent multilingual cluster around Manhattan’s United Nations with relatively fewer cases.
New York City’s multilingual immigrant communities are organizing, from mutual aid among Brooklyn’s Mayan community to a Queens-based Nepali network. The COVID-19 Immigrant Emergency Relief Program announced on April 16 is another important step, but more is needed.
This map was produced by the Mapping Linguistic Diversity partnership, bringing together the Endangered Language Alliance and researchers at the University of British Columbia, with support from the Peter Wall Institute for Advanced Studies.