Uncovering the world’s ethnic inequalities is hampered by a lack of ethnicity-annotated datasets. Name-ethnicity classifiers (NECs) can help, as they are able to infer people’s ethnicities from their names. However, since the latest generation of NECs rely on machine learning and artificial intelligence (AI), they may suffer from the same racist and sexist biases found in many AIs. Therefore, this paper offers an algorithmic fairness audit of three NECs. It finds that the UK-Census-trained EthnicityEstimator displays large accuracy biases with regards to ethnicity, but relatively less among gender and age groups. In contrast, the Twitter-trained NamePrism and the Wikipedia-trained Ethnicolr are more balanced among ethnicity, but less among gender and age. We relate these biases to global power structures manifested in naming conventions and NECs’ input distribution of names. To improve on the uncovered biases, we program a novel NEC, N2E, using fairness-aware AI techniques. We make N2E freely available at www.name-to-ethnicity.com.
The age of migration finds its physical manifestation in the immigrant neighbourhoods of European cities. These ‘ethnic enclaves’ have received much attention from the public, as well as policy makers. Conventional wisdom holds that policies are required to confront such concentrations. Several European countries have implemented measures to achieve a spatial balance – be it through settlement bans or allocation quotas – in the name of fostering immigrants’ integration. However, the scholarly verdict on the relationship between segregation and integration is still pending. This article aims to contribute a novel approach, namely discourse analysis of immigrants’ Facebook groups. To this end, it first establishes the level of segregation in six cities (three in Germany and three in England) using data held by municipal archives. Second, it scrutinises 119 Facebook groups of Pakistanis and Turks in these cities, with a total of 2665 posts. This exploratory analysis suggests that desegregation might be causative for downwards assimilation and transnationalism, whereas ethnic enclaves might provide the basis for a pluralist mode of integration. Therefore, it argues for a re-evaluation of the suitability of dispersal policies for shaping the transformation of ever more European cities into multi-ethnic metropolises.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.