publications

The thesis is an investigation into dual citizenship—that is, formal membership in more than one nation-state—and belonging in the context of immigration. The task was carried out through a rich theoretical discussion and articulated via an original empirical study. The findings of in-depth interviews conducted with Brazilians—dual citizens living in Europe—showed how the participants were aware of citizenship as a project of the politics of belonging, whose property of entitlement to place played a dynamic role in their experiences. Three types were presented that differ in terms of feelings of belonging and self-identification in relation to dual citizenship: found home, home in progress and pragmatic home.

Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representativeness and face-ism in search engine image results. We systematically queried four search engines (Google, Bing, Baidu, Yandex) from three locations, using two browsers and in two waves, with gender-neutral (person, intelligent person) and gendered (woman, intelligent woman, man, intelligent man) terminology, accessing the top 100 image results. We employed automatic identification for the individual’s gender expression (female/male) and the calculation of the face-to-body ratio of individuals depicted. We find that, as in other forms of media, search engine images perpetuate biases to the detriment of women, confirming the existence of the representation and face-ism biases. In-depth algorithmic debiasing with a specific focus on gender bias is overdue.