On a first-name basis: Englishization and naming in Flanders

Zenner, Eline; Marzo, Stefania

doi:10.5209/rev_cjes.2015.v23.51203

Cited by 2 publications

(2 citation statements)

References 29 publications

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“…Tyrimuose aptariamas ir įvairių socialinių grupių tapatybių kūrimas, atsiremiant į britų ir anglų kultūras. Štai olandų gėjų pokalbiai su anglų kalbos intarpais socialiniuose tinkluose laikyti tapatinimusi su jaunais, pozityviais anglo-amerikiečių gėjais -medijų kultūros žvaigždėmis (65), o Belgijoje atliktas flamų vardų sociopragmatinių reikšmių tyrimas parodė, kad vaikams duodami anglų ar amerikiečių popkultūros įžymybių vardai (panašiai kaip prekių pavadinimai rinkodaroje) sužadina simbolines asociacijas su šiomis kultūromis, o per jas -ir su globalumu ar šiuolaikiškumu (8); tas pat pasakytina ir apie kitur tirtas hiphopo ar repo subkultūras (2).…”

Section: Anglo-amerikietiškas Vakarietiškasunclassified

“…Analizuotuose straipsniuose pasitaikanti reikšmė SėkmingAS daugiausia siejama su tarptautinio verslo sėkme. Anglų kalbos, kaip tarptautinės ir globalios, vertė panaudojama duodant angliškus ar anglų kalbos elementus įtraukiančius pavadinimus prekių ženklams, įmonėms, kuriant reklamas ir taip sukuriama simbolinė sąsaja su sėkmingu dalyvavimu globalioje ekonomikoje (8,42). Anglų kalba priimama kaip padidinanti šansą pasiekti sėkmę: pavyzdžiui, angliškas prekės ženklas ar įmonės pavadinimas nurodo į potencialiai globalų pripažinimą (66), sugebėjimą konkuruoti (plg.…”

Section: Sėkmingas Pažangusunclassified

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The Social Meaning Potential of the Global English Based on Data from Different Communities

Vaicekauskienė

2020

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This paper describes the social value of the global English language as identified in the investigations of various communities worldwide and shows how the social meanings of English relate to each other in a broader ideological field universal for today’s locally global world. The notions of indexical field (Eckert 2008) and bivalent indexicality (Cotter, Valentinsson 2018) are applied in the analysis. The aim of the study is to synthesize results obtained by different researchers from different ideological and communicative contexts and to explore the indexical potential of English, including its local varieties and mixed speech styles. The study is based on a qualitative analysis of a corpus of secondary sources, consisting of a total of 74 scholarly publications from the Expanding Circle communities, which were published in English in 1990–2020 (most of them during the second decade of the 21st century).In total, more than 50 social meanings of the global English language have been identified. It is likely that the abundance of social associations with English is due to the strong first-order indexes. Hence, the social meanings were grouped into the following nine indexical categories based on the presumed first-order sociocultural indexicalities: British and American culture; International sphere; Technologies, science and education; Economic and social status; Personal capital; Youth; Popular culture and media; Urban sphere; and Male. Positive social meanings dominate the indexicalities, but for some of them, bivalent indexicality (presence of contradictory positive and negative values) has been recorded. Although there is much overlap between these relative categories, the constellation as a whole is interpreted as a complex of several separate and multivalent indexical fields. It is to be hoped that this study not only illustrates that the notion of indexical field is applicable for analysis of the imagined global community of users of English, but also provides a broader ideological context for further research of the social meaning-making potential of the global English language.

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Section: Anglo-amerikietiškas Vakarietiškasunclassified

Section: Sėkmingas Pažangusunclassified

The Social Meaning Potential of the Global English Based on Data from Different Communities

Vaicekauskienė

2020

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Equal accuracy for Andrew and Abubakar—detecting and mitigating bias in name-ethnicity classification algorithms

2023

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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.

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On a first-name basis: Englishization and naming in Flanders

Cited by 2 publications

References 29 publications

The Social Meaning Potential of the Global English Based on Data from Different Communities

The Social Meaning Potential of the Global English Based on Data from Different Communities

Equal accuracy for Andrew and Abubakar—detecting and mitigating bias in name-ethnicity classification algorithms

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