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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 OutFlip: Generating Examples for Unknown Intent Detection with Natural Language Attack ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Choi, DongHyun; Kim, EungGyun. - : Underline Science Inc., 2021 BASE Show details 2 RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Choi, DongHyun; Kim, EungGyun. - : Underline Science Inc., 2021 BASE Show details 3 Replication Data for: Linguistic Assimilation Does Not Reduce Discrimination Against Immigrants: Evidence from Germany ... Choi, Donghyun Danny; Poertner, Mathias; Sambanis, Nicholas. - : Harvard Dataverse, 2020 Abstract: Many western liberal democracies have witnessed increased discrimination against immigrants and opposition to multiculturalism. Prior research identifies ethno-linguistic differences between immigrant and native populations as the key source of such bias. Linguistic assimilation has therefore been proposed as an important mechanism to reduce discrimination and mitigate conflict between natives and immigrants. Using large-scale field experiments conducted in 29 cities across Germany--a country with a high influx of immigrants and refugees--we empirically test whether linguistic assimilation reduces discrimination against Muslim immigrants in every-day social interactions. We find that it does not; Muslim immigrants are no less likely to be discriminated against even if they appear to be linguistically assimilated. However, we also find that ethno-linguistic differences alone do not cause bias among natives in a country with a large immigrant population and state policies that encourage multiculturalism. ... URL: https://dx.doi.org/10.7910/dvn/d2xpj6 https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/D2XPJ6 BASE Hide details

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