Americanization now and then: the 'nation of immigrants' in the early twentieth and twenty-first centuries

In an analysis of contemporary attempts at US immigration reform in the context of its legal history (especially John F. Kennedy's 1964 Immigration and Nationality Act) this article explores a fundamental paradox in American political thought and practice as regards immigration. It examines the tension between the US's insistence, on one hand, upon immigrants' swift and wholesale integration into American life (as exemplified in the early 20th C Americanization programme, echoed in a 2007 call for a renewed Americanization initiative under President George W. Bush) and its self- definition as a proud 'nation of immigrants' on the other. In so doing, the essay critiques the 'nation of immigrants' shibboleth for its implicit racist bias and introduces the concept of 'ethnic shame,' prevalent for most of the 20th C, to complement today's much more familiar (but also much more recent) notion of Americans' ethnic pride in their immigrant roots. The article concludes that the ostensible paradox of a 'nation of immigrants' insisting on Americanization is best understood within the framework of what is theorised here for the first time as the 'gratitude paradigm,' which governs the granting and the possession of American citizenship to immigrants not just of the first, but of many generations thereafter

The Sensitivity of Language Models and Humans to Winograd Schema Perturbations

Large-scale pretrained language models are the major driving force behind recent improvements in performance on the Winograd Schema Challenge, a widely employed test of common sense reasoning ability. We show, however, with a new diagnostic dataset, that these models are sensitive to linguistic perturbations of the Winograd examples that minimally affect human understanding. Our results highlight interesting differences between humans and language models: language models are more sensitive to number or gender alternations and synonym replacements than humans, and humans are more stable and consistent in their predictions, maintain a much higher absolute performance, and perform better on non-associative instances than associative ones. Overall, humans are correct more often than out-of-the-box models, and the models are sometimes right for the wrong reasons. Finally, we show that fine-tuning on a large, task-specific dataset can offer a solution to these issues.Comment: ACL 202

Why Machiavellianism Matters in Childhood: The Relationship Between Children's Machiavellian Traits and Their Peer Interactions in a Natural Setting

The current study investigated the association between Machiavellianism and children’s peer interactions in the playground using observational methods. Primary school children (N = 34; 17 female), aged 9 to 11 years, completed the Kiddie Mach scale and were observed in natural play during 39 recesses (average observed time = 11.70 hours) over a full school year. Correlations for boys revealed that Machiavellianism was related to more time engaging in direct and indirect aggression, being accepted into other peer groups, and accepting peers into their own social group. Correlations revealed that for girls, Machiavellianism was associated with lower levels of indirect aggression, less time being accepted into other groups and less time accepting and rejecting other children into their own group. This preliminary pilot study indicates that Machiavellianism is associated with children’s observed social behaviour and aims to promote future observational research in this area