An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Supplemental material, sj-R-3-eup-10.1177_14651165211037208 for Discrimination against mobile European Union citizens before and during the first COVID-19 lockdown: Evidence from a conjoint experiment in Germany by Xavier Fernández-i-Marín, Carolin H Rapp, Christian Adam, Oliver James and Anita Manatschal in European Union Politics

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Supplemental material, sj-R-2-eup-10.1177_14651165211037208 for Discrimination against mobile European Union citizens before and during the first COVID-19 lockdown: Evidence from a conjoint experiment in Germany by Xavier Fernández-i-Marín, Carolin H Rapp, Christian Adam, Oliver James and Anita Manatschal in European Union Politics

Supplemental material, sj-R-2-eup-10.1177_14651165211037208 for Discrimination against mobile European Union citizens before and during the first COVID-19 lockdown: Evidence from a conjoint experiment in Germany by Xavier Fernández-i-Marín, Carolin H Rapp, Christian Adam, Oliver James and Anita Manatschal in European Union Politics

Supplemental material, sj-R-3-eup-10.1177_14651165211037208 for Discrimination against mobile European Union citizens before and during the first COVID-19 lockdown: Evidence from a conjoint experiment in Germany by Xavier Fernández-i-Marín, Carolin H Rapp, Christian Adam, Oliver James and Anita Manatschal in European Union Politics

How language users become able to process forms they have never encountered in input is central to our understanding of language cognition. A range of models, including rule-based models, stochastic models, and analogy-based models have been proposed to account for this ability. Despite the fact that all three models are reasonably successful, we argue that productivity in language is more insightfully captured through learnability than by rules or probabilities. Using a combination of computational modelling and behavioural experimentation we show that the basic principle of error-driven learning allows language users to detect relevant patterns of any degree of systematicity. In case of allomorphy, these patterns are found at a level that cuts across phonology and morphology and is not considered by mainstream approaches to language. Our findings thus highlight how a learning-based approach applies to phenomena on the continuum from rule-based over probabilistic to “unruly” and constrains our inferences about the types of structures that should be targeted on a cognitively realistic account of allomorphic representation.

How language users become able to process forms they have never encountered in input is central to our understanding of language cognition. A range of models, including rule-based models, stochastic models, and analogy-based models have been proposed to account for this ability. Despite the fact that all three models are reasonably successful, we argue that productivity in language is more insightfully captured through learnability than by rules or probabilities. Using a combination of computational modelling and behavioural experimentation we show that the basic principle of error-driven learning allows language users to detect relevant patterns of any degree of systematicity. In case of allomorphy, these patterns are found at a level that cuts across phonology and morphology and is not considered by mainstream approaches to language. Our findings thus highlight how a learning-based approach applies to phenomena on the continuum from rule-based over probabilistic to “unruly” and constrains our inferences about the types of structures that should be targeted on a cognitively realistic account of allomorphic representation.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.