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      On the position of subjects in Spanish: Evidence from code-switching

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      Glossa: a journal of general linguistics
      Ubiquity Press, Ltd.

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          Abstract

          Some languages have a fixed subject position, while others are more flexible. Languages like English require pre-verbal subjects; languages like Spanish allow subjects in postverbal position. Because this difference clusters with several linguistic properties distinguishing the two languages, subjects in Spanish and English have been a perennial issue in linguistic theory, touching central problems like the EPP, the nature of cross-linguistic variation, and the relationship between core functional heads. Our project contributes a novel source of evidence to these debates: Spanish/English code-switching. Code-switching, the use of two languages in one utterance, combines the languages’ lexical items and their attendant syntactic features in a single derivation. Because code-switching, like all natural language, is rule-governed, researchers can exploit judgments about the well-formedness of code-switched sentences to draw conclusions about the combinations of features they represent. We report on a formal judgment experiment testing subject position in Spanish/English code-switching as a function of the presence of two functional heads known (from monolingual evidence) to affect subject placement: the C(omplementizer) and T(ense) heads. By manipulating which head appears in which language, we test the availability of post-verbal subjects under different feature combinations. Our results show that post-verbal subjects are only available when both C and T are in Spanish; neither Spanish head alone is sufficient. This finding suggests that the features regulating subject position stem from neither head alone, which is problematic for traditional approaches to the EPP as a feature of T but in line with other recent research on null subjects.

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          Most cited references64

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          Random effects structure for confirmatory hypothesis testing: Keep it maximal.

          Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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            Sometimes I’ll start a sentence in Spanish Y TERMINO EN ESPAÑOL: toward a typology of code-switching1

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              Introducing LexTALE: A quick and valid Lexical Test for Advanced Learners of English

              The increasing number of experimental studies on second language (L2) processing, frequently with English as the L2, calls for a practical and valid measure of English vocabulary knowledge and proficiency. In a large-scale study with Dutch and Korean speakers of L2 English, we tested whether LexTALE, a 5-min vocabulary test, is a valid predictor of English vocabulary knowledge and, possibly, even of general English proficiency. Furthermore, the validity of LexTALE was compared with that of self-ratings of proficiency, a measure frequently used by L2 researchers. The results showed the following in both speaker groups: (1) LexTALE was a good predictor of English vocabulary knowledge; 2) it also correlated substantially with a measure of general English proficiency; and 3) LexTALE was generally superior to self-ratings in its predictions. LexTALE, but not self-ratings, also correlated highly with previous experimental data on two word recognition paradigms. The test can be carried out on or downloaded from www.lextale.com.
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                Author and article information

                Journal
                Glossa: a journal of general linguistics
                Glossa
                Ubiquity Press, Ltd.
                2397-1835
                January 04 2021
                June 01 2021
                : 6
                : 1
                : 73
                Article
                10.5334/gjgl.1449
                4ea9d921-38e2-4ad7-bd70-ad6c029ae697
                © 2021

                https://creativecommons.org/licenses/by/4.0/

                https://creativecommons.org/licenses/by/4.0/


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