There are no language switching costs when codeswitching is frequent

Abstract

International audienceAims and Objectives/Purpose/Research QuestionsThere is ongoing discussion as to the cost of language switching, with some studies indicating high cost and others showing low or no cost. The main research question in this paper is whether there are language switching costs in communities in which codeswitching is frequent. Design/Methodology/Approach We conducted two on-line experiments, i.e. a picture choice with sentence auditory stimuli and a word recognition task in sentence context. We constructed 16 sentences with differing degrees of ecological validity (16 sentences x 4 versions = 64). The sentences included verbs with different language preferences in natural conversations (L1, L2, or both). Data and AnalysisThirty-seven simultaneous L1-Romani L2-Turkish bilinguals participated in Experiment 1 and 49 in Experiment 2. To analyze the results, linear mixed models (lmer) were constructed using the ‘lme4’ package in R.Findings/ConclusionsIn Experiment 1, participants responded significantly faster for the all-Turkish sentences, followed by the mixed Romani-Turkish sentences, and the two types of ecologically non-valid sentences. However, there were no processing costs for the mixed sentences when they contained Turkish verbs that are more frequently used in Turkish in the spontaneous conversations. In Experiment 2, reaction times were similar for Turkish verbs (with Turkish verb morphology) in a mixed Romani-Turkish or a unilingual Turkish sentence.OriginalityTaken together these findings indicate that language switching costs in comprehension depend on the frequency of codeswitching in the bilingual community, as well as on exposure to specific lexical items.Significance/ImplicationsThe Romani-Turkish data support a usage-based approach to bilingual processing and confirm the need to conduct experimental research that takes into account the communicational habits of the participants

From the Field to the Lab: A Converging Methods Approach to the Study of Codeswitching

“…As research on codeswitching continues to grow, we suggest that more interdisciplinary studies are needed that prioritize the role of experience in language processing. An exciting aspect of recent work is that we are beginning to see more theoretical and empirical developments that take into account the linguistic repertoire (e.g., Adamou and Shen 2017) and the interactional context (e.g., Green and Abutalebi 2013) of speakers. We capitalize on the importance of pairing linguistically informed stimuli with an appropriate bilingual sample and encourage future research to adopt the corpus-to-cognition approach we have described here.…”

Codeswitching: A Bilingual Toolkit for Opportunistic Speech Planning

“…Here we put forth the proposal, based on quantitative analyses of spontaneous codeswitched speech, that codeswitching serves as a toolkit, or an opportunistic strategy for optimizing task performance in cooperative communication. While previous research has focused largely on the costs that codeswitching brings to language processing ( Guzzardo Tamargo et al, 2016 ; Adamou and Shen, 2017 ; Beatty-Martínez and Dussias, 2017 ; Byers-Heinlein et al, 2017 ; for reviews see Van Hell et al, 2015 , 2018 ), we consider the possible advantages that codeswitching may offer to language producers during bilingual language interactions. Critical to this endeavor is the view that codeswitching offers a unique flexibility that is driven by an interplay of bottom-up and top-down processes, but through which resources from both languages are ultimately recruited to convey speakers’ communicative intentions.…”

52. Corpus linguistic methods

“…These frequencies may also shed light to the language switching costs that have been noted in the experimental literature. Recently, Adamou and Shen (2019) and Johns, Valdés Kroff, and Dussias (2018) showed that language switching costs align with the codeswitching habits of the community as documented in corpus studies. The typological scale of language mixing presented in Figure 1 needs to be enriched by other layers of annotation.…”