Evidence map›Paper›PMID 37079201›Full record

ArticleCognitive processing2023

The effects of cross-linguistic similarity on phrase-level language switching: evidence from high-proficient Chinese-English bilinguals.

Xin Chang, Xue-Yi Huang, Xin-Zhe Zou, Peijuan Wang, Pei Wang

Abstract read
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In one paragraph

Article in Cognitive processing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xin ChangSchool of Foreign Languages, Tongji University, Shanghai, 200092, China.
Xue-Yi HuangSchool of Foreign Languages, Shanghai Jiaotong University, Shanghai, 200400, China.
Xin-Zhe ZouSchool of Foreign Languages, Shanghai Jiaotong University, Shanghai, 200400, China.
Peijuan WangSchool of Foreign Languages, Tongji University, Shanghai, 200092, China.
Pei WangFaculty of Education Science, East China Normal University, 3663, Zhangshan Road, Putuo District, Shanghai, 200062, China. wangpei1970@163.com.ORCID http://orcid.org/0000-0002-6309-2366

Funding

General Project of Social Science Planning in Shanghai 2017BYY002
6 · The paper itself

Abstract

Previous research on language switching has debated whether high-proficient bilinguals exhibit symmetrical costs and one underlying reason for which may be the potential influence of cross-linguistic characteristics. The previous conflicting findings suggest their impact on language switching needs to be further investigated. In this study, we recruited 36 high-proficient Chinese-English bilinguals and investigated the effect of cross-linguistic similarity on the switching of quantifier expressions under three switch conditions. The results showed that switch costs were significantly greater when the quantifier expression was similar between Chinese and English than when it was different. Larger switch costs were found in the alternate switch condition than those in the non-switch or random switch conditions. In addition, participants exhibited larger switch costs when switching to the first language than when switching to the second language. The results suggest that the similarity of quantifier expressions between the first language and the second language would create more competition and thus induce larger switch costs in phrase-level language switching, which may be derived from the inner word recognition system of the mental lexicon. This study further improves the relevant theories on the origin of switch costs by supporting the Language Non-Specific Selection Hypothesis.

Indexed as

CognitionLinguisticsMultilingualismSpeechEast Asian PeopleHumansLanguageCross-linguistic similarityHigh-proficient Chinese–English bilingualsLanguage switchingQuantifier expressionSwitch costs

Identifiers

PMID37079201

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.