2016
DOI: 10.1017/s1366728916000766
|View full text |Cite
|
Sign up to set email alerts
|

Gender matters: From L1 grammar to L2 semantics

Abstract: The study investigates the effects of grammatical gender on bilingual processing. Native speakers of Russian (a gendered language) learning English and monolingual English controls performed a self-paced reading task in English (a non-gendered language). As predicted, bilingual speakers showed delayed latencies to gendered pronouns (he or she) that were incongruent with the noun's grammatical gender in Russian, indicating that first language (L1) grammatical gender assignment can be interpreted as biological g… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
8
1

Year Published

2017
2017
2021
2021

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(9 citation statements)
references
References 81 publications
(140 reference statements)
0
8
1
Order By: Relevance
“…However, our findings also deviate from this previous research in three important ways. First, we did not find the difference in effects for (GENERIC) ANIMATES versus NON-ANIMATES reported elsewhere (Cook, 2016;Saalbach et al, 2012;Vigliocco et al, 2005). Second, the effect in our study emerged both in an implicit task and for speakers of a language with three genders, for which such findings tend to be unstable or even absent (Cubelli et al, 2011;Sera et al, 2002).…”
Section: Reconciling Conflicting Findings: a Possible Mechanism Of Thcontrasting
confidence: 79%
See 2 more Smart Citations
“…However, our findings also deviate from this previous research in three important ways. First, we did not find the difference in effects for (GENERIC) ANIMATES versus NON-ANIMATES reported elsewhere (Cook, 2016;Saalbach et al, 2012;Vigliocco et al, 2005). Second, the effect in our study emerged both in an implicit task and for speakers of a language with three genders, for which such findings tend to be unstable or even absent (Cubelli et al, 2011;Sera et al, 2002).…”
Section: Reconciling Conflicting Findings: a Possible Mechanism Of Thcontrasting
confidence: 79%
“…From a theoretical point of view, two categories of nouns need to be distinguished: nouns referring to non-animates (mostly objects) that have grammatical gender but no sex (henceforth abbreviated as NON-ANIMATES), and nouns referring to animates (mostly animals) that have both grammatical gender and sex, with the two being potentially in conflict, such as when one particular gender is generically used for individuals of both sexes (GENERIC ANIMATES). Although our own work did not yield diverging effects for the two categories (Bender et al, 2016a), there is a body of research pointing to such differences-most notably that an effect may emerge for animals but not objects (Cook, 2016;Saalbach et al, 2012;Vigliocco et al, 2005), and that natural kinds are more strongly associated with female properties and artifacts more strongly with male properties (Mullen, 1990;Sera et al, 1994Sera et al, , 2000. Although our category of GENERIC ANIMATES is, by definition, confined to natural kinds and our category of NON-ANIMATES consists largely (albeit not exclusively) of artifacts, we ensured that items in each category evoke associations in line with the particular grammatical gender.…”
Section: Overview Of the Current Studymentioning
confidence: 61%
See 1 more Smart Citation
“…Such results might be explained in terms of an effect of membership in the same grammatical category, independently of biological sex information (cf. Cook, 2016). Because this review is entirely concerned with this specific relationship such studies, though clearly interesting in their own right, were omitted.…”
Section: What Is Not In the Reviewmentioning
confidence: 99%
“…Lower word boundaries for excluding unusually fast RTs in SPR research are generally around 200 ms for word-by-word presentations (Jegerski, 2016; Jiang, 2007; Sagarra & Herschensohn, 2010). However, they can be 100 ms (Kim, 2018; Leal, Slabakova, & Farmer, 2017; Litcofsky & Van Hell, 2017), or even as low as 40 or 50 ms (Cook, 2018; Frank, Trompenaars, & Vasishth, 2016), despite research suggesting 100 ms as a minimum to respond to the identity of a signal (Luce, 1991). Rather than rely on conventions, some researchers provide research-driven justifications to determine a cutoff.…”
Section: Outlier Detection and Treatmentmentioning
confidence: 99%