期刊动态 | 语料库语言学SSCI期刊IJCL2022年第3期目录与摘要

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语料库SSCI期刊

IJCL

订阅International Journal of Corpus Linguistics一年4期电子账户956元，可以开具发票，支持对公转账。订阅联系人王老师13501892122

2022年第3期IJCL目录

Lectal contamination: Evidence from corpora and from agent-based simulation

Dirk Pijpops | pp. 259–290

摘要：This paper presents evidence from both corpora and agent-based simulation for the effect of lectal contamination. By doing so, it shows how agent-based simulation can be used as a complementary technique to corpus research in the study of language variation. Lectal contamination is an effect whereby the words that are typical of a language variety more often appear in a morphosyntactic variant typical of that same variety, even among language use from a different variety. This study looks at the Dutch partitive genitive construction, which exhibits variation between a “Netherlandic” variant with -s ending and a “Belgian” variant without -s ending. It is shown that the probability of the Belgian variant without -s increases among more “Belgian” words, in the language use of both Belgians and people from the Netherlands. Meanwhile, an agent-based simulation reveals the crucial theoretical preconditions that lead to this effect.

Handle it in-house? Learner corpora frequency lists and lexical sophistication

Ben Naismith, Alan Juffs, Na-Rae Han, and Daniel Zheng | pp. 291–320

摘要:Vocabulary lists of high-frequency lexical items are an important resource in language education and a key product of corpus research. However, no single vocabulary list will be useful for every learning context, with the appropriateness of such lists affected by the corpora on which they are based. This paper investigates the impact of corpus selection on one measure of lexical sophistication, Advanced Guiraud, focusing on two frequency lists originating from an in-house learner corpus (PELIC) and a global learner corpus (Cambridge Learner Corpus). This analysis shows that frequency lists derived from both types of learner corpus can effectively serve as the basis for measuring the development of lexical sophistication, regardless of the specific program of the learners. Therefore, publicly available learner corpus frequency lists can be a reliable resource for stakeholders interested in the lexical gains of language learners.

Exploring the impact of lexical context on word association responses

Peter Thwaites | pp. 321–348

摘要：In word association tasks, participants respond with the first word that comes to mind on seeing a given cue. These responses are generally assumed to be influenced by a number of factors, including cue semantics, form, and textual distribution. Previous studies exploring the third of these influences have used pairwise association measures, such as mutual information, to evaluate the extent to which textual distributions influence response selection. In the current paper, a different approach is taken. Rather than examining co-occurrences between a cue and its observed responses, this paper explores the possibility that the cue’s holistic collocational environment shapes its associative profile. Regression modelling demonstrates that the predictability of this textual distribution is a significant predictor of variance in the cue’s response profile. Overall, however, the amount of variance explained is small. A subsequent qualitative examination of distributional and associative profiles suggests several semantically based constraints to response generation.

Use words, not constructions! A new perspective on the unit of analysis in collostructional analysis

Thomas Proisl | pp. 349–379

摘要：The aim of collostructional analysis or, more precisely, simple collexeme analysis, is to quantify the statistical association between a construction c and a lexeme l that occurs in a particular slot of the construction. The analysis is based on 2×2 contingency tables that ought to represent a cross-classification of the units of analysis. So far, the units of analysis have been identified either as all constructions in the corpus or all instances of a class C of constructions to which construction c belongs. In practice, it is often not possible or feasible to identify these constructions. Therefore, the sample size is typically approximated by heuristic estimates. The bottom-right cell of the contingency table is most affected by these approximations. I suggest that the units of analysis be defined on the word level, instead, as the class W of word forms that satisfy the restrictions on the collexeme slot of c.

BOOK REVIEWS

Egbert, J. & Baker, P. (Eds.) (2019). Using Corpus Methods to Triangulate Linguistic Analysis. Routledge

Reviewed by Laurence Anthony | pp. 380–385

Carrió-Pastor, M. L. (Ed.) (2020). Corpus Analysis in Different Genres: Academic Discourse and Learner Corpora. Routledge

Reviewed by Shuqiong Wu | pp. 386–392

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