Contesting language policy for asylum seekers in the Northern periphery: The story of Tailor F

This article is about navigating asylum, employment and language policy in a new country as an asylum seeker. Through the story of one individual, we show that profound inequalities are exacerbated when forced migrants are limited in their choice of language they might study or use. The individual is Tailor F, an Iraqi man seeking asylum, and the country is Finland, officially bilingual, with a majority language (Finnish) and a minority language (Swedish). Finland’s official bilingualism does not extend evenly to language education provided for asylum seekers, who are taught Finnish regardless of the region where they are placed. Upon arrival, Tailor F was housed in a reception centre for asylum seekers located in a Swedish-dominant rural area of the country. Through our linguistic ethnography we examine how he navigates multilingually in his early settlement, his current work and his online life. We relate his story to explicit and implicit official bilingualism in Finland and discuss his lived experiences in relation to the contexts of asylum policy and employment. Tailor F’s story shows how, through his practices, he has contested implicit language policy for asylum seekers in order to gain membership of the local Swedish-dominant community, achieve a sense of belonging, and potentially realise his aspirations for the future

Keyness: Appropriate metrics and practical issues

In this paper we examine the definitions of two widely-used interrelated constructs in corpus linguistics, keyness and keywords, as presented in the literature and corpussoftware manuals. In particular, we focus on \u2022 the consistency of definitions given in different sources; \u2022 the metrics used to calculate the level of keyness; \u2022 the compatibility between definitions and metrics Our survey of studies employing keyword analysis has indicated that the vast majority of studies examine a subset of keywords \u2013 almost always the top X number of keywords as ranked by the metric used. This renders the issue of the appropriate metric central to any study using keyword analysis.In this study, we first argue that an appropriate, and therefore useful, metric for keyness needs to be fully consistent with the definition of keyword. We then use four sets of comparisons between corpora of different types and sizes, in order to test whether and to what extent the use of different metrics affects the ranking of keywords. More precisely, we look at the extent of overlap in the keyword rankings resulting from the adoption of different metrics, and we discuss the implications of ranking-based analysis adopting one metric or another. Finally, we propose a new metric for keyness , and demonstrate a simple way to calculate the metric, which supplements the keyword extraction in existing corpus software

A useful methodological synergy? Combining critical discourse analysis and corpus linguistics to examine discourses of refugees and asylum seekers in the UK press

This article discusses the extent to which methods normally associated with corpus linguistics can be effectively used by critical discourse analysts. Our research is based on the analysis of a 140-million-word corpus of British news articles about refugees, asylum seekers, immigrants and migrants (collectively RASIM). We discuss how processes such as collocation and concordance analysis were able to identify common categories of representation of RASIM as well as directing analysts to representative texts in order to carry out qualitative analysis. The article suggests a framework for adopting corpus approaches in critical discourse analysis

Using corpora to foster L2 construction learning: A data‐driven learning experiment

This paper adopts a Construction Grammar approach to test the efficiency of data-driven learning (DDL) when applied to constructions. High-intermediate learners of English as a foreign language took part in an experiment consisting, for each construction, in (i) a pre-test, in which the learners had to produce as many sentences as possible illustrating the constructions, (ii) a DDL intervention, which involved various concordance-based activities, and (iii) several post-tests, similar to the pre-test, performed at regular intervals. The analysis looks at the number of (valid and invalid) constructions produced as well as the native-like nature of these constructions, as established through a comparison with native corpus data. The analysis also examines the evolution of these results over the different post-tests. Finally, it considers learners’ attitudes towards the DDL interventions, as evaluated through a questionnaire