Lexical Input in the Grammatical Expression of Stance: A Collexeme Analysis of the INTRODUCTORY IT PATTERN

Abstract

Previous research on the INTRODUCTORY IT PATTERN unveiled various lexical and grammatical aspects of its use as a grammatical stance device, including the range of the most frequently used adjectival and verbal stance lexemes, associated stance meanings, the most frequent sub-patterns, and the distinct uses in various contextual settings of the pattern. However, the stance meanings of the pattern, which are deeply rooted in the associated lexical resources, are still understudied. This study explores the meanings of the INTRODUCTORY IT PATTERN by referring to the stance meanings of the pattern associated with the adjectival and verbal lexemes that are statistically attracted to the pattern. The research samples were extracted from the British component of the International Corpus of English (ICE-GB). The samples were manually annotated for different stance types and a collexeme analysis was performed to identify the full range of stance lexemes statistically associated with the INTRODUCTORY IT PATTERN (collexemes). The results show that both adjectival and verbal collexemes are statistically and functionally significant for the delivery of discrete stance types/subtypes. Adjectival collexemes are frequently deployed for all four stance types: Epistemic stance, Evaluation stance, Dynamic stance, and Deontic stance, while verbal collexemes are valuable lexical resources for the Epistemic stance, as their use entails modalized evidentiality, pointing to epistemic judgment of the writer-speaker toward events/propositions. Close examination of the use of adjectival and verbal collexemes identified three fundamental meanings of the INTRODUCTORY IT PATTERN. First, the pattern is inherently evaluative as it tends to attract more lexemes with evaluative meanings and associates evaluative meanings with superficially non-evaluative lexemes. Second, it features a scalarized expression of diversified stance types/subtypes, thus, especially reflective of the scalarized semantic feature of stance expression. Third, it connotates an overwhelmingly positive likelihood judgment. The article concludes by discussing the limitations of this study.

Mocking enactments: a case study of multimodal stance-stacking

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“…While the Stance Triangle can be considered as a 'snapshot' of the stance at a given moment in interaction, Iwasaki (2022, p. 15) highlights that "all aspects of the stance activity are in constant motion and emerge across several turns along the temporal trajectory during an interaction". Furthermore, although the Stance Triangle is modality agnostic in theory, traditionally, the focus of stance-taking research has been on lexico-grammatical and to a lesser extent prosodic means (Biber and Finegan, 1989;Couper-Kuhlen, 2012;Wang et al, 2022). Over the past years, interest in multimodal research on stance-taking has increased (Andries et al, 2023).…”

Comparative Corpus-based Study of Evaluative it Patterns in Middle School Learners’ Writing

“…It was found that the evaluative it pattern is typical and representative, and this style is characterized by its frequency of use, evaluation adjectives, and evaluation clause pattern in different registers. Wang Z. et al (2022) explored the significance of the evaluative it pattern with reference to the stance meaning of patterns associated with adjective and verb lexemes. The findings showed that the co-occurrence morphemes of adjectives and verbs were statistically and functionally significant for each stance type/subtype provided.…”

Multimodal stance-taking – A systematic literature review

“…Whereas the large majority of studies have focused on lexico-grammatical means (see e.g. Biber and Finegan, 1989;Du Bois, 2007;Wang et al, 2022) and to a lesser extent prosodic resources (Couper-Kuhlen, 2012) for expressing stance, the stance-taking potential of other embodied resources has only recently attracted systematic attention. This can be explained, at least in part, by a more general multimodal turn in Conversation Analysis (Goodwin, 2000;Deppermann, 2013;Mondada, 2019), usage-based linguistics (Feyaerts et al, 2017;Perniss, 2018) and other fields.…”