Nominal constructions in spoken academic Englishes: A quantitative corpus-based approach
-
Anatol Stefanowitsch
,
Kirsten Middeke
Abstract
Academic English was traditionally treated as a monolithic register with respect to grammar, but recent research has shown that there is considerable variation across modes, dialects, research traditions and disciplines. We apply two quantitative corpus-linguistic methods (keyword analysis and a variant using PoS-grams instead of words) to investigate noun-noun and adjective-noun sequences in two discipline-specific Academic Englishes, that of the Arts and Humanities and that of the Physical Sciences. We show that the function of the various constructions underlying these sequences are exploited in different ways in these discipline clusters, in accordance with specific communicative needs. In the Physical Sciences, there is a need for standardized terminology. Noun-noun compounds are the preferred strategy for creating this terminology, with a specific adjective-noun construction involving relational adjectives playing a minor part and syntactic adjective-noun constituents playing no particular role. In the Arts and Humanities, there is a need for precise ad-hoc descriptions, and syntactic adjective-noun constituents are the preferred way of doing so. This difference accounts for the previously observed distribution, confirmed in our study, that noun-noun sequences are more typical for the natural sciences and adjective-noun sequences are more typical for the humanities.
Author statement
Funding information. The authors state no funding involved.
Author’s contribution (CRediT). Anatol Stefanowitsch: Concepuatlization (equal), Methodology (lead), Software (lead), Validation (equal), Formal Analysis (lead), Investigation (equal), Resources (supporting), Data Curation (equal), Writing — original draft (Sections 2.2, 2.3, 3.1, 3.2, 4), Writing — review & editing (lead), Project administration (equal); Visualization. Kirsten Middeke: Conceptualization (equal), Methodology (supporting), Validation (equal), Formal analysis (supporting), Investigation (equal), Data curation (equal), Writing — original draft (Sections 1, 2.1, 2.3, 3.2), Writing — review and editing (support), Project administration (equal). Fuying Lin: Conceptualization (supporting), Software (supporting), Resources (lead), Data curation (supporting), Investigation (supporting), Writing — original draft (Section 2.1). N/A: Supervision, Funding acquisition.
Conflict of interest. The authors state no conflict of interest.
Data Availability. The datasets generated and analyzed during the current study are available online (see below); any data not found there are available from the corresponding author on reasonable request.
Acknowledgments
We applied the SDC approach for the sequence of authors.
Online Supplementary Materials
Supplementary materials can be found online at https://osf.io/xsrz5/
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Articles in the same Issue
- Frontmatter
- Editorial: Constructions under construction: Items, patterns, grammar
- Constructicon in progress
- Multi-Dimensional Regularity Analysis: How the Entrenchment-and-Conventionalization Model can be applied to corpus data
- Lexical knowledge, memory and experience
- Nominal constructions in spoken academic Englishes: A quantitative corpus-based approach
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Articles in the same Issue
- Frontmatter
- Editorial: Constructions under construction: Items, patterns, grammar
- Constructicon in progress
- Multi-Dimensional Regularity Analysis: How the Entrenchment-and-Conventionalization Model can be applied to corpus data
- Lexical knowledge, memory and experience
- Nominal constructions in spoken academic Englishes: A quantitative corpus-based approach
- Causative constructions in process: How do they come into existence in learner writing?
- “I’m gonna get totally and utterly X-ed.” Constructing drunkenness
- The German geschweige denn construction
- A reference constructicon as a database
- Dimensions of constructional meanings in the German Constructicon: Why collo-profiles matter
