UNIVERSITY OF COLOGNE

Variation between BE- and GET-passives (examples 1 and 2) is a well-attested phenomenon (Hundt et al. 2024; Fehringer 2022; Schwarz 2015, 2017; Collins 1996) and has even been described as “one of the most active grammatical changes taking place in English” (Weiner & Labov 1983). Yet, large-scale, quantitative studies of this variable have been lacking until recently. This is due to difficulties in formally circumscribing the variable context (true passives as opposed to formally identical structures like statal or inchaotive expressions as in examples 3 and 4) as well as operationalizing some of the hypothesized constraints on the variation, such as the alleged adversativity for and responsibility of the subject.

1. I applied, but was not invited for an interview.
2. I applied, but did not get invited for an interview.
3. Kim is excited to join the team.
4. Kelly got exhausted playing two games back to back.

In this talk, I outline some of these challenges and present methodological solutions to scale up quantitative analysis of the English passive alternation using large corpora. Based on recent collaborative work (Bohmann et al. 2023, fc.), I present an automated approach towards delineating central passives from non-central (stative, inchoative, etc.) constructions and methods for operationalizing adversativity through sentiment analysis and subject responsibility through automatic animacy detection. Based on 1.4 million instances of the passive alternation sampled from the Corpus of Historical American English (Davies 2010), a robust but receding effect of subject responsibility can be observed. However, rather than adversativity it appears to be non-neutrality of emotion (whether negative or positive) that predicts higher rates of GET-passives. Beyond the immediate case study, this talk makes a case for adoption of tools from data science for the study of linguistic variation.

References:

• Bohmann, Axel, Julia Müller, Mirka Honkanen, Miriam Neuhausen. 2023. “A Large-scale Diachronic Analysis of the English Passive Alternation.” In Beatrix Busse, Nina Dumrukcic and Ingo Kleiber (eds), Language and Linguistics in a Complex World, 31-56. Berlin: de Gruyter.
• Bohmann, Axel, Julia Müller, Mirka Honkanen, Miriam Neuhausen. Forthcoming. Linguistic Data Science and the English Passive. [Language, Data Science and Digital Humanities]. Bloomsbury.
• Collins, Peter C. 1996. “Get-passives in English.” In: World Englishes 15, 43–56.
• Davies, Mark. 2010. Corpus of Historical American English. www.english-corpora.org/coha.
• Fehringer, Carol. 2022. “The Get-passive in Tyneside English: A Highly Frequent yet Constrained Variant.” English World-Wide, 43(3): 330-356.
• Hundt, M., Dallas, B., & Nakanishi, S. (2024). “The Be- Versus Get-passive Alternation in World Englishes. World Englishes, 43, 86–108.
• Schwarz, Sarah 2015. “Passive voice in American soap opera dialogue.” In: Studia Neophilologica 87, 152–170.
• Schwarz, Sarah. 2017. “‘Like getting nibbled to death by a duck’: Grammaticalization of the get-passive in the TIME Magazine Corpus.” In: English World-Wide 38, 305–335.

For over a century, language has been considered as an amodal and arbitrary system with a primary modality of speech. Yet, as argued in our book A Multimodal Language Faculty (Cohn & Schilperoord 2024), this conception of language cannot account for many of the basic observations revealed in the past decades of language research, particularly the growing recognition of the importance of multimodality. I will present a multimodal model of language that accounts for all unimodal behaviors across the vocal, bodily, and graphic modalities along with their multimodal combinations. This “grand unified” model directly allows for semiotic promiscuity across iconicity, indexicality, and symbolicity, while warranting new understandings of linguistic innateness, relativity, universals, and evolution. Altogether, this approach heralds a shift to a Multimodal Paradigm of the language sciences, re-imagining both its cognitive faculty and the notion of “language” itself.