Inferring cultural models from corpus data: Force-dynamic cultural models reflected in the discursive behavior of a scalar adjectival construction
DOI:
https://doi.org/10.5278/ojs.globe.v1i0.699Nøgleord:
Cultural Model, Scalar Adjectival Construction, Scalar Image Schema, Force-Dynamic Image SchemaResumé
One of the main tasks in cognitive anthropology is the reconstruction of cultural models, which are behavior-regulating schematic cognitive models that are intersubjectively shared in a community. Given their behavior-regulatory status, cognitive anthropologists and other cognitive scientists have developed methods of inferring cultural models from observed behavior – in particular observed verbal behavior. While there are plenty of studies of the reflection of cultural models in artificially generated verbal behavior, not much research has been made into the possibility of inferring cultural models from naturally occurring verbal behavior as documented in language corpora. Even rarer are such corpus-based studies of the interaction between cultural models and grammatical constructions. Exploring the usability of corpus data and methodology in the observation of constructional discursive behavior, the present paper offers a covarying collexeme analysis of the [too ADJ to V]-construction in the Corpus of Contemporary American English. The purpose is to discover the extent to which its force-dynamic constructional semantics interacts with cultural models. We focus on three instantiations of the contruction – namely, [too young to V], [too proud to V], and [too macho to V] – to see whether there are patterns in their ranges of coattracted verbs that are indicative of force-dynamic relations in cultural models of age, pride, and machismo respectively.
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Articles published in Globe: A Journal of Language, Culture and Communication are following the license Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0). Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License: Attribution - NonCommercial - NoDerivs (by-nc-nd). Further information about Creative Commons