{"title":"The Lexicogrammatical Profile of Non-agentive Deverbal -er Nominals: A Usage-based Approach","authors":"Pilar Guerrero Medina, Macarena Palma Gutiérrez","doi":"10.14198/raei.2023.39.04","DOIUrl":null,"url":null,"abstract":"In this paper we analyse the lexicogrammatical profile of 30 non-agentive deverbal -er nominalisations, showing that the different semantic types that middle structures instantiate in Heyvaert’s (2003) usage-based classification (i.e., facility-, quality-, feasibility-, destinyand result-oriented) can be systematically found among the non-agentive -er nominals in our corpus. Following Lemmens (1998) and Heyvaert (2001, 2003), we believe that a detailed analysis of the type of base verbs used in deverbal -er formations is necessary to provide a more accurate classification on a lexicogrammatical basis. A basic distinction is thus made between -er nominals that profile patientive participants and -er nominals that designate circumstantial participants. Patientive nominalisations include Goal-profiling derivations based on transitive verbs, such as Freerider or scratcher, as well as Medium-profiling formations derived from ergative verbs, such as best-seller, top-seller and broiler, where the profiled entities can be said to co-participate in the process. Circumstantial nominalisations (mostly derived from intransitive verbs) include Location-profiling formations, like two-seater or bed-sitter, and Instrumental-profiling formations, such as baby jumper or tourer. We have conducted a qualitative corpus-based analysis in order to examine the lexico-semantic and lexico-paradigmatic profile of 30 deverbal -er nominalisations in present-day English. Using the Concordance section of Sketch Engine in the enTenTen20 corpus, we have been able to retrieve a total of 2,847 contextualised examples, including agentive and non-agentive instantiations.","PeriodicalId":33428,"journal":{"name":"Revista Alicantina de Estudios Ingleses","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Alicantina de Estudios Ingleses","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14198/raei.2023.39.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CULTURAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper we analyse the lexicogrammatical profile of 30 non-agentive deverbal -er nominalisations, showing that the different semantic types that middle structures instantiate in Heyvaert’s (2003) usage-based classification (i.e., facility-, quality-, feasibility-, destinyand result-oriented) can be systematically found among the non-agentive -er nominals in our corpus. Following Lemmens (1998) and Heyvaert (2001, 2003), we believe that a detailed analysis of the type of base verbs used in deverbal -er formations is necessary to provide a more accurate classification on a lexicogrammatical basis. A basic distinction is thus made between -er nominals that profile patientive participants and -er nominals that designate circumstantial participants. Patientive nominalisations include Goal-profiling derivations based on transitive verbs, such as Freerider or scratcher, as well as Medium-profiling formations derived from ergative verbs, such as best-seller, top-seller and broiler, where the profiled entities can be said to co-participate in the process. Circumstantial nominalisations (mostly derived from intransitive verbs) include Location-profiling formations, like two-seater or bed-sitter, and Instrumental-profiling formations, such as baby jumper or tourer. We have conducted a qualitative corpus-based analysis in order to examine the lexico-semantic and lexico-paradigmatic profile of 30 deverbal -er nominalisations in present-day English. Using the Concordance section of Sketch Engine in the enTenTen20 corpus, we have been able to retrieve a total of 2,847 contextualised examples, including agentive and non-agentive instantiations.