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Dictionaries are often a reflection of their time; their respective (socio-)historical context influences how the meaning of certain lexical units is described. This also applies to descriptions of personal terms such as man or woman. Lexicographers have a special responsibility to comprehensively investigate current language use before describing it in the dictionary. Accordingly, contemporary academic dictionaries are usually corpus-based. However, it is important to acknowledge that language is always embedded in cultural contexts. Our case study investigates differences in the linguistic contexts of the use of man and woman, drawing from a range of language collections (in our case fiction books, popular magazines and newspapers). We explain how potential differences in corpus construction would therefore influence the “reality”1 depicted in the dictionary. In doing so, we address the far-reaching consequences that the choice of corpus-linguistic basis for an empirical dictionary has on semantic descriptions in dictionary entries.
Furthermore, we situate the case study within the context of gender-linguistic issues and discuss how lexicographic teams can engage with how dictionaries might perpetuate traditional role concepts when describing language use.
Dictionaries are often a reflection of their time; their respective (socio-)historical context influences how the meaning of certain lexical units is described. This also applies to descriptions of personal terms such as man or woman. Lexicographers have a special responsibility to comprehensively investigate current language use before describing it in the dictionary. Accordingly, contemporary academic dictionaries are usually corpus-based. However, it is important to acknowledge that language is always embedded in cultural contexts. Our case study investigates differences in the linguistic contexts of the use of man and woman, drawing from a range of language collections (in our case fiction books, popular magazines and newspapers). We explain how potential differences in corpus construction would therefore influence the “reality” depicted in the dictionary. In doing so, we address the far-reaching consequences that the choice of corpus-linguistic basis for an empirical dictionary has on semantic descriptions in dictionary entries.Furthermore, we situate the case study within the context of gender-linguistic issues and discuss how lexicographic teams can engage with how dictionaries might perpetuate traditional role concepts when describing language use.
Recent years have seen a growing interest in linguistic phenomena that challenge the received division of labour between lexicon and grammar, and hence often fall through the cracks of traditional dictionaries and grammars. Such phenomena call for novel, pattern based types of linguistic reference works (see various papers in Herbst 2019). The present paper introduces one such resource: MAP (“Musterbank argumentmarkierender Präpositionen”), a web based corpus linguistic patternbank of prepositional argument structure constructions in German. The paper gives an overview of the design and functionality of the MAP prototype currently developed at the Leibniz Institute for the German Language in Mannheim. We give a brief account of the data and our analytic workflow, illustrate the descriptions that make up the resource and sketch available options for querying it for specific lexical, semantic and structural properties of the data.
Recent years have seen a growing interest in linguistic phenomena that challenge the received division of labour between lexicon and grammar, and hence often fall through the cracks of traditional dictionaries and grammars. Such phenomena call for novel, pattern-based types of linguistic reference works (see various papers in Herbst 2019). The present paper introduces one such resource: MAP (“Musterbank argumentmarkierender Präpositionen”), a web-based corpus-linguistic patternbank of prepositional argument structure constructions in German. The paper gives an overview of the design and functionality of the MAP-prototype currently developed at the Leibniz-Institute for the German Language in Mannheim. We give a brief account of the data and our analytic workflow, illustrate the descriptions that make up the resource and sketch available options for querying it for specific lexical, semantic and structural properties of the data.
Less than one percent of words would be affected by gender-inclusive language in German press texts
(2024)
Research on gender and language is tightly knitted to social debates on gender equality and non-discriminatory language use. Psycholinguistic scholars have made significant contributions in this field. However, corpus-based studies that investigate these matters within the context of language use are still rare. In our study, we address the question of how much textual material would actually have to be changed if non-gender-inclusive texts were rewritten to be gender-inclusive. This quantitative measure is an important empirical insight, as a recurring argument against the use of gender-inclusive German is that it supposedly makes written texts too long and complicated. It is also argued that gender-inclusive language has negative effects on language learners. However, such effects are only likely if gender-inclusive texts are very different from those that are not gender-inclusive. In our corpus-linguistic study, we manually annotated German press texts to identify the parts that would have to be changed. Our results show that, on average, less than 1% of all tokens would be affected by gender-inclusive language. This small proportion calls into question whether gender-inclusive German presents a substantial barrier to understanding and learning the language, particularly when we take into account the potential complexities of interpreting masculine generics.
In this article, we provide an insight into the development and application of a corpus-lexicographic tool for finding neologisms that are not yet listed in German dictionaries. As a starting point, we used the words listed in a glossary of German neologisms surrounding the COVID-19 pandemic. These words are lemma candidates for a new dictionary on COVID-19 discourse in German. They also provided the database used to develop and test the NeoRate tool. We report on the lexicographic work in our dictionary project, the design and functionalities of NeoRate, and describe the first test results with the tool, in particular with regard to previously unregistered words. Finally, we discuss further development of the tool and its possible applications.
This paper aims at showing how quantitative corpus linguistic analysis can inform qualitative analysis of digital media discourse with respect to the mediality of language in use. Using the example of protest discourse in Twitter, in the field of anti-Islamic ‘Pegida’ demonstrations, a three-step method of collecting, reducing and interpreting salient data is proposed. Each step is aligned with operative medial features of the microblog: hashtags, retweets and @-interactions. The exemplary analysis reveals the importance of discussions of attendance numbers in protest discourse and the asymmetry between administrative (i.e. the police) and non-administrative discourse agents. Furthermore, it exemplifies how frequency analysis and sequence analysis can be combined for research in media linguistics.