The focus of this chapter is the possible dehumanization or infra-humanization of transgender individuals through grammatical means in the Czech language. This language is rich in these features and uses a grammatical gender for persons (not based on the sex of a subject), as opposed to some, more commonly studied, languages (like English) that mark gender exclusively in pronouns. The research questions concern whether there is any misgendering by morphosyntactic means, and if so, how it is constructed, but also how misgendering is constructed, if not by morphosyntactic means. The material consists of four corpora, one in-group, one out-group, one with news texts and one with online posts of different kinds. To detect cases of misgendering in our corpora the authors look at morphosyntactic alignment within the same clauses as well as in a wider context. The result shows that the neuter pronoun ‘it’, or other neuter misgenderings, are rarely used for trans persons in Czech. Misgendering is constructed mainly by subject–predicate disagreement, but also by predicative nouns such as ‘trans men are women’. When looking for insulting expressions in Czech, the search strategy might thus require complementary parameters compared to e.g. English, enhancing the search for specific morphosyntactic features.

This chapter discusses key grammatical properties of three major classes of nouns in English: common nouns, pronouns, and proper nouns. We demonstrate that the lexical properties of these nouns determine their external syntactic structures. We then examine three types of agreement relationships in English: noun-determiner, pronoun-antecedent, and subject-verb agreement. We observe that the agreement relationship between a noun and its determiner concerns number (NUM) features of the two, while that between a pronoun and its antecedent involves all the three morphosyntactic agreement (AGR) features: person (PER), number (NUM), and gender (GEND). For its part, the subject-verb agreement relationship depends not only on morphosyntactic agreement (AGR) features but also on the semantic index (IND) feature. This hybrid agreement framework offers us a streamlined analysis of mismatches that involve the respective NUM values of subject and verb. The analysis developed here is extended to partitive NPs in English.