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https://doi.org/10.7275/zdg0-0914 

As in many linguistics subfields, studies of prosody have mainly focused on majority languages and dialects and on speakers who hold power in social structures. The goal of this Special Issue is to diversify prosody research in terms of the languages and dialects being investigated, as well as the social structures that influence prosodic variation. The Special Issue brings together prosody researchers and researchers exploring sociological variation in prosody, with a focus on the prosody of marginalized dialects and on prosodic differences based on gender, sexuality, race, and ethnicity. The papers in this volume don’t just advance our understanding of critical issues in sociolinguistics, but they also challenge some of the received wisdom in the exploration of sociolinguistic influences on prosody. Not only does this collection highlight the value of this work to informing theories of prosodic variation and change, but the collected papers also provide examples of methodological innovations in the field that will be valuable for all prosody researchers. 

This paper jointly considers syntactic, semantic, and phonological/phonetic factors in approaching an understanding of BIN, a remote past marker in African American English that has been described as “stressed.” It brings together data from the Corpus of Regional African American Language (CORAAL) and a production study in a small African American English-speaking community in southwest Louisiana to investigate the use and phonetic realization of BIN constructions. Only 20 instances of BIN constructions were found in CORAAL. This sparsity was not simply due to a dearth of semantic contexts for BIN in the interviews, since 122 instances of semantically equivalent been + temporal adverbial variants were also found. These results raise questions about the extent to which BIN constructions and been + temporal adverbial variants are used in different pragmatic and discourse contexts as well as in different speech styles. The production study elicited BIN and past participle been constructions in controlled syntactic and semantic environments. The phonetic realization of BIN was found to be distributed over the entire utterance rather than localized to BIN. BIN utterances were distinguished from past participle been utterances by having higher ratios of fundamental frequency (F0), intensity, and duration in BIN/ been relative to preceding and following material in the utterance. In both studies, BIN utterances were generally realized with a high F0 peak on BIN and a reduced F0 range in the post- BIN region, with variability in the presence and kinds of F0 movements utterance-initially and utterance-finally, as well as in F0 downtrends in the post- BIN region.

 

Work by Green (1998) discusses 3 sub-types of stressed BIN in African American English (AAE): stative, habitual, and completive. BIN constructions that co-occur with temporal adverbials exhibit limited grammaticality, with each sub-type differing in how they interact with these adverbials. Non-BIN constructions that involve multiple instances in the same clause of adverbials of the same class exhibit restrictions that resemble BIN + adverbial data. Drawing on works that analyze BIN as a remote past marker (Rickford 1975, Green 1998) and on works connecting adverbial position to interpretation (Ernst 2020), I argue that BIN is an adverbial itself that situates the initiation of an eventuality in the remote past. This adverbial BIN, in concert with certain combinations of tense and aspect, forms a complex that makes up the canonical BIN construction. 

In this paper, we utilize recent advancements in social media natural language processing to obtain state-of-the-art syntactic dependency parsing results for social media English. We observe performance gains of 3.4 UAS and 4.0 LAS against the previous state-of-the-art as well as less disparity between African-American and Mainstream American English dialects. We demonstrate the computational social scientific utility of this parser for the task of socially embedded entity attribute analysis: for a specified entity, derive its semantic relationships from parses’ rich syntax, and accumulate and compare them across social variables. We conduct a case study on politicized views of U.S. official Anthony Fauci during the COVID-19 pandemic. 

The study of language variation examines how language varies between and within different groups of speakers, shedding light on how we use language to construct identities and how social contexts affect language use. A common method is to identify instances of a certain linguistic feature - say, the zero copula construction - in a corpus, and analyze the feature’s distribution across speakers, topics, and other variables, to either gain a qualitative understanding of the feature’s function or systematically measure variation. In this paper, we explore the challenging task of automatic morphosyntactic feature detection in low-resource English varieties. We present a human-in-the-loop approach to generate and filter effective contrast sets via corpus-guided edits. We show that our approach improves feature detection for both Indian English and African American English, demonstrate how it can assist linguistic research, and release our fine-tuned models for use by other researchers.