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1. Akuzipik/Yupik (St. Lawrence Island, Alaska, USA; Chukotka, Russia) – Language Snapshot

   Koonooka, Christopher Petuwaq; Schreiner, Sylvia L.R.; Masella Soldati, Giulia; Schwartz, Lane; Hunt, Benjamin; Haas, Preston; Chen, Emily; Park, Hyunji Hayley (December 2021, Language documentation and description)

   Akuzipik (Yupigestun/Yupik/St. Lawrence Island Yupik/Siberian Yupik/Chaplinski Yupik) is an endangered language belonging to the Yupik branch of the Inuit-Yupik-Unangan language family. It is currently spoken by 800-900 people in the Bering Strait region, mainly on St. Lawrence Island, Alaska (St. Lawrence Island Yupik), and on the coast of the Chukotka Peninsula, in Russia (Chaplinski Yupik) (de Reuse 1994; Schwartz et al. 2019). The linguistic differences between these two varieties seem to be minor and not affect mutual intelligibility (Krauss 1975). The language has been undergoing a rapid generational shift, beginning in the 1950s in Russia and in the 1990s in Alaska (Schwartz et al. 2019). 

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2. Akuzipik/Yupik (St. Lawrence Island, Alaska, USA; Chukotka, Russia) - Language Snapshot

   https://doi.org/10.25895/ldd43  

   Koonooka, Christopher Petuwaq; Schreiner, Sylvia L.R.; Soldati, Giulia Masella; Schwartz, Lane; Hunt, Benjamin; Haas, Preston; Chen, Emily; Park, Hyunji Hayley (December 2021, Language documentation and description)

   Akuzipik (Yupigestun/Yupik/St. Lawrence Island Yupik/Siberian Yupik/Chaplinski Yupik) is an endangered language belonging to the Yupik branch of the Inuit-Yupik-Unangan language family. It is currently spoken by 800-900 people in the Bering Strait region, mainly on St. Lawrence Island, Alaska (St. Lawrence Island Yupik), and on the coast of the Chukotka Peninsula, in Russia (Chaplinski Yupik) (de Reuse 1994; Schwartz et al. 2019). The linguistic differences between these two varieties seem to be minor and not affect mutual intelligibility (Krauss 1975). The language has been undergoing a rapid generational shift, beginning in the 1950s in Russia and in the 1990s in Alaska (Schwartz et al. 2019). 

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3. The Actuation Problem

   https://doi.org/10.1146/annurev-linguistics-031120-101336  

   Yu, Alan C (January 2023, Annual Review of Linguistics)

   The actuation problem asks why a linguistic change occurs in a particular language at a particular time and space. Responses to this problem are multifaceted. This review approaches the problem of actuation through the lens of sound change, examining it from both individual and population perspectives. Linguistic changes ultimately actuate in the form of idiolectal differences. An understanding of language change actuation at the idiolectal level requires an understanding of ( a) how individual speaker-listeners’ different past linguistic experiences and physical, perceptual, cognitive, and social makeups affect the way they process and analyze the primary learning data and ( b) how these factors lead to divergent representations and grammars across speakers-listeners. Population-level incrementation and propagation of linguistic innovation depend not only on the nature of contact between speakers with unique idiolects but also on individuals who have the wherewithal to take advantage of the linguistic innovations they encountered to achieve particular ideological projects at any given moment. Because of the vast number of contingencies that need to be aligned properly, the incrementation and propagation of linguistic innovation are predicted to be rare. Agent-based modeling promises to provide a controlled way to investigate the stochastic nature of language change propagation, but a comprehensive model of linguistic change actuation at the individual level remains elusive. 

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4. Socially-guided allocation of attention and the memory encoding of spoken language

   Clapp, William (June 2025, Stanford University Libraries)

   It is now well established that memory representations of words are acoustically rich. Alongside this development, a related line of work has shown that the robustness of memory encoding varies widely depending on who is speaking. In this dissertation, I explore the cognitive basis of memory asymmetries at a larger linguistic level (spoken sentences), using the mechanism of socially guided attention allocation to explain how listeners dynamically shift cognitive resources based on the social characteristics of speech. This dissertation consists of three empirical studies designed to investigate the factors that pattern asymmetric memory for spoken language. In the first study, I explored specificity effects at the level of the sentence. While previous research on specificity has centralized the lexical item as the unit of study, I showed that talker-specific memory patterns are also robust at a larger linguistic level, making it likely that acoustic detail is fundamental to human speech perception more broadly. In the second study, I introduced a set of diverse talkers and showed that memory patterns vary widely within this group, and that the memorability of individual talkers is somewhat consistent across listeners. In the third study, I showed that memory behaviors do not depend merely on the speech characteristics of the talker or on the content of the sentence, but on the unique relationship between these two. Memory dramatically improved when semantic content of sentences was congruent with widely held social associations with talkers based on their speech, and this effect was particularly pronounced when listeners had a high cognitive load during encoding. These data collectively provide evidence that listeners allocate attentional resources on an ad hoc, socially guided basis. Listeners subconsciously draw on fine-grained phonetic information and social associations to dynamically adapt low-level cognitive processes while understanding spoken language and encoding it to memory. This approach positions variation in speech not as an obstacle to perception, but as an information source that humans readily recruit to aid in the seamless understanding of spoken language. 

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5. Improved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology

   Chen, Emily; Park, Hyunji Hayley; Schwartz, Lane (May 2020, LREC proceedings)

   St. Lawrence Island Yupik is an endangered polysynthetic language of the Bering Strait region. While conducting linguistic fieldwork between 2016 and 2019, we observed substantial support within the Yupik community for language revitalization and for resource development to support Yupik education. To that end, Chen & Schwartz (2018) implemented a finite-state morphological analyzer as a critical enabling technology for use in Yupik language education and technology. Chen & Schwartz (2018) reported a morphological analysis coverage rate of approximately 75% on a dataset of 60K Yupik tokens, leaving considerable room for improvement. In this work, we present a re-implementation of the Chen & Schwartz (2018) finite-state morphological analyzer for St. Lawrence Island Yupik that incorporates new linguistic insights; in particular, in this implementation we make use of the Paradigm Function Morphology (PFM) theory of morphology. We evaluate this new PFM-based morphological analyzer, and demonstrate that it consistently outperforms the existing analyzer of Chen & Schwartz (2018) with respect to accuracy and coverage rate across multiple datasets. 

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