How do speakers design what they say in order to communicate effectively with groups of addressees who vary in their background knowledge of the topic at hand? Prior findings indicate that when a speaker addresses a
- Award ID(s):
- 1911835
- NSF-PAR ID:
- 10285683
- Date Published:
- Journal Name:
- Proceedings of the Annual Conference of the Cognitive Science Society
- ISSN:
- 1069-7977
- Page Range / eLocation ID:
- 2232-2238
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract pair of listeners with discrepant knowledge, that speakersAim Low , designing their utterances for the least knowledgeable of the two addressees. Here, we test the hypothesis that speakers will depart from anAim Low approach in order to efficiently communicate with larger groups of interacting partners. Further, we ask whether the cognitive demands of tracking multiple conversational partners' perspectives places limitations on successful audience design. We find that speakers can successfully track information about what up to four of their partners do and do not know in conversation. When addressing groups of 3–4 addressees at once, speakers design language based on the combined knowledge of the group. These findings point to an audience design process that simultaneously represents the perspectives of multiple other individuals and combines these representations in order to design utterances that strike a balance between the different needs of the individuals within the group. -
We provide an overview and update on initiatives and approaches to add taxonomic data intelligence to distributed biodiversity knowledge networks. "Taxonomic intelligence" for biodiversity data is defined here as the ability to identify and renconcile source-contextualized taxonomic name-to-meaning relationships (Remsen 2016). We review the scientific opportunities, as well as information-technological and socio-economic pathways - both existing and envisioned - to embed de-centralized taxonomic data intelligence into the biodiversity data publication and knowledge intedgration processes. We predict that the success of this project will ultimately rest on our ability to up-value the roles and recognition of systematic expertise and experts in large, aggregated data environments. We will argue that these environments will need to adhere to criteria for responsible data science and interests of coherent communities of practice (Wenger 2000, Stoyanovich et al. 2017). This means allowing for fair, accountable, and transparent representation and propagation of evolving systematic knowledge and enduring or newly apparent conflict in systematic perspective (Sterner and Franz 2017, Franz and Sterner 2018, Sterner et al. 2019). We will demonstrate in principle and through concrete use cases, how to de-centralize systematic knowledge while maintaining alignments between congruent or concflicting taxonomic concept labels (Franz et al. 2016a, Franz et al. 2016b, Franz et al. 2019). The suggested approach uses custom-configured logic representation and reasoning methods, based on the Region Connection Calculus (RCC-5) alignment language. The approach offers syntactic consistency and semantic applicability or scalability across a wide range of biodiversity data products, ranging from occurrence records to phylogenomic trees. We will also illustrate how this kind of taxonomic data intelligence can be captured and propagated through existing or envisioned metadata conventions and standards (e.g., Senderov et al. 2018). Having established an intellectual opportunity, as well as a technical solution pathway, we turn to the issue of developing an implementation and adoption strategy. Which biodiversity data environments are currently the most taxonomically intelligent, and why? How is this level of taxonomic data intelligence created, maintained, and propagated outward? How are taxonomic data intelligence services motivated or incentivized, both at the level of individuals and organizations? Which "concerned entities" within the greater biodiversity data publication enterprise are best positioned to promote such services? Are the most valuable lessons for biodiversity data science "hidden" in successful social media applications? What are good, feasible, incremental steps towards improving taxonomic data intelligence for a diversity of data publishers?more » « less
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Abstract The common ground that conversational partners share is thought to form the basic context for language use. According to the classic view, inferences about common ground, or mutual knowledge, are guided by beliefs about the physical, cognitive, and attentional states of one's communicative partners. Here, we provide a first test of the
attention assumption for common ground, the proposal that common ground for a co‐present entity—such as an object or an utterance—can only be formed if a person has evidence that his or her partner has also attended to it. In three experiments, a participant speaker and two partners learned names for novel monster pictures as a group. The speaker was then asked to describe the monsters to each partner separately in a referential communication task. The critical manipulation was the (in)attentiveness of one partner at different points in the study. Analysis of the speaker's referring expressions revealed that speakers assumed their partner shared common ground for the monster names only when that partner exhibited engaged attention as the names were learned. These findings provide key and novel support for the classic proposal that formation of common ground critically depends on assumptions about the attentional state of one's conversational partner. -
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Abstract The world is facing a crisis of language loss that rivals, or exceeds, the rate of loss of biodiversity. There is an increasing urgency to understand the drivers of language change in order to try and stem the catastrophic rate of language loss globally and to improve language vitality. Here we present a unique case study of language shift in an endangered Indigenous language, with a dataset of unprecedented scale. We employ a novel multidimensional analysis, which allows the strength of a quantitative approach without sacrificing the detail of individual speakers and specific language variables, to identify social, cultural, and demographic factors that influence language shift in this community. We develop the concept of the ‘linguatype’, a sample of an individual’s language variants, analogous to the geneticists’ concept of ‘genotype’ as a sample of an individual’s genetic variants. We use multidimensional clustering to show that while family and household have significant effects on language patterns, peer group is the most significant factor for predicting language variation. Generalized linear models demonstrate that the strongest factor promoting individual use of the Indigenous language is living with members of the older generation who speak the heritage language fluently. Wright–Fisher analysis indicates that production of heritage language is lost at a significantly faster rate than perception, but there is no significant difference in rate of loss of verbs vs nouns, or lexicon vs grammar. Notably, we show that formal education has a negative relationship with Indigenous language retention in this community, with decreased use of the Indigenous language significantly associated with more years of monolingual schooling in English. These results suggest practical strategies for strengthening Indigenous language retention and demonstrate a new analytical approach to identifying risk factors for language loss in Indigenous communities that may be applicable to many languages globally.
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Aims and objectives: This paper describes the multilingualism patterns practiced in the Zauzou community, a small ethnic group in Southwestern China. Zauzou is in contact with Lisu, Bai, Lama, and Mandarin Chinese. The present study aims to characterize the relationship between the social/linguistic factors including age, second language (L2), types of code-alternation, and the multilingualism patterns in this community.
Design/methodology/approach: Self-reports and participant observation were used to discover any recurrent multilingualism patterns regulated by social/linguistic factors.
Data and analysis: Self-reported data on Zauzou speakers’ language repertoire and language use were collected by means of demographic survey. Code-alternation between Zauzou and different L2s were collected from systematic linguistic fieldwork.
Findings/conclusions: Zauzou is the dominant language in intragroup multilingualism, while intergroup multilingualism is dominated by Zauzou speakers’ L2s. Zauzou speakers exhibit a shift from the local multilingualism toward Mandarin-Zauzou bilingualism. The two patterns can be characterized by speakers’ age, L2, and the type of code-alternation. Zauzou-Mandarin bilingualism is realized as both code-mixing and code-switching, and is pervasive among the younger generation, while multilingualism is realized as code-switching and is dominant among older speakers. This shift is due to the new market economy and the language policy that promotes Mandarin in the whole area.
Originality: This study presents naturalistic data on multilingualism practices in a small minority group in China, which is overlooked by most linguistic descriptions and sociolinguistic studies of lesser-studied languages in China.
Significance/implications: This paper discovers three parameters to define two cross-linguistic multilingualism patterns in small indigenous societies: the local multilingualism and the national bilingualism, and the shift toward bilingualism that directly results from language policy and economy.
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