Restrictions on the Meaning of Determiners: Typological Generalisations and Learnability

Hunter, Tim B.; Lidz, Jeffrey; Wellwood, Alexis; Conroy, Anastasia

doi:10.3765/salt.v0i0.2531

Cited by 3 publications

(3 citation statements)

References 7 publications

(9 reference statements)

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“…However, the structure of this distribution, which reflects cognitive biases, might be restricted in ways that shorten time to convergence. For example, if certain structures are unlearnable (as discussed in, e.g., Hunter, Lidz, Wellwood, & Conroy, 2010;Pinker & Jackendoff, 2009), then the number of possible languages is effectively decreased, lowering time to convergence.…”

Section: Future Workmentioning

confidence: 99%

Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor

2014

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Analyzing the rate at which languages change can clarify whether similarities across languages are solely the result of cognitive biases or might be partially due to descent from a common ancestor. To demonstrate this approach, we use a simple model of language evolution to mathematically determine how long it should take for the distribution over languages to lose the influence of a common ancestor and converge to a form that is determined by constraints on language learning. We show that modeling language learning as Bayesian inference of n binary parameters or the ordering of n constraints results in convergence in a number of generations that is on the order of n log n. We relax some of the simplifying assumptions of this model to explore how different assumptions about language evolution affect predictions about the time to convergence; in general, convergence time increases as the model becomes more realistic. This allows us to characterize the assumptions about language learning (given the models that we consider) that are sufficient for convergence to have taken place on a timescale that is consistent with the origin of human languages. These results clearly identify the consequences of a set of simple models of language evolution and show how analysis of convergence rates provides a tool that can be used to explore questions about the relationship between accounts of language learning and the origins of similarities across languages.

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Section: Future Workmentioning

confidence: 99%

Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor

2014

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“…To concretize the problem, suppose that the end result of understanding There are more apples than bananas is the LoT expression “A > B” and that of There is more sand than mud is “S > M.” Specifically, what's required is a specification of (i) how the single symbol “>” (Wellwood, 2019) can be interpreted by cognitive systems operating both over domains representing pluralities of objects and those representing stuff (Odic, Pietroski, Hunter, Lidz, & Halberda, 2012; see Rips & Hespos, 2015), and (ii) the logical relationships that an LoT expression enters into by virtue of being built around this symbol in a certain way (e.g., via proof-theoretic inference rules). We have suggested (Hunter & Wellwood, 2023) that for a nonlinguistic system to interpret a symbol such as “>” in the appropriate way is exactly for this interpretation to abide by some algebraic laws that are, in effect, specified by some inference rules governing expressions built out of “>.” For example, a rule licensing a logical inference from “A > B” and “B > C” to “A > C” essentially specifies that, in each content domain where “>” has an interpretation, that interpretation must correspond to a transitive binary relation.…”

mentioning

confidence: 99%

“…6.2, para. 5), is to suppose that the outputs of (specifically linguistic) language comprehension simply are LoT expressions (e.g., Hunter & Wellwood, 2023; Wellwood, 2020). On the contrary, the pathway from associationistic learning episodes to such representations is rather less direct.…”

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confidence: 99%

Linguistic meanings in mind

Wellwood,

Hunter

2023

Behav Brain Sci

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The target article focuses on evidence from nonlinguistic faculties to defend the claim that cognition generally traffics in language-of-thought (LoT)-type representations. This focus creates needed space to discuss the mounting accumulation of nonclassical evidence for LoT, but it also misses relevant work in linguistics that directly offers a perspective on specific hypotheses about candidate LoT representations.

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Default meanings: language’s logical connectives between comprehension and reasoning

Lobina

Demestre

Garcı́a-Albea

et al. 2022

Linguist and Philos

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Language employs various coordinators to connect propositions, a subset of which are “logical” in nature and thus analogous to the truth operators of formal logic. We here focus on two linguistic connectives and their negations: conjunction and and (inclusive) disjunction or. Linguistic connectives exhibit a truth-conditional component as part of their meaning (their semantics), but their use in context can give rise to various implicatures and presuppositions (the domain of pragmatics) as well as to inferences that go beyond semantic/pragmatic properties (the result of reasoning processes). We provide a comprehensive review of the role of the logical connectives in language and argue that three sets of factors—semantic, pragmatic, and those related to reasoning—are separate and separable, though some details may differ cross-linguistically. As a way to showcase the argument, we present two experiments in language comprehension in Spanish wherein pragmatic content was minimised and reasoning processes neutered, thus potentially highlighting what might be the default meanings of the connectives under study. In Experiment 1 we show that the conjunctive reading of inclusive disjunction is available in positive contexts other than in syntactically intricate cases such as downward entailing and free choice contexts, contrary to what has been claimed in the literature. In Experiment 2 we show that negated conjunctions and disjunctions in Spanish can easily receive the same interpretation when contrasted against the same context and, moreover, that these interpretations match those available in English, despite claims from the literature that linguistic connectives and local negation interact differently in English and Romance languages.

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Restrictions on the Meaning of Determiners: Typological Generalisations and Learnability

Abstract: No abstract.

Cited by 3 publications

References 7 publications

Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor

Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor

Linguistic meanings in mind

Default meanings: language’s logical connectives between comprehension and reasoning

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