Linguistic and non-linguistic cues to acquiring the strong distributivity of <em>each</em>

Abstract

The universal quantifier each is more strongly distributive than its counterparts every and all. It forces predicates to apply to individuals, it more often supports pair-list readings, it’s unfriendly to genericity, and, in psycholinguistic tasks, it encourages encoding and remembering individual properties. But what information leads learners to acquire this aspect of em&gt;each’s meaning? We explore the hypothesis that, because of its meaning, parents are more likely to use each in situations that independently promote representing the domain of quantification as a series of individuals (as opposed to a group). In line with this, we find that in child-directed speech, parents often use each to quantify over small numbers of physically present things. The same cannot be said of every and all. Because such situations are independently known to trigger object-files – the mind’s system for representing individuals – we argue that these cases are ideal for acquiring the individualistic aspect of each.

Cross-linguistic comparisons on distributive universal quantification: <i>Each</i> vs. <i>every</i> vs. <i>mei</i>

“…And when asked to imagine the size of the domain, participants given a sentence in which DUQ is indicated with each reliably offer estimates of two or three items; participants given a matched sentence using every more often offer estimates of far higher cardinalities. Knowlton & Gomes (2022) show that this same pattern emerges in naturalistic speech to children: parents use each to quantify over small numbers of physically present things far more often than they do so with every or all. This set size difference is a wellknown signature of the difference between using the cognitive systems for individuation and for grouping: the system for individuation builds high-fidelity representations, and is thus subject to stricter working memory constrains.…”

“…We briefly summarize these results before asking how they might be captured under the DVH/STH. Knowlton et al (2022) presented participants with scenes consisting of circles of various colors and sizes and asked them to evaluate simple sentences like each big circle is blue and every big circle is blue. After answering these questions, participants were then asked to recall how many circles there were, a property that holds of the group as a whole and not of any one individual circle.…”

Quantifying events or entities?—A corpus-based study of universal quantifiers in early child English and child-directed speech

“…All QNPs containing each basically appear in subject/object position, while most QNPs containing every appear in adverbials; the vast majority of each quantify the individual entity, while the majority of every quantify the time. Knowlton and Gomes (2022) further confirmed the distinction by analyzing the videos of parent-child interactions in a corpus: parents often use each to quantify over entities physically present in small numbers, use all to quantify over domains that are larger than children's working memory capacity, and use every to quantify over times or individuals that are not present.…”

“…It is the development of the ability to count and compute concrete entities that get children from A- to D-quantification. Parents use each to quantify entities physically present in small numbers but use every to quantify over times or individuals that are not present (Knowlton & Gomes, 2022). This contrast is also found in our child data.…”

The Binding Problem 2.0: Beyond Perceptual Features

“…In the course of evolution, did the binding of conceptual features to indexicals emerge together with the concepts themselves? How might the language system have impacted the indexical system(s) across the course of evolution, and what is the nature of their interface in modern humans (Knowlton & Gomes, 2022)? Many more such questions, demanding the collective forces of subfields across the cognitive sciences, remain to be asked and solved within Binding Problem 2.0.…”