Evidence map›Paper›PMID 38597678›Full record

ArticleDevelopmental science2024

When is a word in good company for learning?

Layla Unger, Tyler Chang, Olivera Savic, Benjamin K Bergen, Vladimir M Sloutsky

Abstract read
In one paragraph

Article in Developmental science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Layla UngerDepartment of Psychology, University of York, York, UK.ORCID https://orcid.org/0000-0002-8888-1265
Tyler ChangDepartment of Cognitive Science, University of California San Diego, San Diego, California, USA.
Olivera SavicBasque Center on Cognition, Brain and Language, San Sebastian, Spain.
Benjamin K BergenDepartment of Cognitive Science, University of California San Diego, San Diego, California, USA.
Vladimir M SloutskyDepartment of Psychology, The Ohio State University, Columbus, Ohio, USA.

Funding

ONTOGENESIS OF CATEGORIZATION: LINKING DEVELOPMENT, MECHANISMS, AND BIOLOGYP01HD080679 · NICHD · OHIO STATE UNIVERSITY · PI SLOUTSKY, VLADIMIR M · 2016 to 2020
$5.8M
The Development of CategorizationR01HD078545 · NICHD · OHIO STATE UNIVERSITY · PI SLOUTSKY, VLADIMIR M · 2014 to 2025
$4.7M
BCBL Severo Ochoa excellence accreditation CEX2020-001010-SBERC 2022-2025 programMarie Skłodowska-Curie 101063306NICHD NIH HHS P01 HD080679NICHD NIH HHS R01 HD078545NIH HHS P01HD080679NIH HHS R01HD078545UCSD HDSI graduate fellowship
6 · The paper itself

Abstract

Although identifying the referents of single words is often cited as a key challenge for getting word learning off the ground, it overlooks the fact that young learners consistently encounter words in the context of other words. How does this company help or hinder word learning? Prior investigations into early word learning from children's real-world language input have yielded conflicting results, with some influential findings suggesting an advantage for words that keep a diverse company of other words, and others suggesting the opposite. Here, we sought to triangulate the source of this conflict, comparing different measures of diversity and approaches to controlling for correlated effects of word frequency across multiple languages. The results were striking: while different diversity measures on their own yielded conflicting results, once nonlinear relationships with word frequency were controlled, we found convergent evidence that contextual consistency supports early word learning. RESEARCH HIGHLIGHTS: The words children learn occur in a sea of other words. The company words keep ranges from highly variable to highly consistent and circumscribed. Prior findings conflict over whether variability versus consistency helps early word learning. Accounting for correlated effects of word frequency resolved the conflict across multiple languages. Results reveal convergent evidence that consistency helps early word learning.

Indexed as

Language DevelopmentVerbal LearningVocabularyChild LanguageChild, PreschoolFemaleHumansLanguageLearningMalecontext diversitylanguage acquisitionlexical acquisitionword learning

Identifiers

PMID38597678
PMCPMC11333179

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.