Evidence map›Paper›PMID 40228126›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Iconicity as an organizing principle of the lexicon.

Erin E Campbell, Zed Sevcikova Sehyr, Elana Pontecorvo, Ariel Cohen-Goldberg, Karen Emmorey, Naomi Caselli

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed.

  1. Iconicity as an organizing principle of the lexicon.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Article
  3. Article
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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

6 authors.

Erin E CampbellDeaf Center, Boston University, Boston, MA 02215.ORCID 0000-0002-8770-2317
Zed Sevcikova SehyrDepartment of Communication Sciences and Disorders, Chapman University, Orange, CA 92866.ORCID 0000-0001-7912-5428
Elana PontecorvoDeaf Center, Boston University, Boston, MA 02215.ORCID 0000-0002-1340-0121
Ariel Cohen-GoldbergDepartment of Psychology, Tufts University, Medford, MA 02155.
Karen EmmoreySchool of Speech, Language and Hearing Sciences, San Diego State University, San Diego, CA 92182.ORCID 0000-0002-5647-0066
Naomi CaselliDeaf Center, Boston University, Boston, MA 02215.ORCID 0000-0002-6602-4203

Funding

NSF (NSF) 1625761NSF (NSF) 1625793NSF (NSF) 1625954NSF (NSF) 1918252NSF (NSF) 1918261NSF (NSF) 1918556NSF (NSF) 2234786NSF (NSF) 2234787
6 · The paper itself

Abstract

The view that words are arbitrary is a foundational assumption about language, used to set human languages apart from nonhuman communication. We present here a study of the alignment between the semantic and phonological structure (systematicity) of American Sign Language (ASL), and for comparison, two spoken languages-English and Spanish. Across all three languages, words that are semantically related are more likely to be phonologically related, highlighting systematic alignment between word form and word meaning. Critically, there is a significant effect of iconicity (a perceived physical resemblance between word form and word meaning) on this alignment: words are most likely to be phonologically related when they are semantically related and iconic. This phenomenon is particularly widespread in ASL: half of the signs in the ASL lexicon are

Indexed as

LanguageSemanticsSign LanguageHumansPhoneticsiconicitylanguagephonological similaritysemantic associationssystematicity

Identifiers

PMID40228126
PMCPMC12037011

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.