Evidence map›Paper›PMID 37645154›Full record

ArticleOpen research Europe2021

Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K'iche'.

Ben Ambridge, Laura Doherty, Ramya Maitreyee, Tomoko Tatsumi, Shira Zicherman, Pedro Mateo Pedro, Ayuno Kawakami, Amy Bidgood, Clifton Pye, Bhuvana Narasimhan and 13 more

Abstract read
In one paragraph

Article in Open research Europe, 2021. 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

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

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

23 authors.

Ben AmbridgeUniversity of Liverpool, Liverpool, UK.ORCID https://orcid.org/0000-0003-2389-8477
Laura DohertyUniversity of Liverpool, Liverpool, UK.
Ramya MaitreyeeUniversity of Liverpool, Liverpool, UK.
Tomoko TatsumiKobe University, Kobe, Japan.ORCID https://orcid.org/0000-0001-5590-016X
Shira ZichermanHebrew University of Jerusalem, Jerusalem, Israel.
Pedro Mateo PedroUniversidad del Valle de Guatemala, Guatemala City, Guatemala.
Ayuno KawakamiUniversity of Liverpool, Liverpool, UK.
Amy BidgoodUniversity of Salford, Salford, UK.ORCID https://orcid.org/0000-0002-9719-4256
Clifton PyeUniversity of Kansas, Lawrence, Kansas, USA.
Bhuvana NarasimhanUniversity of Colorado, Boulder, Boulder, Colorado, USA.
Inbal ArnonHebrew University of Jerusalem, Jerusalem, Israel.
Dani BekmanHebrew University of Jerusalem, Jerusalem, Israel.
Amir EfratiHebrew University of Jerusalem, Jerusalem, Israel.
Sindy Fabiola Can PixabajUniversidad del Valle de Guatemala, Guatemala City, Guatemala.
Mario Marroquín PelízUniversidad del Valle de Guatemala, Guatemala City, Guatemala.
Margarita Julajuj MendozaUniversidad del Valle de Guatemala, Guatemala City, Guatemala.
Soumitra SamantaUniversity of Liverpool, Liverpool, UK.
Seth CampbellUniversity of Calgary, Calgary, Canada.
Stewart McCauleyUniversity of Iowa, Iowa City, Iowa, USA.
Ruth BermanTel Aviv University, Tel Aviv, Israel.
Dipti Misra SharmaIndian Institute of Information Technology, Hyderabad, India.
Rukmini Bhaya NairIndian Institute of Technology, Delhi, India.ORCID https://orcid.org/0000-0002-2185-1651
Kumiko FukumuraUniversity of Stirling, Stirling, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How do language learners avoid the production of verb argument structure overgeneralization errors (

Indexed as

causativechild language acquisitiondiscriminative learningEnglishHebrewHindiJapaneseK’iche'verb semantics

Identifiers

PMID37645154
PMCPMC10446094

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.