MétaCan
Menu
Back to cohort
Record W4391449796 · doi:10.1075/ml.21015.nic

Bilingual and monolingual adults’ lexical choice in storytelling

2023· article· en· W4391449796 on OpenAlexaff
Elena Nicoladis, Danat Tewelde, Valin Zeschuk

Bibliographic record

VenueThe Mental Lexicon · 2023
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsStorytellingLinguisticsNatural language processingComputer sciencePsychologyArtificial intelligenceNarrative

Abstract

fetched live from OpenAlex

Abstract Bilinguals often have a harder time accessing words for production than monolinguals, perhaps because they have less exposure to words from each language (the weaker-links hypothesis). This research on lexical access mostly comes from studies of words in isolation. The purpose of the present study was to test whether bilinguals also show greater lexical access difficulties than monolinguals when telling a story. In the context of a narrative, we predicted that bilinguals would produce fewer different words and words of higher frequency than monolinguals, in order to make lexical access easier. For the same reason, we also predicted that bilinguals would use more cognates than monolinguals. English monolinguals, French monolinguals, and highly proficient French-English bilinguals watched a cartoon and told the story back. We coded the words they used for frequency and cognate status. In English, the results showed little difference between bilinguals and monolinguals on word frequency and cognate status. In French, first-language-English bilinguals used higher frequency words than first-language-French bilinguals. These results support predictions from the weaker-links hypothesis in lexical access for storytelling, albeit only for French.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.320
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Mental LexiconSame topicLanguage, Metaphor, and CognitionFrench-language works237,207