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Record W2076455146 · doi:10.1075/lab.1.2.03str

Jij doe wat girafe?

2011· article· en· W2076455146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLinguistic Approaches to Bilingualism · 2011
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInterrogativeLinguisticsVerbInversion (geology)Structural approachPsychologyInterrogative wordComputer scienceArtificial intelligenceNatural language processingPhilosophyGeology

Abstract

fetched live from OpenAlex

In this study we consider the role of cross-linguistic influence in the domain of wh -movement and subject-verb inversion in children simultaneously acquiring Dutch and French, two typologically different languages. Wh -questions were elicited in Dutch by means of an elicited production task. The participants consisted of 5- and 7-year-old Dutch-French bilingual children, and two control groups of monolingual Dutch children and adults (N = 46). Target-like wh -fronted questions with subject-verb inversion formed the majority of responses. However, two qualitatively different structures were produced as a result of transfer from French: wh -in-situ questions and wh -fronted questions without inversion. Structural overlap approaches to transfer can predict cross-linguistic influence from the language with more structural options (French) to the one with only one interrogative construction (Dutch). However, we argue that a complexity-based theory of transfer provides a better account for the presence of the attested structures than a structural overlap approach.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.319
GPT teacher head0.301
Teacher spread0.018 · 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