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Record W4409166972 · doi:10.3389/flang.2025.1413119

The acquisition of object clitic pronouns in Heritage Romanian

2025· article· en· W4409166972 on OpenAlexfundaboutno aff
Mihaela Pirvulescu, Virginia Hill

Bibliographic record

VenueFrontiers in Language Sciences · 2025
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCliticRomanianLinguisticsObject (grammar)Object pronounComputer sciencePsychologyGeographyPersonal pronounPhilosophy

Abstract

fetched live from OpenAlex

This paper examines the acquisition of object clitic pronouns in Heritage Romanian (HR) by school-age children in Toronto who are second-generation speakers of Romanian—i.e., children of first-generation immigrant parents. These children have been exposed to Romanian as their first language (L1) since birth within the home, while English has served as the societal language, primarily encountered outside the home. Additionally, they were enrolled in French immersion programs between the ages of 3 and 6. This study looks at both production and comprehension of preverbal object clitic pronouns. The findings demonstrate that HR exhibits similar patterns in the domain of object clitics as those observed in Romanian-dominant trilingual children, particularly regarding clitic omissions at specific developmental stages. Moreover, HR shares characteristics commonly identified in bilingual (heritage) language acquisition, such as gender errors. Overall, this study provides further evidence that both language use and literacy play a crucial role in shaping heritage language proficiency.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.456
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.005
GPT teacher head0.266
Teacher spread0.262 · 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 designTheoretical or conceptual
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
Published2025
Admission routes2
Has abstractyes

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