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Record W4318822952 · doi:10.1177/01427237221147614

Acquisition during normative code-mixing: Trinidadian children’s varilingual pronoun usage

2023· article· en· W4318822952 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

VenueFirst Language · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPossessivePronounCreole languageLinguisticsPsychologyObject pronounSubject pronounVariation (astronomy)Noun

Abstract

fetched live from OpenAlex

While monolingual English speakers acquire most pronouns by age 5, acquisition amid prevalent, normative code-mixing, such as in Trinidad, is underexplored. This study examines how Trinidadian 3- to 5-year-olds express third-person subject, object, reflexive and possessive pronouns and factors influencing pronoun choices. Seventy-five preschoolers produced pronouns via a word elicitation task conducted in Trinidadian English Creole and Trinidad and Tobago English. Responses were coded for children’s age, gender, district and socioeconomic status; task language; grammatical gender/number; and response form. Conditional inference trees facilitated statistical analysis. When choices were available, children exhibited variable production, with Creole forms often dominant. Grammatical gender influenced whether English or Creole pronouns were selected. Task language influenced possessive pronoun choices, indicating developing sociolinguistic competence. The non-significance of other variables suggests widespread mixing of English and Creole pronouns. Findings underscore the importance of describing understudied populations, especially where variation is inherent, to ensure accurate language assessment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.392
Teacher spread0.363 · 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