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Record W4414066816 · doi:10.1017/s0305000925100172

The Acquisition of Demonstratives and Locative Adverbs in Inuktitut

2025· article· en· W4414066816 on OpenAlexfundaboutno aff
Shanley Allen

Bibliographic record

VenueJournal of Child Language · 2025
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLocative caseDemonstrativeAdverbMorphemeUtterancePronunciationGrammaticalizationLanguage acquisition

Abstract

fetched live from OpenAlex

Demonstratives and locative adverbs cross-linguistically are typically acquired relatively late, with children initially overusing proximal forms. However, these findings are largely based on research in languages with only two or three demonstratives. It is unclear whether the findings extend to languages with more complex systems. The present study examines data from Inuktitut, a language of the Inuit-Yupik-Unangan family, which has 20 demonstrative roots and 10 locative adverb roots representing six spatial distinctions. It uses data from 18 Inuktitut speakers (8-60 years) to investigate the target-like use of demonstratives/locatives and data from eight Inuktitut-speaking children (1-4 years) and their mothers to determine the acquisition trajectories of these structures. Children initially used only the proximal demonstratives/locatives, which aligns with prior research. The proportion of proximal forms out of all others decreased significantly with mean length of utterance in morphemes (MLUm), and by MLUm 2.50, children were using the full demonstrative/locative paradigm in a target-like manner. This differs from prior research and highlights the importance of language diversity in acquisition research.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.147

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 head0.003
GPT teacher head0.283
Teacher spread0.280 · 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 designObservational
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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