MétaCan
Menu
Back to cohort
Record W1987144723 · doi:10.1075/lab.5.1.02she

Tense, aspect, and agreement in heritage Labrador Inuttitut

2015· article· en· W1987144723 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLinguistic Approaches to Bilingualism · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsCarleton University
Fundersnot available
KeywordsMorphemeComprehensionLinguisticsAgreementRule-based machine translationVerbNatural language processingObject (grammar)Computer scienceFluentArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Heritage receptive bilinguals (RBs) are individuals who report understanding but not speaking their family language. This study tests whether semantic features of functional morphemes, namely tense, aspect, and agreement markers, are accessible to them in comprehension. RBs in this study are fluent speakers of English with receptive knowledge of Labrador Inuttitut. Many RBs showed fluent-like comprehension of aspectual suffixes, subject-object-verb agreement suffixes, and past versus future contrasts in tense suffixes, but most could not identify remoteness degrees in tense suffixes. Lowest-proficiency RBs did not show knowledge of any morphemes. Remoteness features are missing from most RBs’ grammars; the same applies to many features in LRBs’ grammars. Some RBs showed inconsistent performance: better than chance, but worse than fluent speakers. The corresponding parts of RBs’ grammars are therefore fluent-like, but access to them is difficult. RBs’ grammars consist of fluent-like parts, parts with reduced access, and incomplete parts.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 head0.144
GPT teacher head0.261
Teacher spread0.118 · 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