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Record W2728220137 · doi:10.1017/cnj.2017.33

The ergative-antipassive alternation in Inuktitut: Analyzed in a case of new-dialect formation

2017· article· en· W2728220137 on OpenAlexaffabout
Julien Carrier

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsErgative caseLinguisticsAlternation (linguistics)RelocationContext (archaeology)HistoryComputer scienceMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper analyzes the ergative-antipassive alternation in Inuktitut using a variationist sociolinguistic approach. This alternation is not a typical linguistic variable, as these constructions are traditionally believed to have different syntactic functions. However, the nature of those functions remains controversial (e.g., Bittner 1987, Manga 1996), and they are undergoing changes in some dialects (e.g., Johns 2001, Carrier 2012), with the antipassive being increasingly used in place of the ergative. Thus, a variationist sociolinguistic approach is employed here to identify the significant functions of these constructions, and to find the specific context where they overlap and the language change is taking place. The study examines data collected in Resolute Bay, Nunavut, which presents a case of new-dialect formation due to the High Arctic relocation. The analysis reveals the functions of these constructions, describes the source of fading ergativity for the dialects considered in this study, and supports Trudgill's (2004) theory on new-dialect formation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.004
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.326
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations29
Published2017
Admission routes2
Has abstractyes

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Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicLinguistic Variation and MorphologyFrench-language works237,207