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Record W7097929082

Argument Structure and Antipassivization in Inuit

2007· article· en· W7097929082 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
Fundersnot available
KeywordsMorphemeAllomorphTransitive relationSuffixVerbArgument (complex analysis)Focus (optics)Object (grammar)Morphophonology
DOInot available

Abstract

fetched live from OpenAlex

This paper examines some seemingly disparate uses of the morpheme -si in two very closely related Inuit (Eskimo) languages: Inuktitut (spoken in Northeastern Canada) and West Greendlandic. I will use the term "Inuit" to refer to both West Greenlandic and Inuktitut as they pattern together. The morpheme -si is traditionally associated with antipassive morphology, although it also appears in several other environments that do not, at first, seem related to antipassivization. I will show that there are actually systematic patterns underlying the distribution of -si, indicating that the uses of of the morpheme in question are not as disparate as initial observations have assumed. I will discuss the implications of these patterns for a theory of the morphosyntax of antipassivization. Antipassivization is canonically a valency-changing operation that intransitivizes a transitive verb by "demoting" the direct object to an oblique Case or omitting it altogether. In Inuit, the antipassive is marked by a suffix which has several allomorphs. Many researchers claim that the specific allomorph which appears is lexically governed to some extent, and is at least partially abitrary or idiosyncratic, and not necessarily conditioned by phonological or other factors. Johnson (1980) and Bittner (1987) argue that the different antipassive morphemes are not allomorphs, but actually are used in different discourse contexts. The most common overt antipassive marker is -si, the one that we will focus on in this paper.

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 categoriesInsufficient payload (model declined to judge)
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 score0.293
Threshold uncertainty score1.000

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)0.0010.000

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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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.

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
Published2007
Admission routes1
Has abstractyes

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