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Record W3160867475 · doi:10.3765/sp.15.11

Two paths to habituality: The semantics of habitual mode in Tlingit

2022· article· en· W3160867475 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSemantics and Pragmatics · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsLinguisticsVerbSemantics (computer science)SentenceVariety (cybernetics)AdverbCovertLexical semanticsMorphology (biology)Computer scienceHistoryLexical itemArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

This paper presents a detailed description and formal semantic analysis of habitual sentences in Tlingit (Na-Dene; Alaska, British Columbia, Yukon). As in many other languages (Carlson 2005, 2012), there are two means in Tlingit for expressing a habitual statement, such as my father eats salmon. The first employs a relatively unmarked verb, realizing imperfective aspect. In the second type of habitual sentence, however, the verb bears special habitual morphology. Although there is a significant overlap in the use of these constructions, certain semantic contrasts do exist. Most notably, the special habitual marking cannot be used to express pure, unrealized dispositions/functions/duties (e.g., Mary handles any mail from Antarctica). In other words, Tlingit habitual morphology --- unlike imperfective aspect --- requires the habituality in question to have actually occurred, an effect that has also observed for habitual morphology in a variety of other, unrelated languages (Green 2000, Bittner 2008, Boneh & Doron 2008, Filip 2018). I develop and defend a formal semantic analysis that captures these (and other) contrasts between imperfective and habitual verbs. In brief, imperfective aspect is argued to possess a modal semantics, quantifying over alternative worlds/situations (Arregui et al. 2014, Ferreira 2016). Habitual morphology, however, is argued to be associated with a (potentially covert) quantificational adverb, one that quantifies strictly over times in the actual world. The consequences of this account for the analysis of habitual sentences in other languages are explored. Most notably, we find that (i) “habituality” so-called is potentially a heterogeneous phenomenon, and resists unified definition or semantic analysis, and (ii) therefore is a sui generis category of phenomena, which cannot be reduced as an instance of aspect or modality (Filip & Carlson 1997, Filip 2018). EARLY ACCESS

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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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.230
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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