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Record W1995208062 · doi:10.1075/livy.7.07mat

Evidentials as epistemic modals: Evidence from St'át'imcets

2007· article· en· W1995208062 on OpenAlexaff
Lisa Matthewson, H. J. Davis, Hotze Rullmann

Bibliographic record

VenueLinguistic Variation Yearbook · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsModal verbEpistemic modalityEvidentialityCertaintyArgument (complex analysis)LinguisticsModality (human–computer interaction)ModalPhilosophyEpistemologyPsychologyComputer scienceArtificial intelligenceVerb

Abstract

fetched live from OpenAlex

This paper argues that evidential clitics in St’át’imcets (a.k.a. Lillooet; Northern Interior Salish) must be analyzed as epistemic modals.We apply a range of tests which distinguish the modal analysis from the main alternative contender (an illocutionary operator analysis, as in Faller 2002), and show that the St’át’imcets evidentials obey the predictions of a modal analysis. Our results support the growing body of evidence that the functions of encoding information source and epistemic modality are not necessarily distinct. The St’át’imcets data further provide a novel argument against the claim that evidentiality and epistemic modality are separate categories. Many authors argue that evidentials differ from modals in that the former do not encode speaker certainty (see, e.g., de Haan 1999; Aikhenvald 2004).We argue that modals are also not required to encode speaker certainty; we provide evidence from St’át’imcets that marking quantificational strength is not an intrinsic property of modal elements.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.046
GPT teacher head0.288
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

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 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

Citations376
Published2007
Admission routes1
Has abstractyes

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