MétaCan
Menu
Back to cohort
Record W4317774198 · doi:10.1162/ling_a_00503

Commitment Phrase: Linking Proposition to Illocutionary Force

2023· article· en· W4317774198 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.

Bibliographic record

VenueLinguistic Inquiry · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPropositionLinguisticsPredicate (mathematical logic)PragmaticsNegationComputer scienceImplicatureSpeech actPhraseNoun phraseCommitUtteranceSentenceRomanianProjection (relational algebra)PhilosophyNoun

Abstract

fetched live from OpenAlex

This article provides empirical support for the projection of a Commitment Phrase (CommitP) in the field that maps the conversational pragmatics at the periphery of clauses. Krifka (2015, 2019, 2020) proposes CommitP as a projection that maps the speaker’s commitment to act on the proposition insofar as the speaker has evidence for the truth condition or expects the addressee to produce and commit to such evidence. CommitP replaces Ross’s (1970) idea that the speaker/addressee is related to the proposition by a speech-act predicate such as declare. Krifka argues for the alternative approach primarily on theoretical grounds. This article verifies and validates this proposal on the basis of Japanese sentence-final particles and Romanian speech-act particles. We extend our analysis beyond these languages that overtly mark CommitP to English, which does not, by proposing an analysis of so-called biased questions that incorporates CommitP.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.085
GPT teacher head0.338
Teacher spread0.253 · 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