MétaCan
Menu
Back to cohort
Record W4284896578 · doi:10.16995/glossa.6557

The syntactization of kinship in vocative phrases

2022· article· en· W4284896578 on OpenAlexaff
Virginia Hill

Bibliographic record

VenueGlossa a journal of general linguistics · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLinguisticsKinshipRelation (database)Speech actProsodyPsychologyAnaphora (linguistics)Head (geology)Rank (graph theory)Computer scienceSociologyArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Current studies point out that vocative phrases encode the social relation between speaker and addressee by the interaction of various means, i.e., prosody, lexical options, morpho-syntactic operations. As a contribution to this body of research, this paper focuses on reversed vocatives, and develops two main arguments: (i) vocative phrases provide the default domain for the morpho-syntactic encoding of speaker’s social superiority; and (ii) reversed vocatives are a case in order, where the syntactization of the kinship rank ensures the speaker’s upper-hand in the social relation. Formally, the mapping of the kinship feature entails syntactic head splitting, so the analysis confirms that the derivations concerning the conversational field conform to the general split-and-remerge options available to functional heads (on a par with D, C, T fields).

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.039
GPT teacher head0.292
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

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 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGlossa a journal of general linguisticsSame topicLanguage, Discourse, Communication StrategiesFrench-language works237,207