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Record W2790634503 · doi:10.1017/s0022226718000087

Building verbs in Chuj: Consequences for the nature of roots

2018· article· en· W2790634503 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

VenueJournal of Linguistics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsMcGill University
Fundersnot available
KeywordsMerge (version control)Root (linguistics)VerbValence (chemistry)Transitive relationArgument (complex analysis)LinguisticsMathematicsComputer sciencePhilosophyBiologyCombinatoricsPhysics

Abstract

fetched live from OpenAlex

This paper offers an in-depth look at roots and verb stem morphology in Chuj (Mayan) in order to address a larger question: when it comes to the formation of verb stems, what information is contributed by the root, and what is contributed by the functional heads? I show first that roots in Chuj are not acategorical in the strict sense (cf. Borer 2005), but must be grouped into classes based on their stem-forming possibilities. Root class does not map directly to surface lexical category, but does determine which functional heads (i.e. valence morphology) may merge with the root. Second, I show that while the introduction of the external argument, along with clausal licensing and agreement generally, are all governed by higher functional heads, the presence or absence of an internal argument is dictated by the root. Specifically, I show that transitive roots in Chuj always combine with an internal argument, whether it be (i) a full DP, (ii) a bare pseudo-incorporated NP, or (iii) an implicit object in an antipassive. In the spirit of work such as Levinson (2007, 2014), I connect this to the semantic type of the root; root class reflects semantic type, and semantic type affects the root’s combinatorial properties. This work also contributes to the discussion of how valence morphology operates. In line with works such as Alexiadou, Anagnostopoulou & Schäfer (2006), I argue that valence morphology applies directly to roots, rather than to some ‘inherent valence’ of a verb.

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)0.001
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.241
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.018
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 head0.036
GPT teacher head0.303
Teacher spread0.268 · 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