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Record W6931470091 · doi:10.5281/zenodo.5524282

Future interpretation in Gitksan and reduced clausal complements

2021· book-chapter· en· W6931470091 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterpretation (philosophy)Focus (optics)CovertConjunction (astronomy)Connection (principal bundle)Complement (music)Margin (machine learning)Feature (linguistics)Semantic interpretation

Abstract

fetched live from OpenAlex

This paper explores temporal interpretations in clausal complements in Gitksan,<br> a language without temporal morphology. Bare predicates in Gitksan can receive<br> present or past reading. Jóhannsdóttir &amp; Matthewson (2007) capture these readings<br> with a covert non-future tense. For future reading, bare predicates must combine<br> with a marker dim; in syntax, dim combines with the non-future tense. In this paper,<br> I focus on the connection between the syntactic make-up of Gitksan complements<br> and the availability of future-oriented reading. Assuming the non-future tense in<br> Gitksan, I show that the attested readings can only be captured if some of the<br> complements project TPs, while the others do not. I propose that the observed patterns<br> follow straightforwardly from Wurmbrand’s (2001 et seq.) idea that clausal<br> complements are of different sizes: some complements are CPs, but some can project<br> as little as vPs. Gitksan provides support for this approach through the<br> syntax-semantics interaction in the embedded temporal-modal domain.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.879
Threshold uncertainty score0.996

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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