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Record W2182409846 · doi:10.1075/lfab.5.03asu

Towards a unified theory of resumption

2011· book-chapter· en· W2182409846 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

VenueLanguage faculty and beyond · 2011
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceSyntaxUnificationLinguisticsNatural language processingArtificial intelligenceProgramming languagePhilosophy

Abstract

fetched live from OpenAlex

This paper presents a unified theory of resumptive pronouns, based on the Resource Management Theory of Resumption. It identifies a common basis for puzzlingly different resumptive pronouns in languages such as Irish, in which resumptive pronouns do not behave syntactically like gaps ( syntactically active resumptives ), versus languages such as Vata, in which resumptive pronouns do behave syntactically like gaps ( syntactically inactive resumptives ). The Resource Management Theory of Resumption is based on the Resource Sensitivity Hypothesis, which holds that natural language is resource-sensitive – as captured through the use of a resource logic for semantic composition – and the empirical observation that resumptive pronouns are morpho-lexically ordinary pronouns – languages do not employ special paradigms or special items in resumptive-only uses. The unification of the two kinds of resumption is captured in semantic composition, but Vata-type resumptives also involve an additional syntactic mechanism, which is captured through an operation on feature-value pairs in a constraint-based, non-transformational theory of syntax.

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: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.242
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 science0.0000.000
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 head0.051
GPT teacher head0.253
Teacher spread0.203 · 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