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Record W2972415627 · doi:10.1017/cnj.2019.24

Dissociating the Person Case Constraint from its “repair”

2019· article· en· W2972415627 on OpenAlexaff
Tomohiro Yokoyama

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCliticPhenomenonComplementarity (molecular biology)Constraint (computer-aided design)Computer scienceFeature (linguistics)UnavailabilityPhraseLinguisticsComplement (music)Natural language processingArtificial intelligenceMathematicsPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract In French ditransitive sentences, certain person combinations of the two internal arguments cannot be expressed with two co-occurring clitics (a phenomenon referred to as the Person Case Constraint or PCC). To fill the interpretational gap created by this restriction, there is an alternative construction characterized as a “repair”, where the goal is realized as an independent phrase. The fact that the double-clitic construction and the repair construction are in complementary distribution led to a proposal of an interface algorithm that provides a way to repair a non-convergent structure. This article proposes an alternative account of the PCC, and claims that the complementarity between the PCC and its repair is instead accidental and is an artefact of the feature structure of arguments. The proposed account explains the unavailability of certain clitic combinations and some repairs independently, without resorting to a trans-derivational device like the previously proposed algorithm.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.024
GPT teacher head0.225
Teacher spread0.201 · 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 designNot applicable
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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicSyntax, Semantics, Linguistic VariationFrench-language works237,207