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Record W4223593610 · doi:10.1017/s0959269522000035

The French intensifier<i>auto,</i>and the roles of<i>v</i>and Voice in introducing agents

2022· article· en· W4223593610 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 French Language Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSyntaxHead (geology)Ellipsis (linguistics)Computer scienceRealization (probability)PrefixLinguisticsGenerative grammarArgument (complex analysis)Interpretation (philosophy)Event (particle physics)Semantics (computer science)Projection (relational algebra)Artificial intelligenceNatural language processingPhilosophyProgramming languageMathematicsAlgorithm

Abstract

fetched live from OpenAlex

Abstract The paper focuses on the syntax and semantics of the French verbal prefix auto . It is proposed that auto is an intensifier stating that no agent other than the one specified in the clause (agent-focusing), or, in anticausative clauses, no agent (agent-denying), is responsible for the event. Syntactically, auto merges with a verbal projection, and the nature of the constituent to which it attaches determines and constrains the interpretation of the clause. The proposed analysis of auto provides support for generative approaches in which a v head introduces the external argument role, while a grammatical Voice head determines its syntactic realization.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.263
Teacher spread0.240 · 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