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Record W2309066231

Argument Structure and Multicompetence

2013· article· en· W2309066231 on OpenAlexaff
Patricia Balcom

Bibliographic record

VenueThe Journal of Macrodynamic Analysis (Memorial University of Newfoundland) · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsLinguisticsPhilosophyHumanitiesPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Cook (1991Cook ( , 1992) discussed the question of ultimate attainment in second language acquisition in terms of what he called 'multicompetence'.He proposed that the internalized L2 grammars of very advanced (native-like) learners are different from those of monolingual native speakers, although their performance is similar, since the L1 and L 2 grammars may influence each other.This article explores the acceptance and use of inappropriate passive morphology by very advanced francophone learners of English, comparing their linguistic performance (measured by a fill-in-the-blanks task) and linguistic intuitions (measured by a grammaticality judgement task) to those of native speakers of English with very little previous exposure to French.The results supported Cook's muIticompetence hypothesis.The very advanced learners had performance which was indistinguishable from that of native speakers on the controlled production task.However, there were significant differences between the two groups in their acceptance of inappropriate passive morphology on the grammaticality judgement task, particularly with verbs having a Theme in subject position and describing a state or change of state.•.This research was supported by research grant #004109 from the Faculte des etudes superieures et de la recherche, Universite de Moncton, for which I am grateful.Earlier versions of this paper were presented at the conference «Les Acadiens et leur(s) langue (s»>,Moncton N.B., August 1994;Second Language Research Forum '94, Montrea!, Que., October 1994; and the 18th Annual Meeting of the Atlantic Provinces Linguistic Association, St. John, N.B., October 1994.I would like to thank the audiences for their questions and comments, and an anonymous reviewer for thought-provoking comments.A paper in French describing this study will appear in Les Actes du colloque «les Acadiens et leur(s) langue(s)>>.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.009
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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