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Record W2614239733 · doi:10.5430/elr.v6n2p26

The Connectionist Approach of Processing L2 Ambiguous English Sentences

2017· article· en· W2614239733 on OpenAlexvenueno aff
Hulin Ren

Bibliographic record

VenueEnglish Linguistics Research · 2017
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsGrammaticalityConnectionismLinguisticsComprehensionPolitenessComputer scienceSecond languagePsychologyNatural language processingArtificial intelligenceGrammarArtificial neural network

Abstract

fetched live from OpenAlex

The connectionist approach to language processing is popular in second language (L2) study in recent years. The paper is to investigate the connectionist approach of Chinese learners’ individual differences in the comprehension of certain ambiguous English sentences. Comprehension accuracy and grammaticality judgment are carried out with three groups with different background of language experience, namely, well-experienced English natives (group 1), well-experienced non-native English learners (group 2) and semi-experienced non-native English learners (group 3) on four types of ambiguous English sentences such as The polite actor thanked the old man who carried the black umbrella. Results of the study are discussed and a number of conclusions based on the results are summarized with regard to L2 learners’ differences in the performance to comprehend ambiguous syntactic structures.

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)0.003
metaresearch head score (Gemma)0.078
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.078
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.407
Teacher spread0.315 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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