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Record W24219268 · doi:10.1075/lald.47.04goa

Prosodic transfer and the representation of determiners in Turkish-English interlanguage

2008· book-chapter· en· W24219268 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 acquisition & language disorders · 2008
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsInterlanguageTurkishLinguisticsRepresentation (politics)Transfer (computing)Computer scienceMathematicsPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Problems with the second language (L2) acquisition of articles in Turkish-English interlanguage are examined, specifically omission, substitution of other determiners in place of articles, overuse of stressed articles and differential treatment of articles in DPs with and without adjectives. Trenkic’s (2007) syntactic misanalysis account is argued against, that difficulties with articles for L2 English speakers from L1s like Turkish and Serbian stem from the absence of DP in the L1 grammar. Instead, in accordance with the Prosodic Transfer Hypothesis, it is proposed that L1 prosodic representations underlie these problems; L2 learners are argued to have difficulty in producing functional morphology in target-like fashion when the L2 requires a prosodic representation that is unavailable in the L1 grammar.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.224
Teacher spread0.214 · 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