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Record W2767255993 · doi:10.1111/tger.12037

Producing Lexical Stress in Second Language German

2017· article· en· W2767255993 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

VenueDie Unterrichtspraxis/Teaching German · 2017
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCognateGermanLinguisticsSchwaStress (linguistics)VocabularyComputer scienceLexical itemProduction (economics)PsychologyNatural language processing

Abstract

fetched live from OpenAlex

Lexical stress assignment plays a central role in being understood in a second language. In fact, research has shown that it may be more important for the comprehensibility of second language learners’ speech than, for example, grammatical correctness (Trofimovich & Isaacs, ). Nonetheless, its production poses challenges for second language learners. This study investigated the effect of perceptual training on the production of three types of predictable German lexical stress patterns by native speakers of English. Beginner and intermediate learners produced German words from three categories: words ending in schwa; words with unstressed suffixes; and German‐English cognates. The results demonstrate that both beginner and intermediate learners improved in their production of lexical stress after the training. Though participants in both groups had more difficulties in assigning lexical stress to cognate words than to non‐cognate words, production accuracy could best be predicted by the presence of certain suffixes. The results have implications for teaching second language vocabulary.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.415
Teacher spread0.381 · 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