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Record W3173915048 · doi:10.1515/iral-2020-0104

Lexical stress assignment preferences in L2 German

2021· article· en· W3173915048 on OpenAlex
Mary Grantham O’Brien, Ross Sundberg

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIRAL - International Review of Applied Linguistics in Language Teaching · 2021
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcGill UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGermanLinguisticsStress (linguistics)PsychologyLexiconSyllableFirst languageComputer science

Abstract

fetched live from OpenAlex

Assigning stress to the appropriate syllable is consequential for being understood. Despite the importance, second language (L2) learners' stress assignment is often incorrect, being affected by their first language (L1). Beyond the L1, learners' lexical stress assignment may depend on analogy with other words in their lexicon. The current study investigates the respective roles of the L1 (English, French) and analogy in L2 German lexical stress assignment. Because English, like German, has variable stress assignment and French does not, participants included English- and French-speaking German L2 learners who assigned stress to German nonsense words in a perceptual preference and a production task. Results suggest a role of the L1, with English-speaking German L2 learners performing more like L1 German speakers. While French-speaking German L2 learners' performance could not be predicted by other factors, L2 German proficiency and the ability to produce analogous words were predictive of English-speaking German L2 learners' production performance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.430
Teacher spread0.397 · 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