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Record W4232022171 · doi:10.3138/cmlr.62.2.285

Orientations to Learning German: Heritage Language Learning and Motivational Substrates

2005· article· en· W4232022171 on OpenAlexfundvenueno aff
Kimberly A. Noels

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersCanadian Psychological Association
KeywordsGermanHeritage languageCompetence (human resources)PsychologyFeelingLanguage acquisitionAutonomySocial psychologyLinguisticsMathematics educationPedagogyPolitical science

Abstract

fetched live from OpenAlex

This study examined how two motivational substrates may be differentially important depending upon the learner's language background. Students registered in German classes (N = 99) completed a questionnaire that assessed (a) their intrinsic, extrinsic, integrative, and instrumental reasons for learning German; (b) their feelings of autonomy, competence, and relatedness; and (c) their engagement in language learning and intergroup contact variables. The results show that heritage language learners were more likely than non-heritage learners to learn German because it was an important aspect of their self-concept. Moreover, although intrinsic and self-determined extrinsic orientations fostered motivation both for heritage and non-heritage learners, aspects of contact with the German community also played a role in motivated learning, particularly for heritage language learners.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.252
Teacher spread0.237 · 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 designObservational
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

Citations66
Published2005
Admission routes2
Has abstractyes

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