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Record W2982244404 · doi:10.1515/jhsl-2019-0005

Canadian heritage German across three generations: A diary-based study of language shift in action

2019· article· en· W2982244404 on OpenAlexaboutno aff
Doris Stolberg

Bibliographic record

VenueJournal of Historical Sociolinguistics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHeritage languageGermanLanguage shiftImmigrationLinguisticsAction (physics)Language contactSociologyHistory

Abstract

fetched live from OpenAlex

Abstract It is well known that migration has an effect on language use and language choice. If the language of origin is maintained after migration, it tends to change in the new contact setting. Often, migrants shift to the new majority language within few generations. The current paper examines a diary corpus containing data from three generations of one German-Canadian family, ranging from 1867 to 1909, and covering the second to fourth generation after immigration. The paper analyzes changes that can be observed between the generations, with respect to the language system as well as to the individuals’ decision on language choice. The data not only offer insight into the dynamics of acquiring a written register of a heritage language, and the eventual shift to the majority language. They also allow us to identify different linguistic profiles of heritage speakers within one community. It is discussed how these profiles can be linked to the individuals’ family backgrounds and how the combination of these backgrounds may have contributed to giving up the heritage language in favor of the majority language.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0070.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.069
GPT teacher head0.453
Teacher spread0.384 · 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 designQualitative
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

Citations5
Published2019
Admission routes1
Has abstractyes

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