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Record W2423984443 · doi:10.1017/s0954394516000065

A tale of two cities (and one vowel): Sociolinguistic variation in Swedish

2016· article· en· W2423984443 on OpenAlexaff
Johan Gross, Sally Boyd, Therese Leinonen, James A. Walker

Bibliographic record

VenueLanguage Variation and Change · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsYork University
Fundersnot available
KeywordsVariation (astronomy)VowelLinguisticsImmigrationContext (archaeology)Ethnic groupLanguage contactIdentity (music)SociolinguisticsLanguage changeSociologyAppealPsychologyGeographyPolitical scienceAnthropologyArt

Abstract

fetched live from OpenAlex

Abstract Previous studies of language contact in multilingual urban neighborhoods in Europe claim the emergence of new varieties spoken by immigrant-background youth. This paper examines the sociolinguistic conditioning of variation in allophones of Swedish /ε:/ of young people of immigrant and nonimmigrant background in Stockholm and Gothenburg. Although speaker background and sex condition the variation, their effects differ in each city. In Stockholm there are no significant social differences and the allophonic difference appears to have been neutralized. Gothenburg speakers are divided into three groups, based on speaker origin and sex, each of which orients toward different norms. Our conclusions appeal to dialectal diffusion and the desire to mark ethnic identity in a diverse sociolinguistic context. These results demonstrate that not only language contact but also dialect change should be considered together when investigating language variation in modern-day cities.

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)0.001
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.036
GPT teacher head0.314
Teacher spread0.278 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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