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Record W3055611048 · doi:10.33137/twpl.v42i1.33384

Second-generation Persians’ Participation in the Oklahoma Dialect

2020· article· en· W3055611048 on OpenAlexvenueno aff
Shima Dokhtzeynal

Bibliographic record

VenueToronto Working Papers in Linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsPersianVowelLinguisticsVariation (astronomy)ImmigrationHistoryLanguage contactGeographyArchaeology

Abstract

fetched live from OpenAlex

Vowel systems are a rich source of information about speakers’ social affiliations and linguistic influences. With the purpose of contributing to recent dialect investigations of immigrant communities inside the US, this study examined the acoustics of bilingual Persian-Oklahomans and their participation in Oklahoma dialect features. Twenty Oklahoma-born second-generation Persian-Americans were compared to ten monolingual European-Oklahomans with respect to their production of local dialect features. Results showed similar vowel spaces between the groups indicating that second-generation Persian-Oklahomans participated in the local mix of Southern and Midland features, with one notable exception: they did not display the pin/pen merger, a feature of Southern dialects. Similar studies on European-Oklahoman speakers suggested a uniform presence of pin/pen merger among Research on the Dialects of English in Oklahoma (RODEO) project respondents. However, Persian-Oklahomans’ productions of these vowels were consistently unmerged across the continuum of speech styles. Accordingly, this study argues for a connection between this acoustic variation and speakers’ demographic traits, make-up of social network, and heritage Farsi despite their frequent contact with the merger and their rich social network with middle-class European-Oklahoman speakers of the Oklahoma dialect.

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 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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
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 integrity0.0000.000
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 head0.067
GPT teacher head0.336
Teacher spread0.269 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2020
Admission routes1
Has abstractyes

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