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Record W3016558584 · doi:10.1111/josl.12414

Systems, features, figures: Approaches to language and class vs. language and race

2020· article· ko· W3016558584 on OpenAlex

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

VenueJournal of Sociolinguistics · 2020
Typearticle
Languageko
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Waterloo
FundersCanada Foundation for Innovation
KeywordsRace (biology)Class (philosophy)LinguisticsSociologyComputer scienceGender studiesArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper contrasts different approaches taken in research on language and race vs. language and class. It looks at the timescales, units of analysis, and phenomena that have drawn scholars’ attention, and considers how each subfield approaches the study of language and inequality. 본고는 언어와 인종주의 연구, 언어와 사회계층 연구의 두 분야에서 쓰이는 다양한 이론적 접근들을 비교·분석 한다. 본고는 기존연구들에서 쓰여진 시공간적 접근방법, 연구분석 단위와 분석방법 및 연구 현상을 면밀하게 검토하며 이러한 이론적 접근들을 언어와 사회 불평등 연구분야에 어떻게 적용시킬 수 있는지 알아본다.

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)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.328
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.116
GPT teacher head0.394
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