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Record W2093058638 · doi:10.1111/josl.12094

Work that –s!: Drag queens, gender, identity, and traditional Newfoundland English

2014· article· en· W2093058638 on OpenAlexafffundabout
Becky Childs, Gerard Van Herk

Bibliographic record

VenueJournal of Sociolinguistics · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsMemorial University of Newfoundland
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSalientParallelsSituatedIdentity (music)SociologyLinguisticsFeature (linguistics)PopulationSociolinguisticsGender studiesGeographyAestheticsArtDemographyComputer scienceArchaeology

Abstract

fetched live from OpenAlex

Making use of three data sets of Newfoundland English, this paper uncovers the linguistic and social motivations and strategies used by young speakers to reclaim and re‐shape a traditional, local, relic language feature (verbal –s attachment, as inI goes). While each group that we discuss (young females, drag queens, and a sample of the Newfoundland population) is differently situated with respect to the broader local culture (i.e. they each have their own social identities), similarities and parallels in the reclamation and use of verbal –s indicate important processes that occur in the enregisterment and reappropriation of a salient, traditional linguistic form. Results indicate that the local social and linguistic reconstruction of a speech feature can change a path of decline and prove fertile ground for creating a unique identity that moves toward the global while still motioning to the past of a community.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.093
GPT teacher head0.330
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 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

Citations13
Published2014
Admission routes3
Has abstractyes

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