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Record W1969441012 · doi:10.1215/00031283-2009-014

REVISED PERCEPTIONS: CHANGING DIALECT PERCEPTIONS IN WISCONSIN AND MICHIGAN'S UPPER PENINSULA

2009· article· en· W1969441012 on OpenAlexaboutno aff
Kathryn Remlinger, Joseph Salmons, Luanne von Schneidemesser

Bibliographic record

VenueAmerican Speech · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsPeninsulaIndexicalityPerceptionVariety (cybernetics)Ethnic groupGeographyVariation (astronomy)SociologyEconomic geographyHistoryLinguisticsAnthropologyPsychologyArchaeology

Abstract

fetched live from OpenAlex

This article documents the developing awareness of and positive attitudes toward regional English used in Michigan's Upper Peninsula and Wisconsin and also exemplifies some key regional markers in each variety. Findings demonstrate how this awareness and affinity has taken shape through historical processes. These processes have affected the structure of variation in that features once considered ethnic markers are now recognized as regional features. This indexical shift has occurred through relations with outsiders and economic processes. These new indexes are reinforced through discursive and metadiscursive practices, in particular those represented in the media, and are very much underway, shifting and changing at present. With them, some structural features have come to mean “local” and those who use them are perceived to be the “best” speakers and thus the “most authentic” locals, despite the fact that many of the stereotypical features are found throughout the upper Midwest, even in other parts of the United States and southern Ontario.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.319
Teacher spread0.305 · 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.

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

Citations23
Published2009
Admission routes1
Has abstractyes

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