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Record W2490750356 · doi:10.1017/cbo9780511486920.024

Checklist of nonstandard features

2005· other· en· W2490750356 on OpenAlexaboutno aff
Raymond Hickey

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsVariation (astronomy)Variety (cybernetics)LinguisticsIndigenousLoanwordGrammarPhonologySyntaxMainstreamVocabularyHistoryLexisSection (typography)Varieties of EnglishIrishLexical itemComputer sciencePolitical sciencePhilosophyLawArtificial intelligence

Abstract

fetched live from OpenAlex

The variation found in varieties of English can be documented for different linguistic levels. Below, an attempt is made to indicate what the chief features of phonology, morphology and syntax are which are more or less removed from contemporary conceptions of standard English in major anglophone countries. Vocabulary is only dealt with briefly (see section 4) as the variation here is not a matter of structural differences. In a way lexical variation represents a relatively simple case: a word in an anglophone variety is either a dialect survival, an indigenous loanword or an independent development, if it has not been inherited through historical continuity with mainstream English. There may be some cases of disagreement, an instance being shanty which could stem from the Canadian French for ‘log cabin’ or be possibly connected with the Irish for ‘old house’. However, the levels of sounds and grammar provide many contentious issues because the sources of their features are not so easily identified. These levels constitute subsystems in language – closed classes – which speakers are not usually aware of and where for virtually every parallel between an extraterritorial variety and a British dialect there is an equally significant difference. Such situations are tantalising for the linguist but also represent a challenge to present a convincing case either for or against dialect influence. Not all the items listed below are necessarily instances of dialect retention or at least may have other possible origins as contact features or independent developments.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.046
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.007
Science and technology studies0.0030.002
Scholarly communication0.0030.004
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0460.012

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 head0.012
GPT teacher head0.323
Teacher spread0.311 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2005
Admission routes1
Has abstractyes

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