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Record W2991039843 · doi:10.1075/ahs.10

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2019· book· en· W2991039843 on OpenAlexaboutno aff

Bibliographic record

VenueAdvances in historical sociolinguistics · 2019
Typebook
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The current volume presents a number of chapters which look at informal vernacular letters, written mostly by emigrants to the former colonies of Britain, who settled at these locations in the past few centuries, with a focus on letters from the nineteenth century. Such documents often show features for varieties of English which do not necessarily appear in later sources or which are not attested with the same range or in the same set of grammatical contexts. This has to do with the vernacular nature of the letters, i.e. they were written by speakers who had a lower level of education and whose speech, and hence their written form of language, does not appear to have been guided by considerations of standardness and conformity to external norms of language. Furthermore, the writers of the emigrant letters, examined in the current volume, were very unlikely to have known of, still less have used, manuals of letter writing. Emigrant letters thus provide a valuable source of data in tracing the possible development of features in varieties of English in the USA, Canada, South Africa, Australia and New Zealand.

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)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.121
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0110.010
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1210.107

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 head0.031
GPT teacher head0.377
Teacher spread0.346 · 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

Citations20
Published2019
Admission routes1
Has abstractyes

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