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Record W6987278316

The sounds of English around the world an introduction to phonetics and phonology

2023· other· en· W6987278316 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsPhoneticsPhonologyVarieties of EnglishIntonation (linguistics)Active listeningStress (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

"Most introductions to English phonetics and phonology focus primarily on British or American English, which fails to account for the rich diversity of English varieties globally. This book addresses this gap, providing an overview of English phonetics and phonology through an exploration of the sounds of English around the world, including older varieties of English such as American, Canadian, British, and Australian Englishes, as well as new varieties of English such as Indian, Singaporean, Hong Kong, and Kenyan English. It focuses on diversity in vowels and consonants, allophonic variation, and stress and intonation patterns across regional, ethnic and social varieties of English in North America, The Caribbean, Asia, Africa, Europe, and Oceania. Listening exercises are incorporated throughout to facilitate the understanding of different concepts, and the book also has an accompanying website with a wide range of speech samples, allowing readers to hear the phonetics of the varieties under discussion."

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)0.000
metaresearch head score (Gemma)0.001
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 score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0480.023

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 head0.005
GPT teacher head0.249
Teacher spread0.244 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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