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Record W4381741192 · doi:10.55606/jupensi.v3i2.2008

The Importance Of English Vowel In English Linguistics For Literacy Study

2023· article· en· W4381741192 on OpenAlexaboutno aff
Masita Hamidiyah, Azzahra Natasya, Yani Lubis

Bibliographic record

VenueJurnal Pendidikan dan Sastra Inggris · 2023
Typearticle
Languageen
FieldComputer Science
TopicEnglish Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsPronunciationBritish EnglishAmerican EnglishLiteracyLinguisticsVowelVarieties of EnglishVocabularyAustralian EnglishEnglish languageEnglish-based creole languagesEnglish studiesPopulationFirst languagePsychologySociologyHistoryModern languageLanguage assessmentPedagogy

Abstract

fetched live from OpenAlex

English is a native-speaking language hundreds of millions of the world's population consisting of Americans, Australia, New Zealand, Canada and of course·only the British themselves. This fact allows the emergence of several English variants or varieties; Among another emergence of British English and American English. In the world of education, English as a language foreigners in Indonesia, the second variant has not received attention. Most English teaching institutions without be the choice of certain English variants. On Basically, the official provisions regarding this matter are not yet there is. However, there are variants of British English and American English can bring teacher doubts in dealing with abnormalities, vowel, vocabulary, or pronunciation the language. This is one of the considerations for the need to know English variants for prospective teachers and students English teacher, especially when the American influence is growing.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.291
Teacher spread0.277 · 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
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

Citations1
Published2023
Admission routes1
Has abstractyes

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