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Record W4386220893 · doi:10.5539/ells.v13n3p59

Vowel Blindness and Gender: The Case of ESL Learners at the University of Jeddah

2023· article· en· W4386220893 on OpenAlexvenueno aff
Rahaf Bandar Almoabdi

Bibliographic record

VenueEnglish Language and Literature Studies · 2023
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVowelSpellingPsychologyNasal vowelVocabularyLinguisticsFirst languageNoticeAffect (linguistics)Reading (process)Communication

Abstract

fetched live from OpenAlex

Because vocabulary knowledge is considered the building block of language learning, any difficulties concerned with vocabulary can harm the overall vocabulary acquisition process. Literature suggests that native Arabic speakers struggle to notice vowels while reading English texts. This can result from the differences between L1 and L2 linguistic systems or the negative transfer of L1 processing routines to the L2 in their attempt to process the L2 forms. This study investigates this problem and whether gender affects this phenomenon or not. It used a test on Twenty-eight participants to examine the effect of gender on vowel blindness, which type of vowels (short or long vowels) are more problematic, and the kinds of vowel spelling errors that are easily noticed when processing vowels. The results showed that gender does not affect vowel blindness in a significant way. In other words, the overall results showed that the role of gender cannot be considered to have a significant effect. Thus, male and female students both struggled to deal with short vowels equally. However, males also showed difficulties regarding the long vowels. The research also revealed that missing vowel spelling errors are salient and more likely to be noticed while processing vowels for both genders.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.306
Teacher spread0.286 · 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 designQualitative
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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