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The role of gender in learning English as a foreign language

2022· article· en· W4285061467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACADEMICIA An International Multidisciplinary Research Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsEarl Haig Secondary School
Fundersnot available
KeywordsPsychologyLinguisticsForeign languageMathematics educationPhilosophy

Abstract

fetched live from OpenAlex

ESL learners may encounter a number of challenges while learning English as a foreign language. Gender difference is one of the crucial aspects that affect in language learning. This study aimed to identify what is the impact of gender on learners’ performances in learning English as a foreign language. This study was conducted at 22nd secondary school at Mirishkor District in Kashkadarya, Uzbekistan. A total of five classes were selected for participation in this experiment based on deeply specialized criteria and methods. At the end of the study, it was concluded that gender plays a crucial role on learning English due to environment as well as societal factors. In other words, males prone to learn languages mainly through using their senses. Therefore, it is highly suggestable for teachers to implement materials during the lessons that involve learners’ senses, and with this they may keep the balance between sexes.

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.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.003
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 head0.065
GPT teacher head0.452
Teacher spread0.387 · 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