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Record W7100138037

The Interactional Experiences of English Language Learners in the Malay Community: A Malaysian Case Study

2015· article· en· W7100138037 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMalayNarrativeSituatedLanguage acquisitionIdentity (music)NegotiationLanguage assessmentSocial constructivismSecond-language acquisitionFirst language
DOInot available

Abstract

fetched live from OpenAlex

This paper seeks to explore how learners of English who desire mastery of their second language ne-gotiate for access, participation, and acceptance in their various communities. To this end, it draws on the concept of communities of practice and constructivist notions of identity to provide a theoretical framework for understanding the process of adult second language learning beyond the classroom in non-native societies. By focusing on the situated experiences of a group of Malay learners gleaned through the use of first-person narratives in the form of student journals and focus group discussions, the study seeks insights into learners ’ beliefs and experiences as they negotiate their way through conflicting ideologies and practices in their world. Such stories, which are seldom heard and rarely analyzed, offer an important contribution to research on second language learning and teaching, and can help educators bridge the gap between classroom learning and real world experiences. Key words: identity, Malay learners of English, narratives Background Issues of identity and the second language learner have been the subject of much study and debate in recent years. In current research practices, learning a second language is seldom simply regarded as a skill acquired through persistence and practice as was traditionally maintained. Instead, utilizing constructivist frameworks, scholars have highlighted the complex social interactions and power diffe-rentials that engage the identities of language learners. Many of these studies have investigated adult learners of English in the traditional native-speaker countries like Canada, the United States, Australia

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.005
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.320
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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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