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Record W2151534828 · doi:10.5430/elr.v3n1p66

Adapting English Newspapers to Develop Language Proficiency in Low-Level EFL Learners

2014· article· en· W2151534828 on OpenAlex
Yi-chun Pan

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnglish Linguistics Research · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperAdaptation (eye)ComprehensionReading (process)Reading comprehensionLanguage proficiencyComputer scienceNothingPsychologyMathematics educationLinguisticsPedagogySociologyMedia studies

Abstract

fetched live from OpenAlex

Students can increase their awareness of current events and develop into knowledgeable citizens of the world by reading the news. Authentic English news items, however, often contain difficult linguistic elements (including lexica and structures) that may prevent low-proficiency students from developing a genuine comprehension of the material, thus reducing this useful information to nothing more than a waste of paper. In order to provide students with lower levels of proficiency the opportunity to acquire more knowledge about the world while simultaneously improving their language abilities, this paper illustrates the adaptation of an authentic news item for low-proficiency learners.This research will identify the objectives of teaching an authentic news item, adapting and presenting it in a classroom environment, and will describe the student response to this instruction.

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)0.006
metaresearch head score (Gemma)0.226
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.226
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.101
GPT teacher head0.355
Teacher spread0.255 · 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