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Record W2889938366 · doi:10.3968/10458

Theories, Practices, Challenges, and the New Tendency in Connecting Reading and Writing

2018· article· en· W2889938366 on OpenAlexvenueno aff
Zhanfang Li

Bibliographic record

VenueCanadian social science · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)EnthusiasmTask (project management)Process (computing)Similarity (geometry)Writing processComputer scienceForeign languageMathematics educationLinguisticsPedagogySociologyPsychologySocial psychologyManagementArtificial intelligence

Abstract

fetched live from OpenAlex

Since the 21th centuary, the similarity views of reading and writing started an ever-lasting enthusiasm for connecting reading and writing. The present paper reviewed the studies in the recent 20 years and categorized them into the following four aspects. First, theoretical investigations were mainly concerned with the dynamic relationships between reading and writing and the cultivation of critical thinking in the connection process. Secondly, contextualized practices from foreign language teachers gave adequate evidence of the possibility and necessity of the integration. Thirdly, in the integration task, various challenges were faced by both the language teachers and the students. Finally, in the digital age, the Computer-assisted language learning (CALL) and computer-mediated communication (CMC) inevitably started a new tendency.

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)0.017
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.006
Science and technology studies0.0070.122
Scholarly communication0.0210.026
Open science0.0030.007
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.296
Teacher spread0.239 · 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 designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

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