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Record W2293942340 · doi:10.18192/olbiwp.v7i0.1355

Introduction: Literacies and autonomy of the advanced language learner

2015· article· en· W2293942340 on OpenAlexaffvenueabout
Nikolay Slavkov

Bibliographic record

VenueOLBI Journal · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAutonomyTheme (computing)Learner autonomySociologyPedagogyDiversity (politics)Section (typography)Field (mathematics)Engineering ethicsLanguage educationComputer sciencePolitical scienceComprehension approachEngineeringWorld Wide Web

Abstract

fetched live from OpenAlex

The present volume contains ten articles related to the literacies and autonomy of the advanced language learner, which was the overarching theme of the 2014 CCERBAL Conference organized by the OLBI and hosted by the University of Ottawa. This theme was implemented in various ways and within various scholarly domains during the conference, representing work related to the main pillars of the OLBI’s expertise: language teaching, language policy, language assessment and technology-enhanced language learning. Similarly, the articles in this issue revolve around these core areas and represent a diversity of perspectives generated by both established researchers and emerging scholars. Some of the articles draw on completed research projects, others report on work in progress or pilot studies, and still others are based on pedagogical workshops. This mix of approaches and perspectives exemplifies the dynamic nature of the field and is indicative of the vibrant research and teaching culture fostered by the OLBI and its research centre, the CCERBAL. The volume is introduced by a lead article, and the rest of the submissions are divided into two sections: Research and Pedagogical Perspectives. The Research section contains articles based on empirical studies, while the Pedagogical Perspectives section contains articles based on reflections on classroom practices or teaching workshops. Some of the articles contain elements from both categories, which highlights the interconnectedness and, in some cases, fusion of research and practice. This invites us to pause for a moment and rethink some of the traditional lines that we are used to drawing in conceptualizing scholarly communication.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.005
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0120.004

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreEditorial

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 routes3
Has abstractyes

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