MétaCan
Menu
Back to cohort
Record W2916675878 · doi:10.1075/lllt.52.10spa

Discussion

2019· book-chapter· en· W2916675878 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

VenueLanguage learning and language teaching · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Abstract In this chapter I reflect on the contributions to this volume with respect to two guiding criteria: Relevance to classroom applications and Advantages and challenges of methodology. I examine the goals, focus, and research questions investigated in the descriptive, quasi-experimental and experimental studies presented in this collection. I analyze their methodological characteristics in terms of cost, ethics, participant availability, experimental control, teacher collaboration, student motivation, and generalizability. I argue that all the ISLA studies presented in this volume are relevant to L2 pedagogy. Echoing the words of the editors, I also argue that placing experimental and descriptive research into a dichotomous relationship where the former is characterized as not relevant to the classroom and the latter as lacking validity is problematic. Such a categorization fails to acknowledge the different purposes of both types of research and the different contributions each can make to L2 pedagogy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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