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.
Bibliographic record
Abstract
Introduction: Second and Additional Language Learning through Drama Joe Winston *'Dramatic' Language Learning in the Classroom Li-Yu (Sabina) Chang * Using Stories and Drama to teach English as a Foreign Language at Primary Level Li-Yu (Sabina) Chang and Joe Winston * Theatre, Language Learning and Identity (1): empowering additional language learners through theatre in education Deborah Hull * Theatre, Language Learning and Identity (2): empowering additional language learners through classroom drama projects Erene Palechorou and Joe Winston * Drama and languages education: authentic assessment through process drama Julia Rothwell * Accessing traditional tales: The Legend of Bukit Merah Madonna Stinson * Insights from a drama/EAL classroom: Using drama with English language learners in a Canadian high school Burcu Yaman Ntelioglou * Using drama to enrich School Based Assessment in the Hong Kong secondary school English language classroom Tanya Kempston * Second language learning and cultural empowerment: teaching Shakespeare in Taiwan Yi-Mei (Astrid) Cheng and Joe Winston * Digital storytelling, drama and second language learning Kirsty McGeoch * Film & drama aesthetics for Additional Language teaching Erika C. Piazzoli
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.220 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it