Bibliographic record
Abstract
04–95 Andrews, Stephen (University of Hong Kong, Hong Kong SAR, China). Teacher language awareness and the professional knowledge base of the L2 teacher . Language Awareness (Clevedon, UK), 12 , 2 (2003), 81–95. 04–96 Carless, David R. (Hong Kong Institute of Education; Email : dcarless@ied.edu.hk ). Putting the learning into assessment . The Teacher Trainer (Canterbury, UK), 17 (2003), 14–18. 04–97 Gupta, Renu (National University of Singapore, Singapore). Old habits die hard: literacy practices of pre-service teachers . Journal of Education for Teaching (Abingdon, UK), 30 , 1 (2004), 67–78. 04–98 Lamb, Terry (Sheffield U., UK; Email : t.lamb@sheffield.ac.uk ) and Simpson, Michael. Escaping from the treadmill: practitioner research and professional autonomy . Language Learning Journal (London, UK), 28 (Winter 2003), 55–63. 04–99 Lawes, Shirley (London U., UK). What, when, how and why? Theory and foreign language teaching . Language Learning Journal (London, UK), 28 (Winter 2003), 22–28. 04–100 Moris, Lori (Universite du Québec à Montreal, Canada). Linguistic knowledge, metalinguistic knowledge and academic success in a language teacher education programme . Language Awareness (Clevedon, UK), 12 , 2 (2003), 109–122. 04–101 Mullock, Barbara (University of New South Wales, Australia). What makes a good teacher? The perceptions of postgraduate TESOL students . Prospect (Sydney, Australia), 18 , 3 (2003), 3–24. 04–102 Roessingh, Hetty and Kover, Pat (U. of Calgary, Canada). Variability of ESL learners' acquisition of cognitive academic language proficiency: what can we learn from achievement measures? TESL Canada Journal/Revue TESL du Canada (Burnaby, Canada), 21 , 1 (2003), 1–21. 04–103 Simpson, Carole, Popovic, Radmila and Stojanovic, Smiljka. Modifying tasks in teacher education sessions to meet learners' need better . The Teacher Trainer (Canterbury, UK), 18 , 1 (2004), 5–? 04–104 Walsh, Steve (Queen's University Belfast, Northern Ireland). Developing interactional awareness in the second language classroom . Language Awareness (Clevedon, UK) 12 , 2 (2003), 124–142. 04–105 Wang, Wendy (OISE, U. of Toronto, Canada). How is pedagogical grammar defined in current TESOL training practice? TESL Canada Journal/Revue TESL du Canada (Burnaby, Canada), 21 , 1 (2003), 64–78. 04–106 Yurtseven, Bengü (Bilkent U., Turkey; Email : bengu@bilkent.edu.tr ). Three-way observation: including language learner feedback . The Teacher Trainer (Canterbury, UK), 17 (2003), 3–6.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".