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
■ It has been suggested by some researchers that the world of the teacher of English as a foreign language is terra incognita . Little research seems to be widely available to map this world for external observers, particularly from the perspectives of non-native-speaking (NNS) teachers of the language working in those contexts where most English language teaching worldwide occurs—state education systems. This article aims to make a contribution to mapping the world of NNS language teachers through a case study of the life of a teacher of English in a government school in Thailand. It hopes to contribute to a wider contextual appreciation of teachers and teaching through exploring in particular this teacher's perceptions on her own language learning, her experiences as a teacher of English and her attempts to innovate in her classroom in a context which seemed to militate against such innovation. In so doing the study also aims to make a case for further research into the careers of NNS English teachers in order that the full richness and complexity of teaching and learning of English in the widest possible variety of socio-educational contexts can be revealed and compared.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it