Bibliographic record
Abstract
This edited book is a comparative study on teacher education across ten major Englishspeaking regions of the world (USA, English Canada, England and Wales, Scotland, Ireland, Singapore, Hong Kong, South Africa, Australia, New Zealand). The focus on individual regions is reflective of a comparative approach with a long tradition going back to the turn of the twentieth century. This approach is still valid at the present time as it provides one of the best ways of initially structuring our understanding of teacher education at the macro level in order to facilitate communication of the situation crossnationally and prepare the way for higher levels of analyses. To this end, the book has twelve chapters: An introductory chapter details the focus of the book. This is followed by a chapter on each of the ten regions. Each of these chapters, written by an expert in the field: focuses on general trends in teacher education rather than on any specific aspect of it; focuses primarily on pre-service teacher education at the primary and post-primary levels, although some reference is also made to continuing professional development; strikes a balance between past, present and future trends; deals broadly with access to, the processes involved in, and the structure of, teacher education; has a unique structure rather than one based upon a formulaic approach. In the final chapter major themes are distilled from the case studies. It also outlines how the book furthers understanding of teacher education internationally, considers other groupings of regions ripe for consideration along similar lines, and indicates initiatives arising out of the case studies worthy of consideration for the improvement of teacher education cross-nationally. [Book Synopsis]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.463 | 0.281 |
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 source (direct Gemma or distilled Codex), 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".