What should teacher education be about? Initial comparisons from Scotland and Alberta
Bibliographic record
Abstract
This article empirically examines the ways in which Initial Teacher Education in Scotland and Alberta, Canada, seeks to ‘get students in’, ‘get them out and into the workforce’, ‘get on with teaching future teachers’ and how it should ‘get on with students’. Using Adams’ (2016) policy heuristic, which posits that policy can be discerned in three realms: frame; explanation; and formation, this paper considers the middle realm: that of policy explanation. Here, attempts to position policy through public pronouncement, policy directive, mandate and/or missive are examined in the context of ITE in Scotland and Alberta. By analysing policy explanations, the paper marks out how both jurisdictions should begin to attempt to craft ITE located in career-long, professional learning and development that understands and acknowledges tensions between ITE and later teacher-education phases. Finally, the paper makes a tentative proposal as to what such ITE might hope to achieve and how it might contribute to a well-developed workforce, so that both locations and other jurisdictions might orient initial teacher development.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".