Bibliographic record
Abstract
This paper focuses on Alberta, Canada's 1998 "Teacher Growth, Supervision and Evaluation " policy, examining its origins and adoption along with the significant shift in images of teaching and supervision that it conveys. Both the process and substance of the policy are analyzed within the context of Alberta's larger plan to restructure education during the 1990s. Following an overview of the larger study upon which this paper is based, five key conceptual issues are addressed in a review of relevant literature (e.g., policy cycles and policy learning, successful educational reform, policies to encourage quality teaching, teacher supervision and evaluation and images of practice). The next two sections review aspects of the origin and adoption phases of this policy change. The paper discusses the image of policy change as learning and notes a metaphor of reform as capacity building. It concludes that this policy serves as an exemplary model for future educational reform. (Contains 148 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document. rip
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 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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.223 | 0.057 |
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".