Awards and recognition for exceptional teachers : K-12 and community college programs in the USA, Canada and other countries. [Book Review]
Bibliographic record
Abstract
The purposes of schools adopting a teacher award and recognition structure are multiple. The structure can serve as a type of portfolio assessment that helps teachers attain important teaching abilities. It can create a setting in which serious discourse about teaching can occur – teaching is made public in a way that the outcomes of practice can be developed into shared norms of practice across the profession. More teachers are encouraged and challenged to achieve excellence, and highly qualified and motivated people are attracted to the teaching profession. Andrews is a major advocate of award structures and his work brings a wealth of knowledge and research to bear on this topic. Andrews’ book (see http://www.matildapress.com) is organised around three major foci: (i) it gives educational practitioners a guide for the successful implementation of a recognition programme; (ii) it encourages more governing boards to understand the need for recognition and award programmes for their teachers; and (iii) it exhibits best practices of awards and recognition from across the USA, Canada and elsewhere.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".