Bibliographic record
Abstract
The Accord on Initial Teacher Education was created by the Canadian Deans of Education in 2006 to guide teacher educators across Canada. The Story Model (Drake et al., 1992) is aligned with the principles in the Accord and has proven useful in teacher education. Here it is explored as a framework for curriculum development and as an instructional strategy for students to analyze complex educational issues. This framework uses an inside-outside/past- future approach to analyze current issues and includes personal, cultural and global perspectives. Literacy and emerging new literacies are explored within the framework, as well as traditional assessment and assessment for and as learning. The Story Model looks toward creating a dynamic pan-Canadian “new story” in teacher education. En 2006, l’Association canadienne des doyens et doyennes des facultés d’éducation a créé l’Accord sur la formation initiale à l’enseignement afin de guider les formateurs des enseignants au Canada. Le modèle du récit (Story Model – Drake et al., 1992) correspond aux principes de l’Accord et a démontré son utilité en matière de formation des enseignants. Dans cet article, les auteurs le présentent à titre de cadre de référence pour l’élaboration de programmes d’enseignement, de même qu’à titre de stratégie d’enseignement permettant aux étudiants d’analyser des enjeux pédagogiques complexes. Ce cadre utilise une méthode intérieur-extérieur/passé-présent pour analyser les enjeux actuels et considère les perspectives personnelles, culturelles et globales. Les auteurs étudient la littéracie et les nouvelles littéracies, tout comme l’évaluation traditionnelle et celle qui est au service de l’apprentissage. Le modèle du récit (Story Model) vise à créer un « nouveau récit » pancanadien dynamique en matière d’éducation des enseignants.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".