Bibliographic record
Abstract
Although historical thinking has been the subject of a substantial body of recent research, few attempts explicitly apply the results on a large scale in North America. This article, a narrative inquiry, examines the first stages of a multi-year, Canada- wide project to reform history education through the development of classroom- based assessments. The study is based on participant-observations, documents gen- erated by the project, and interviews, questionnaires, and correspondence with parti- cipants. The authors find impediments – apparently surmountable – in teachers’ ap- plication of potentially difficult concepts, and in their organizational resistance. Key words: assessment, historical thinking, history education, narrative inquiry Bien que la pensee historique ait ete recemment le sujet de nombreuses recherches, peu d’entre elles tentent explicitement d’en appliquer les resultats sur une large echelle en Amerique du Nord. Dans cet article, l’auteur decrit les premieres etapes d’un projet canadien de plusieurs annees visant a reformer les cours d’histoire en recourant a des evaluations basees sur les classes. L’etude s’appuie sur l’observation des participants, des documents generes par le projet ainsi que des entrevues, des questionnaires et de la correspondance avec les participants. Les auteurs identifient des obstacles – apparemment surmontables – a la mise en application par les enseignants de concepts potentiellement difficiles et notent leur resistance organisa- tionnelle. Mots cles : evaluation, pensee historique, cours d’histoire, recherche descriptive
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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 | 0.044 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.026 | 0.036 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".