How should citizenship be integrated into high school history programs? Public controversies and the Québec History and Citizenship Education curriculum: an analysis
Bibliographic record
Abstract
From 30 July to 2 August, 2009, over 2,000 North American tourists had prepared to go to Quebec City to re-enact an episode of the Seven Years War: the battle of the Plains of Abraham in Quebec City, where two European colonial powers had clashed on 13 September, 1759. As is usual for this type of lay gathering, everything that has fascinated 20 century history scholars was excluded from the planned spectacle, such as issues of family, material culture, and the social structures of the people involved. Such an event illustrates the interest a number of people have, worldwide, in a particular approach to the past, based on what Barton and Levstik (2004) call the exhibition stance. According to Rosenzweig and Thelen (1998), Letourneau (2008), and Conrad, Letourneau and Northrup (2009), such activities are widespread, and might illustrate the centrality of the past for the re-enactors’ identities. This particular event especially encapsulates the popular appeal of this kind of relation to the past, inasmuch as the reenactors devote considerable time to learning their re-enactment roles and spend significant financial resources to buy the accessories they need.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".