To the past : history education, public memory, and citizenship in Canada
Bibliographic record
Abstract
Recent years have witnessed a breakdown in consensus about what history should be taught within Canadian schools; there is now a heightened awareness of the political nature of deciding whose history is, or should be, included in social studies and history classrooms. Meanwhile, as educators are debating what history should be taught, developments in educational and cognitive research are expanding our understanding of how best to teach it. To the Past explores some of the political, cultural and educational issues surrounding what history education is, and why we should care about it, in the twenty-first century in Canada. Originally broadcast in the fall of 2002 on the CBC Radio program Ideas, the lectures that comprise this volume not only address how history is taught in Canadian classrooms, but also explore strands within larger discussions about the meaning and purposes of history more generally. Contributors show how Canadians are demonstrating a new interest in what scholars have termed 'historical consciousness' or collective memory, through participation in a wide range of cultural activities, from visiting museums to watching the History Channel. Canadian adults and children alike seem to be seeking answers to questions of identity, meaning, community and nation in their study of the past. Through this series of essays, readers will have the opportunity to explore some of the political and ethical issues involved in this emerging field of Canadian 'citizenship through history' as they learn about public memory and broadly defined history education in Canada
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.036 | 0.013 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".