Catherine Carstairs, Bethany Philpott, and Sara Wilmshurst, Be Wise! Be Healthy! Morality and Citizenship in Canadian Public Health Campaigns
Bibliographic record
Abstract
intended goals.Drawing from diverse disciplines including history, philosophy, psychology, and education, Curren and Dorn provide an insightful account of the aims, rationales, methods, and conceptions that have been featured in US patriotic education.Unfortunately, their comprehensive theory of civic education centred on the notion of virtuous patriotism fails to convincingly address previous critiques of patriotic education raised by citizenship educators.Wineburg's book is more of a compilation of his greatest hits than an original and comprehensive account of what history education can contribute to civic education in an information-infused society.His contention that history education should focus on nurturing the dispositions and abilities to help students differentiate fact from fiction offers an inadequate justification for learning history in the twenty-first century.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.022 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".