A railway runs through it: “Tracking Canada’s Past ” in the schools
Bibliographic record
Abstract
Education being a social process, the school is simply that form of community life in which all those agencies are concentrated that will be most effective in bringing the child to share in the inherited resources of the race, and to use his own powers for social ends. (Dewey 1897) For many years now, the participants in this seminar and many of our colleagues have explored the question of what it means to know and understand History — meaning not only knowledge of specific, culturally-valued events and people from the past, but also knowledge of how the past comes to be understood by historians. The body of scholarship built over the past decade, in particular, has made considerably clearer what a difficult enterprise it is for students to build a mature understanding of History as a discipline, and has identified many of the stumbling blocks to students ’ success in this endeavour. To mention a few of the hurdles familiar in this circle: • Textbook accounts of historical events are often oversimplified, and present a single, homogenized perspective on events (Beck and McKeown 1994; McKeown and Beck 1994), usually in a depersonalized voice (Wineburg 1991).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.063 | 0.023 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".