Bibliographic record
Abstract
July 1st 1867 is celebrated as Canada's Confederation - the date that Canada became a country. But 1867 was only the beginning. As the country grew from a small dominion to a vast federation encompassing ten provinces, three territories, and hundreds of First Nations, its leaders repeatedly debated Canada's purpose, and the benefits and drawbacks of the choice to be Canadian. Reconsidering Confederation brings together Canada's leading historians to explore how the provinces, territories, and Treaty areas became the political frameworks we know today. In partnership with The Confederation Debates, an ongoing crowdsourced, non-partisan, and non-profit initiative to digitize all of Canada's founding colonial and federal records, this book breaks new ground by integrating the treaties between Indigenous peoples and the Crown into our understanding of Confederation. Rigorously researched and eminently readable, this book traces the unique paths that each province and territory took on their journey to Confederation. It shows the roots of regional and cultural grievances, as vital and controversial in early debates as they are today. Reconsidering Confederation tells the sometimes rocky, complex, and ongoing story of how Canada has become Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.028 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".