Bibliographic record
Abstract
Introduction to the 2019 Edition I n some significant ways, Canada is a different place than it was in 2013, the year Clearing the Plains was first published.Despite the official apology for the Indian Residential School system in the early days of the Stephen Harper government, there was a growing sense of frustration among many that simply saying sorry was not enough.Idle No More brought a new spirit of hope and activism to Indigenous peoples and it moved them into the national media's spotlight.The Truth and Reconciliation Commission, itself born of legal action in the aftermath of the apology, was making its way across the country, bearing witness to the thousands of lives still affected by residential schools.Ian Mosby's explosive article on nutritional experiments conducted on the children of residential schools was front-page news. 1 The horrific number of missing and murdered Indigenous women and girls fuelled an ever-growing call for an official response to address the issue.The horror of Indigenous young peoples choosing to end their lives, rather than continue to endure the humiliation of poverty, the pain of alienation from both their own traditions and mainstream Canadian society, and the hopelessness for any real change for their future, was a relentless reminder to all of us of the depth of inequity in our nation.In official circles, the impending bicentennial of the birth of Sir John A. Macdonald was seen as an opportunity to celebrate our success as Canadians that would culminate in the Canada 150 celebration in 2017.Canada-as the realization of Macdonald's vision, tenacity, and 1
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.711 | 0.653 |
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".