Book Review: Troubling Truth and Reconciliation in Canadian Education: Critical Perspectives
Bibliographic record
Abstract
I reviewed Troubling Truth and Reconciliation in Canadian Education: Critical Perspectives with the hope, in transitioning full-time into the academy, that I would be provided solutions to a well-known 'reconciliation in education' predicament.Seven years after the release of the Truth and Reconciliation Commission of Canada's Final Report (2015), while the book through its many chapter contributors does not profess to provide definitive answers on reconciliation, the truths it does present, some troubling, some poignant, are real.In the introduction entitled, A Troubling Place to Start: Reconciliation in Collapse, Kempf et al get to the heart of the never-ending impasse, "We watch as many school boards and universities fumble awkwardly through land acknowledgements.Universities often assert commitments to "Indigenize the academy" …and develop grammars of colonial benevolence while simultaneously holding firm on practices of colonial reproduction" (p.xix).So continues the difficult dialogue on how we, Indigenous and non-Indigenous educators, administrators, and staff, should and must work together to Book Review: Varis viii
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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 | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.018 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".