Book Review of "Truth and Reconciliation Through Education: Stories of Decolonizing Practices"
Bibliographic record
Abstract
Since the Truth and Reconciliation Commission released its final report in 2015, universities across Canada have attempted to respond to the calls to action forwarded by the commissioners.Some of those calls name specific Indigenous course requirements for faculties such as journalism, law, medicine, and nursing.Other calls encourage post-secondary institutions to offer degree programs in Indigenous languages and to establish reconciliation as an ongoing research area.Many of those calls are "in progress" according to the CBC's "Beyond 94" webpage, which keeps track of progress on the calls to action.While the degree to which "progress" has been made is dependent on the specific institution in question, it is hard to deny the attention devoted to truth and reconciliation in higher education in recent years.This movement has facilitated the publication of many edited collections focused on reconciliation and related topics in education (e.g., Cote-Meek & Moeke-Pickering, 2020; Styres & Kempf, 2022).Among these, Truth and Reconciliation Through Education: Stories of Decolonizing Practices, the recently published collection edited by Yvonne Poitras Pratt and Sulyn Bodnaresko, stands out for two reasons: its focus around a particular program, and its assertion that truth and reconciliation can happen through education.The book collects 23 essays by faculty members, students, and alumni of the "Indigenous Education: A Call to Action" master's certificate program offered at the University of Calgary.The program comprises four courses-two
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".