The Truth and Reconciliation Commission of Canada: Insights into the Goal of Transformative Education
Bibliographic record
Abstract
In 2006, the Government of Canada announced the approval of a final Residential Schools Settlement Agreement with the collaboration of the four churches responsible (United, Anglican, Presbyterian, Catholic), the federal government and residential school survivors. Schedule "N" of the Agreement lists the mandate of the TRC; therein, the TRC states one of its goals as: (d) to promote awareness and public education of Canadians about the system and its impacts. Can education - as the TRC hopes to engender - truly be transformative, renewing relationships and promoting healing in the process of forging these new relationships? The literature reviewed and the conferences attended highlighted that generating empathy may be a necessary ingredient for the instigation of social change, but is insufficient. Transformation through education, or reconciliation through truth-telling, testimonial reading and responsible listening would mean claiming a genuine, supportive responsibility for the colonial past. Educational policy and media initiatives are fundamental to creating awareness, developing public interest and support of the TRC's recommendations. However, authors also stress the importance of critical pedagogy in the whole process of truth and reconciliation, and that real reconciliation would require confronting the racism that initiated these institutions and allowed for a decontextualization of their impacts.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.053 | 0.035 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".