Teaching reconciliation by educating non-Indigenous communities
Bibliographic record
Abstract
How is it possible to teach Canadian pupils about their history by repairing the cultural erasure of the indigenous populations? This was the question that Deni Élis Béchard and the Innu writer Natasha Kanapé Fontaine raised in their conversation about structural racism in Kuei my friend. This pedagogical dialogue followed the report of the Truth and Reconciliation Commission in Canada which was established as a result of the Statement of Reconciliation of the 7th of January 1998 to collect evidence about the situation of residential for Indigenous children (TRS, 2009-2015). This commission illustrated the institutionalization of memory as an attempt of analysing the consequences of such an official violence against First Nations communities (MacDonald, 2017: 168). The presentation focuses on the analysis of this dialogue between a famous reporter in Québec and an Innu writer. What are the main topics of this conversation? This dialogue on reconciliation will be analysed with the help of two approaches, on the one hand non-violent communication that produces empathy to rebuild links with discriminated communities and on the other hand the mediation (Faget 2010). Empathy differs from sympathy; it implies a discrete connection between people from antagonistic backgrounds. A specific focus will be devoted to the proposed exercises of the dialogue between Béchard and Fontaine at the end of the book. The challenge of the presentation is to explore the possibilities of restoring a dialogue between communities in Canada. This presentation was made during the 21st International Baltic Conference on Canadian Studies on "Canada: diversity, inclusion, equity"
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".