Reconciliation through Art: The Power of Unmasking Identity
Bibliographic record
Abstract
The education system has established institutional hierarchies and perpetuated different forms of oppression that restrict the learning experiences of diverse students across Canada. Oppression is a significant problem within education. One of the ways that educators address and disrupt oppression within education is through reconciliation. By giving educators a chance to engage in reconciliation, they can learn about Indigenous ways of knowing, what reconciliation is, and build new relationships with their diverse students. By using arts-based practices, it can create a space where educators can experience a deep exploration and understanding of themselves and others by re-imagining lived experiences in and through time. By combining arts-based practices and reconciliation together, it gives educators the opportunity to develop awareness of their positionality, develop supportive environments, have critical conversations to promote reconciliation, be accountable to the diverse community, foster vulnerability, and develop allyship. Through critical artistic reflection on their practice in conjunction with learning reconciliation strategies, educators can learn to reflect on their practice in such a way that they become more aware of how to disrupt oppression within their classroom.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.047 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".