Relational Ethics Through the Flesh: Considerations for an Anti-Colonial Future in Art Education
Bibliographic record
Abstract
In this article, we reflect on our teaching practices that include the development of an artist-in-residency program in one teacher education course and one graduate course in the Fall of 2022 at The University of British Columbia. During these residencies, Carrier Wit’at artist and printmaker Whess Harman and Indigenous scholar and a/r/tographer Jocelyne Robinson of the Algonquin Timiskaming First Nation demonstrate through their art practices how love and land are central tenets to relational ethics. We engage with Cherrie Moraga and Gloria Anzaldua’s theory in the flesh alongside the artists-in-residencies as we consider an anti-colonial future in art education. We propose the concept of relational ethics through the flesh as a reflexive, embodied, social justice–oriented way of being in the world.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.104 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".