From discomfort to accountability: exploring an ethical relational approach to teaching anti-racism and decolonisation in a Canadian introductory social work classroom
Bibliographic record
Abstract
In this article, we share results from an introductory social work course evaluation that infused an ethical relational approach into anti-racist and decolonial pedagogy. 53 of the 137 students enrolled in the course provided written informed consent. A variety of creative approaches, including reflective writing, podcasts, infographics, social media posts, and letters to the editor, were used to capture students’ understanding of social work history, ethics, theories and approaches, and their emerging social work identity and future practice aspirations. The data was managed with NVivo 14, and thematic analysis was used to analyse the data. Study findings suggest that this approach contributed to students’ demonstrated awareness and comprehension of decolonial and anti-racist concepts, leading to critical self-reflection, empathy, and a greater appreciation for diverse perspectives. These findings emphasise the need for pedagogical advancements prioritising ethical relationality in preparing students for social work practice grounded in decolonial and anti-racist principles.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".