Unlearning clubs: creating environments of cultural safety, anti-racism, and trustworthiness in population and public health
Bibliographic record
Abstract
BACKGROUND: Unlearning is a necessary practice for disrupting the deeply ingrained colonial narratives and racialized assumptions that sustain racism in Canada. We created and implemented an "Unlearning Club" in British Columbia's Office of the Provincial Health Officer (OPHO). It is a structured and on-going space where public health professionals and trainees critically engage with Indigenous rights, anti-racism, anti-white supremacy, and cultural safety. METHODS: The Unlearning Club and the reflective research presented in this paper draw on the frameworks of Dr. Camara Jones and Jody Wilson-Raybould to guide three key processes: naming racism and white supremacy (LEARN), asking, how are they operating here (UNDERSTAND), and organizing and strategizing to act (ACT). To document teachings and reflections, we used two approaches. Participants completed a structured rapid reflection tool (n = 67) after each session to capture experiences and insights. Second, Unlearning Club hosts engaged in a relational reflection process, allowing for deeper discussion on lessons learned and future directions. PRAGMATIC REFLECTIONS: (1) Spotlighting Land Acknowledgement: starting each session with a more in-depth land acknowledgments allowed participants to ground their unlearning in the place-based inherent rights of Indigenous Peoples. (2) Relational Accountability: Unlearning Club nurtured solidarity and accountability among colleagues, giving tools needed to move into action. (3) Sustained Unlearning: The process of unlearning led to profound shifts in perspective, as individuals were unable to "unsee" pervasive ways in which white supremacy operates, moving individuals beyond feeling paralyzed by injustice. (4) Collective Responsibility: The cohort model allowed relationship-building and fostered shared commitment to addressing racism and white supremacy, creating a stronger group-wide sense of purpose and accountability. (5) Counters Resistance: Eagerness and gratitude was widespread among participants; individuals were willing to invest the time and effort necessary to engage deeply in the unlearning process. (6) Moving to Action: Participants highlighted the effectiveness of the "Learn, Understand, Act" framework in preventing stagnation. This structured approach offered clear pathways to translate new insights into tangible actions. CONCLUSION: The Unlearning Club has emerged as a pivotal strategy for fostering environments of cultural safety, anti-racism, and trustworthiness within our public health office. Sustained engagement in anti-racist education, supported by strong leadership and an inclusive structure, can significantly reduce resistance to anti-racism initiatives.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".