Bibliographic record
Abstract
This partial grounded theory study explores the topic of Traditional medicine in social work practice in Toronto, Canada. Given the dearth of knowledge in this area, I wanted to explore the contrapuntal nature of two social workers’ practice who refer to Traditional Medicine, and to conceptualize further on this approach. Social work literature and practice has paid little attention to this topic despite the field’s purported commitment to equity and social justice. This is largely a reflection of how greatly we take for granted the bias towards Western medicine in our public health care system and in the social work referral system that is aligned with it. The World Health Organization defines Traditional medicine as: “Health practices, approaches, knowledge, and beliefs incorporating plant, animal, and mineral based medicines, spiritual therapies, manual techniques, and exercises, applied singularly or in combination to treat, diagnose, and prevent illnesses or maintain well-being” (Fokunang et al., 2011). Such approaches, which are based on Indigenous and non-Western ways of knowing are not covered by the Ontario Health Insurance Plan (OHIP), and thus remain largely inaccessible to the most financially marginalized. This is a problem for those who cannot afford to pay out of pocket for their health care. It is a grave disservice to those whose culture does not align with Western medicine; those whose health conditions have not been helped by Western medicine; and those who require a combination of Western and Traditional approaches to bring them to full health. This research explores the knowledge, experience, and processes of two social workers in Toronto who refer clients to Traditional medicine in spite of the structural bias towards Western medicine and its approaches. Key Words: Traditional medicine, social work practice, contrapuntal approach, decolonization, the Medicine Wheel, Toronto
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.018 | 0.028 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".