Bibliographic record
Abstract
Melissa and Sandra begin Pathway 8 by revisiting the synergy between being and doing. Many of the Teachings and practices in this book invite practitioners to lean into their awareness as cultural and relational beings before they engage in doing therapeutic work. Melissa shares a nehiyaw (Cree) Teaching about how small changes ripple outward. This Teaching honours connections between caring for ourselves as helpers or healers and caring for those we walk alongside. Melissa and Sandra position microlevel therapeutic change after systems level change (Pathway 7) to ensure that practitioners carefully consider systemic, contextual factors in understanding and addressing client challenges. Their intent is to disrupt conventional individualist perspectives on health and healing. This decolonial and anti-pathologizing approach creates space for multiple levels of complementary change, including change processes within microlevel contexts of clients’ lives. To balance being and doing, the chapters in this pathway begin with a focus on presence and self-reflection. Embracing a self-reflective way of being allows counsellors and psychotherapists to offer the best of themselves to clients, while holding client stories with care and integrity. The chapters in the second half of Pathway 8 focus on the doing of culturally responsive care, drawing forward the focus on epistemological pluralism to invite consideration of multiple ways of knowing, being, and doing. To embrace a stance of cultural humility, Sandra and Melissa draw on the Wise Practices lens from Pathway 6 as a framework for responsibly and ethically amplifying Indigenous and other culture-centred approaches to health and healing. Melissa and Sandra are joined in this Pathway by co-author, Kaltrina Kusari, who offers a visualization exercise that invites readers to notice how awareness can open space for deeper connection and more meaningful engagement in health, healing, and care.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.047 | 0.013 |
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".