Trauma-Informed Yoga Psychology: Theory and Practice
Bibliographic record
Abstract
This chapter introduces trauma-informed yoga psychology as a wholistic, culturally responsive approach to understanding and healing trauma. Readers will explore the types of trauma and the impacts of trauma on the nervous system, including polyvagal theory, triggers, glimmers, and principles of trauma therapy. Melissa and Michael highlight how trauma is both personal and political, shaped by the enduring impacts of colonization and systemic oppression. Integrating decolonization into trauma-informed care offers a transformative path to honouring Indigenous Knowledges, worldviews, and healing practices while fostering cultural safety, partnership, and community-led solutions. Guided by Etuaptmumk, or Two-Eyed Seeing, this chapter invites readers to consider how integrating psychological frameworks with Indigenous Wisdom traditions can support more inclusive care that centres body, mind, spirit, and heart. This includes practices such as trauma-informed yoga and mindfulness Indigenous to South Asia. Through the authors’ work at the Trauma-Informed Yoga Psychology School, they share how blending the insights of psychology with ancient yoga traditions can deepen practice and contribute to healing rooted in cultural humility, agency, and relational care. Melissa and Michael are so appreciative of the contributions by these co-authors: • Swaati Mehra-Ramcharan offers trauma-informed yoga practices that support grounding, presence, and choice, drawing on her connection to Indian culture, Hindu philosophy, and spiritualism. • sakâw laboucan shares a powerful poem and reflection from a queer nehiyaw perspective, inviting readers to consider storytelling as a pathway for reclaiming spirit, identity, freedom, and miyo pimatisiwin. • Nicole Lightning-Strongman offers visual and audio reflections through Tree of Life: Indigenous and Yoga Teachings, inviting deeper awareness of relationality, interconnectedness, and the sacred relationships that sustain us. • Kitana Connelly shares Waves Unseen, a visual reflection on the layered emotional currents of generational trauma, pride, and healing.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".