Navigating Two Worlds: Experiences of Counsellors who Integrate Aboriginal Traditional Healing Practices
Bibliographic record
Abstract
There is revival in the use of traditional healing among Canadian Aboriginal communities and the therapeutic benefits of these practices have received much research attention. An argument is repeatedly made for incorporating indigenous healing into clinical interventions, yet recommendations on how this may be accomplished are lacking. The present study aimed to address this limitation. We interviewed nine mental health professionals who routinely employ both Western psychological interventions and Aboriginal traditional healing practices. Grounded Theory data analysis identified four core themes and led to a model that illustrates participants’ integrative efforts. Implications for counsellors working with Aboriginal clients are addressed. Les pratiques traditionnelles de guerison refont surface dans les communautes Autochtones du Canada et les benefices de ces pratiques ont deja fait l’objet de plusieurs etudes. Malgre les suggestions repetees d’integrer les pratiques de guerison traditionnelles en pratique cliniques, il n’existe pas de lignes directrices pour guider ce processus. Cette etude se penche sur ce sujet. Nous avons interviewer neuf praticiens en sante mentale qui integre des pratiques traditionnelles de guerison Autochtones dans leur pratique psychologique. En utilisant la theorie a base empirique, nous avons identifie quatre themes principaux et elabore un modele qui illustre comment les participants arrivent a cette integration. Les implications pour les conseillers qui travaillent avec des clients Autochtones sont discutees.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.014 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".