Response-Based Practice Informed Art Therapy for Non-Indigenous Practitioners Working with Indigenous Children Affected by Domestic Violence
Bibliographic record
Abstract
The following research examines how non-Indigenous art therapy practitioners might ethically and effectively support Canadian Indigenous children who have experienced domestic violence by integrating response-based practice into an art therapy intervention framework. While this study is grounded in the Canadian context, with appropriate cultural and contextual adaptation its findings may be relevant to art therapy practitioners in other settler-colonial nations working with Indigenous populations. Through a scoping review of relevant literature, this research identifies theoretical and practical alignments between response-based practice and various art therapy modalities, including client-centered, strengths-based, and trauma-informed approaches. Findings indicate that these approaches are compatible in their consideration of contextual factors, decentralization of pathology, promotion of client agency, and ethical mandate to pursue therapeutic work from an anti-oppressive stance, making their integration a promising direction for therapeutic work with this population. Tools like the Medicine Wheel of Resistance, and theoretical approaches such as the Expressive Therapies Continuum offer complementary methods for assessment and structuring therapeutic interventions, supporting both verbal and non-verbal forms of expression. However, the integration of these methods is underdeveloped in current literature and epistemological tensions present challenges. Additionally, the absence of direct consultation with Indigenous communities and children limits this research's applicability. Future studies should pursue collaborative, community-based research with Indigenous nations and communities to further develop and evaluate the effectiveness of integrative therapeutic models.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".