Decolonizing the Conceptualization of Trauma: An Indigenous Focusing-Oriented Approach
Bibliographic record
Abstract
Counselling psychology prides itself on social justice and diversity in treatment modalities. Yet, many Indigenous clients continue to receive culturally irrelevant treatment, as evidenced by high dropout rates and mistrust of the health care system. In 2015, the Truth and Reconciliation Commission of Canada (TRC) released 94 calls to action directly addressing the unlawful treatment of Indigenous Peoples throughout Canada. In response to the TRC and with the goal of decolonization, reconciliation, and reclamation, a jointly-struck task force was created on behalf of the Canadian Psychological Association and the Psychology Foundation of Canada. The task force highlighted the need for ethical Indigenous research and culturally relevant approaches to psychological treatment for Indigenous Peoples; hence, this research is a direct response to both documents. Utilizing a relational methodology and Indigenous research methods of conversation, witnessing, and reflexive journaling, this study sought to understand the conceptualization of trauma within Indigenous Focusing-oriented therapy (IFOT). Grounded in land and an Indigenous ontology, IFOT is a holistic, decolonizing approach to health and wellbeing. Resulting from the wisdoms shared by four knowledge holders versed in the teachings of IFOT, the conceptualization of trauma is understood through the Trauma Wisdom Tree and Medicine Roots. Indigenous Peoples hold centuries of wisdoms having survived through intergenerational trauma and cultural genocide. Thus, through connection with our Medicine Roots, clients can restore healing, balance, and harmony. Moreover, reflecting on the concept of survivance, intergenerational trauma and resistance to colonialism is honoured. In addressing decolonization, cultural appropriation, and the issue of “evidence”, these findings present implications for practice, research, and social justice within education, counselling psychology, and related fields.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.067 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".