Using the Biopsychosocial Framework to Address the Ongoing Impacts of the Indian Residential School System and Colonization in Canadian Health Care Systems
Bibliographic record
Abstract
Traumatic experiences during childhood can have significant, detrimental impacts on physical and mental health and negatively impact social functioning in adulthood. Such an understanding is imperative to providing adequate and well-informed health care to Indigenous populations residing on the land now called Canada. The Indian Residential School (IRS) system, which was in operation for over one hundred years, was one of the most violent colonial tactics implemented by Canada's federal government. This system was conceptualized to forcibly alienate Indigenous children from their families, communities, and culture to eradicate Indigenous culture and identity. Combined with witnessing violent acts perpetrated by colonizers against members of their community, the shared experience of being abducted from their families, and suffering physical, mental, emotional, and sexual abuse, led to widespread trauma amongst Indigenous people for generations. It is expected that such trauma has resulted in disruptions in attachment, social functioning and emotional development in individuals who survived the Indian Residential School system, thus potentially triggering a cascade of maladaptive, trauma-related behaviours through subsequent generations (termed intergenerational trauma). These writers recommend that healthcare providers consult a biopsychological framework when engaging with Indigenous individuals, especially Indian Residential School survivors and their relatives, as it emphasizes the multidirectional relationship between psychological, biological, and experiential factors implicated in an individual's well-being. Furthermore, such a framework may aid in contextualizing an individual's unique challenges within the broader scope of colonization.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.032 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".