Bibliographic record
Abstract
Aboriginal peoples have been and continue to be subjected to multiple traumas and stressors that contribute to their greater risk for a variety of health and social problems.Among these health issues, cancer has been identified as the third leading cause of death in the First Nations population, and survival rates are lower because many are not diagnosed until it is too late.Due to the high prevalence and mortality rates of cancer, its diagnosis and treatment commonly evoke extreme psychological distress that can have significant implications for treatment and recovery.Having a greater understanding of risk factors that contribute to individual differences in psychological responses to cancer will help identify vulnerable populations and facilitate the development of culturally appropriate interventions.The present study assessed how familial Indian Residential School (IRS) attendance is linked with psychological distress among those with and without cancer in a representative sample of First Nations adults living on-reserve.Statistical analyses were carried out using data from the 2008-10 First Nations Regional Heath Survey (RHS), a representative survey of 4,934 First Nations living on-reserve from across Canada (excluding Nunavut).Analyses revealed that having a parent who attended IRS put First Nations adults diagnosed with cancer at greater risk for psychological distress relative to those without this family history.These findings point to the need for culturally safe cancer care for First Nations individuals and communities that have been affected by Residential Schools and other historical trauma events.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.699 | 0.484 |
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".