Racial discrimination and biological dysregulation among Indigenous adults: The role of culture
Bibliographic record
Abstract
Abstract Background Racial discrimination is an ongoing social concern that requires public health solidarity to address. Indigenous peoples in many countries report high levels of discrimination across a variety of life domains, particularly when they migrate into urban centres for school or work. Discrimination has wide-ranging impacts that go beyond mental distress to include alterations in stress biomarkers across multiple systems. This study examined the impacts of discrimination on multisystem biological dysregulation among urban Indigenous adults in Canada, operationalized through allostatic load; and the role that Indigenous cultural continuity might play in resilience. Methods This cross-sectional study collected data from 150 Indigenous adults attending university in a small city in western Canada between 2015 and 2017 (M age: 28 years). Allostatic load (AL) was measured as a composite of 7 biomarkers assessing neuroendocrine, cardiovascular, metabolic, and immune system function. Bias-corrected and accelerated bootstrapped linear regression models examined associations adjusted for confounders. Results Past-year discrimination was significantly and linearly associated with increased AL adjusting for age and income (B = 0.17, p = 0.02). Among adults with low cultural continuity, past-year discrimination was associated with AL in models adjusted for age and child discrimination (B = 0.17, p = 0.01), with past-year discrimination and the full model explaining 24% and 41% of the variance in AL; respectively. Among adults with high cultural continuity, past-year discrimination was not associated with AL, and the full model explained 1% of the variance in AL. Conclusions Past-year racial discrimination was an adverse event capable of influencing multisystem biological dysregulation among Indigenous adults, independent of age and income. Indigenous cultural continuity may promote biological resilience against racism within this population. Key messages Racial discrimination was associated with multisystem biological dysregulation among urban Indigenous adults, controlling for age and income. Indigenous cultural continuity buffered the impact of discrimination on biological health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".