Childhood racial discrimination and adult allostatic load: The role of Indigenous cultural continuity in allostatic resiliency
Bibliographic record
Abstract
OBJECTIVE: To examine the association between racial discrimination experienced in childhood on allostatic load (AL) in adulthood, and whether this association differed by cultural continuity among Indigenous adults. METHOD: Data were collected from Indigenous adults attending university in a small city in western Canada between 2015 and 2017 (N = 105). The frequency of childhood racial discrimination was measured using an item modified from the Experience of Discrimination Scale. AL was measured as a composite of 7 biomarkers assessing neuroendocrine, cardiovascular, metabolic, and immune system function. Cultural continuity was measured using the Vancouver Index Enculturation Scale. Bootstrapped linear regression models examined associations adjusted for confounders, with and without stratification by a dichotomized measure of Indigenous cultural continuity. RESULTS: Most Indigenous adults (72.3%) experienced racial discrimination some or most of the time in childhood. The frequency of child discrimination was significantly associated with AL, explaining 11% of the variance in adult AL score after adjustment for age and income. In the high cultural continuity group, there was no association between child discrimination and adult AL. In the low cultural continuity group, child discrimination was significantly associated with AL, explaining 21% of the variance in adult AL score. CONCLUSION: Childhood racial discrimination may have a biological toll on adult health through altered activation of the stress response system which could, over time, exacerbate health inequities in this population. High Indigenous cultural continuity served as a resilience factor that buffered the adverse impacts of childhood discrimination on adult AL score.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".