Social Inequalities and the Road to Allostatic Load: From Vulnerability to Resilience
Bibliographic record
Abstract
Abstract Vulnerability and resilience are intertwined yet unraveling constructs in the allostatic load literature centered on stress‐disease pathways. In examining this paradigm shift, this chapter focuses on allostatic load indices of multisystemic physiological dysregulations among marginalized populations. Social inequalities reviewed include early adversity, socioeconomic health gradients, race/ethnicity and discrimination, Brazil's shifting economy, the struggles of North American and Australian Indigenous peoples, and finally sex/gender diversity and sexual orientation as key determinants of allostatic load. We then present innovative biochemical, neurological, and cognitive approaches for future empirical consideration, with conclusions centered on clinical and social policy implications. In espousing a developmental psychopathology approach that emphasizes causal processes, developmental mechanisms, and diverse conceptualizations of health, we highlight allostatic load studies that focus on resilient pathways and how these trajectories can be promoted to protect populations otherwise considered vulnerable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".