EFFECT OF CHILDHOOD ADVERSITY ON PSYCHOLOGICAL AND BIOLOGICAL MARKERS OF STRESS IN MIDDLE AND LATER LIFE
Bibliographic record
Abstract
A growing number of studies have identified significant linkages between adverse childhood experiences and health outcomes in later life. Guided by a broad theoretical framework of the life course perspective, these studies have postulated that childhood adversities are the seedbed for vulnerabilities that may accumulate across the life course. This symposium includes four presentations that build on such existing knowledge, and its primary aim is to investigate the effects of early childhood adversities on psychological and biological markers of stress in middle and later adulthood. Using nationally representative samples, the four presentations focus on examining various aspects of psychological and biological markers of stress in later adulthood, including biomarkers of inflammation, alpha amylase, grip strength, and daily emotional reactivity. Particularly, biomarker data such as inflammation have key strengths: providing objective data about health and functioning in contrast to measurements based on self-reports and indicating potential risk of future disease. This symposium also addresses a wide range of childhood adversities, including neglect and abuse, low socioeconomic status, and early parental loss and provides insights around how different types and characteristics of adverse childhood experiences may unfold differently across the life course. Additionally, this symposium consists of a group of multidisciplinary presenters with diverse scholarly and cultural backgrounds. For example, one of the presentations discusses the experience of older Korean adults and offers a chance to understand cross-cultural differences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".