Socioeconomic status and the health of youth: A multilevel, multidomain approach to conceptualizing pathways.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous research has clearly established associations between low socioeconomic status (SES) and poor youth physical health outcomes. This article provides an overview of the main pathways through which low SES environments come to influence youth health. We focus on 2 prevalent chronic health problems in youth today, asthma and obesity. We review and propose a model that encompasses (a) multiple levels of influence, including the neighborhood, family and person level; (b) both social and physical domains in the environment; and finally (c) dynamic relationships between these factors. A synthesis of existing research and our proposed model draw attention to the notion of adverse physical and social exposures in youth's neighborhood environments altering family characteristics and youth psychosocial and behavioral profiles, thereby increasing youth's risk for health problems. We also note the importance of acknowledging reciprocal influences across levels and domains (e.g., between family and child) that create self-perpetuating patterns of influence that further accentuate the impact of these factors on youth health. Finally, we document that factors across levels can interact (e.g., environmental pollution levels with child stress) to create unique, synergistic effects on youth health. Our model stresses the importance of evaluating influences on youth's physical health not in isolation but in the context of the broader social and physical environments in which youth live. Understanding the complex relationships between the factors that link low SES to youth's long-term health trajectories is necessary for the creation and implementation of successful interventions and policies to ultimately reduce health disparities.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it