Network Analysis of Health Service Utilization and Community Involvement in Youth
Bibliographic record
Abstract
Health service access is an important correlate of youth well-being. However, evidence suggests that many adolescents are under-utilizing (or not accessing) services that they may need (Power et al., 2005), especially those in underrepresented, minoritized, and newcomer communities. It is important to better understand the patterns and predictors of health service use—particularly from a community systems-based perspective—to identify ways to support diverse youth in their access to, and appropriate utilization of, health services. One particularly important consideration involves understanding how engagement with community and social services is linked to the use of formalized health services, given that these interactions may relate to well-being, and could either motivate or hinder youth's use of health services. This study therefore adopted psychometric network analysis to examine the intersection between various aspects of community involvement, engagement with social services, and use of health services in a sample of Canadian youth aged 9–18.
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How this classification was reachedexpand
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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.035 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".