Community types and mental health: a multilevel study of local environmental stress and coping
Bibliographic record
Abstract
Research has found that neighborhood structural characteristics can influence residents' mental health. Few studies, however, have explored the proximal reasons behind such influences. This study investigates how different types of communities, in terms of environmental stressors (social and physical disorder and fear of crime) and social resources (informal ties and formal organizational participation), affect well-being, depression, and anxiety in adult residents. Data are from a survey of 412 residents nested in 50 street blocks. Block stressors and resources were cluster analyzed to identify six block types. After controlling for several individual- and block-level characteristics, results from multilevel models suggest that in communities facing relatively few stressors, higher levels of formal participation are associated with better mental health. Because high levels of formal participation were not found in communities with higher levels of stressors, the impact of participation in such contexts could not be examined. However, results suggest that in communities where stressors are more common, isolation from neighbors may have a protective effect on mental health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".