The Effects of Social Capital and Neighborhood Characteristics on Intimate Partner Violence: A Consideration of Social Resources and Risks
Why this work is in the frame
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Bibliographic record
Abstract
Intimate partner violence (IPV) is a growing public health problem, and gaps exist in knowledge with respect to appropriate prevention and treatment strategies. A growing body of research evidence suggests that beyond individual factors (e.g., socio-economic status, psychological processes, substance abuse problems), neighborhood characteristics, such as neighborhood economic disadvantage, high crime rates, high unemployment and social disorder, are associated with increased risk for IPV. However, existing research in this area has focused primarily on risk factors inherent in neighborhoods, and has failed to adequately examine resources within social networks and neighborhoods that may buffer or prevent the occurrence of IPV. This study examines the effects of neighborhood characteristics, such as economic disadvantage and disorder, and individual and neighborhood resources, such as social capital, on IPV among a representative sample of 2412 residents of Toronto, Ontario, Canada. Using a population based sample of 2412 randomly selected Toronto adults with comprehensive neighborhood level data on a broad set of characteristics, we conducted multi-level modeling to examine the effects of individual- and neighborhood-level effects on IPV outcomes. We also examined protective factors through a comprehensive operationalization of the concept of social capital, involving neighborhood collective efficacy, community group participation, social network structure and social support. Findings show that residents who were involved in one or more community groups in the last 12 months and had high perceived neighborhood problems were more likely to have experienced physical IPV. Residents who had high perceived social support and low perceived neighborhood problems were less likely to experience non-physical IPV. These relationships did not differ by neighborhood income or gender. Findings suggest interesting contextual effects of social capital on IPV. Consistent with previous research, higher levels of perceived neighborhood problems can reflect disadvantaged environments that are more challenged in promoting health and regulating disorder, and can create stressors in which IPV is more likely to occur. Such analyses will be helpful to further understanding of the complex, multi-level pathways related to IPV and to inform the development of effective programs and policies with which to address and prevent this serious public health issue.
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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 | 0.002 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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