The Risk of Family Violence After Incarceration: An Integrative Review.
Bibliographic record
Abstract
Despite the importance of understanding the prevalence, causes, and consequences of conflict and violence within families, the specific risk of violence following a family member's release from incarceration has been hard to ascertain. Research indicates that a significant percentage of persons released from incarceration will experience involvement in family violence in their life, yet it remains unclear whether this heightened risk exists due to larger family or structural contexts or whether incarceration itself leads to heightened risk of family violence after release. Using an integrative review methodology that combines results from both qualitative and quantitative studies, we review existing studies of family violence after incarceration to explore (1) the prevalence, (2) variation in measurement, (3) risk factors, and (4) protective factors for family violence after a family member's incarceration. Through a search of three separate databases for peer-reviewed and gray literature, we analyzed 26 studies that estimated any form of physical family violence after any family member had been incarcerated. Where reported, intimate partner violence occurs in almost a quarter of cases, although only four studies examine the prevalence of violence perpetrated against children by parents. Family violence history, weakened family support during incarceration, and substance use after release all emerged as persistent risk factors. Directions and opportunities for future research are discussed.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".