Intimate Partner Violence and Structural Violence in the Lives of Incarcerated Women: A Mixed-Method Study in Rural New Mexico
Bibliographic record
Abstract
Intimate partner violence (IPV) is a common feature in the lives of incarcerated women returning to rural communities, enhancing their risk of mental ill-health, substance use, and recidivism. Women's experiences of IPV intersect with challenges across multiple social-ecological levels, including risky or criminalizing interpersonal relationships, geographic isolation, and persistent gender, racial, and economic inequities. We conducted quantitative surveys and qualitative interviews with 99 incarcerated women in New Mexico who were scheduled to return to micropolitan or non-core areas within 6 months. Quantitative and qualitative data were analyzed separately and then triangulated to identify convergences and divergences in data. The findings underscore how individual and interpersonal experiences of IPV, substance use, and psychological distress intersect with broad social inequities, such as poverty, lack of supportive resources, and reluctance to seek help due to experiences of discrimination. These results point to the need for a more proactive response to the mutually constitutive cycle of IPV, mental distress, incarceration, and structures of violence to improve reentry for women returning to rural communities. Policy and treatment must prioritize socioeconomic marginalization and expand community resources with attention to the needs of rural women of color.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".