The Socio-Legal Impacts of Maternal Incarceration on Children: Emotional, Social, and Physical Considerations in Sentencing Decisions
Bibliographic record
Abstract
This paper explores the socio-legal impacts of maternal incarceration on children in the United States. The steep rise in incarceration rates, particularly among women, has highlighted challenges faced by children with incarcerated mothers. These challenges include emotional distress, social stigmatization, behavioral issues, psychological maladjustment, and more. Despite the existence of programs aimed at supporting these children, such initiatives often lack a cohesive national policy, resulting in inequality in access and implementation. This study advocates for a comprehensive analysis of the legal context, including trends, sentencing policies, and the rights of the child. It emphasizes the need for a more consistent application of the "best interests of the child" standard in sentencing decisions. At the same time, it analyzes international and national practices and programs situated in addressing said challenges. By evaluating current approaches and proposing reforms, this study aims to provide insights for improving support systems for children affected by maternal incarceration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".