Low-Income Black Mothers Parenting Adolescents in the Mass Incarceration Era: The Long Reach of Criminalization
Bibliographic record
Abstract
Punitive and disciplinary forms of governance disproportionately target low-income Black Americans for surveillance and punishment, and research finds far-reaching consequences of such criminalization. Drawing on in-depth interviews with 46 low-income Black mothers of adolescents in urban neighborhoods, this article advances understanding of the long reach of criminalization by examining the intersection of two related areas of inquiry: the criminalization of Black youth and the institutional scrutiny and punitive treatment of Black mothers. Findings demonstrate that poor Black mothers calibrate their parenting strategies not only to fears that their children will be criminalized by mainstream institutions and the police, but also to concerns that they themselves will be criminalized as bad mothers who could lose their parenting rights. We develop the concept of “family criminalization” to explain the intertwining of Black mothers’ and children’s vulnerability to institutional surveillance and punishment. We argue that to fully grasp the causes and consequences of mass incarceration and its disproportionate impact on Black youth and adults, sociologists must be attuned to family dynamics and linkages as important to how criminalization unfolds in the lives of Black Americans.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".