Barred: Labor Market Dynamics and Human Capital Development among People on Probation and Parole
Bibliographic record
Abstract
Obtaining employment is a major barrier to social reintegration for people on probation or parole. Research on the reentry process identifies several mechanisms that accentuate difficulties in locating work, including human capital development, structural changes in the labor market, and onerous probation and parole conditions. In this article, we review theories that explain low labor market participation rates among people reentering society, and we draw on multiple sources of data to identify the types of jobs that are available to people with low human capital. We find that nearly a quarter of people in America’s state and federal prisons had permanently removed themselves from the formal labor market before their most recent arrest; however, exclusionary hiring practices in the formal labor market often push those carrying the stigma of a criminal record into underground or informal labor markets, where wage rates are markedly higher than the federal minimum wage. Our findings demonstrate that severe and chronic employment struggles often predate and follow incarceration. We provide a detailed discussion of policy reform proposals that could help to remedy this harmful dynamic.
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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 | 0.004 |
| 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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".