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Cited by 521

The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.

Reentry and the Ties that Bind: An Examination of Social Ties, Employment, and Recidivism

Berg, Mark T., Huebner, Beth M.·2011·Justice Quarterly

Abstract

Scholars consistently find that reentering offenders who obtain steady work and maintain social ties to family are less likely to recidivate. Some theorize that familial ties may operate through employment to influence recidivism and that such ties may also serve a moderating role. The current study employs an integrated conceptual framework in order to test hypotheses about the link between familial ties, post‐release employment, and recidivism. The findings suggest that family ties have implications for both recidivism and job attainment. In fact, the results suggest that good quality social ties may be particularly important for men with histories of frequent unemployment. The implications of these findings are discussed with regard to theory and future research on prisoner reentry and recidivism.

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Crossref · 10.1080/07418825.2010.498383

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Metadata

Authors
Berg, M. T., & Huebner, B. M.
Venue
Justice Quarterly
Published
2011-04
Volume
28
Issue
2
Pages
382-410
ISSN
  • 0741-8825 (ISSN-L)
  • 1745-9109
OpenAlex
W2135613165
Cited by
521
References
67
FWCI
35.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Reentry and the Ties that Bind: An Examination of Social Ties, Employment, and Recidivism. https://app.cochat.ai/papers/10.1080/07418825.2010.498383
The paper
Berg, M. T., & Huebner, B. M. (2011). Reentry and the Ties that Bind: An Examination of Social Ties, Employment, and Recidivism. Justice Quarterly. https://doi.org/10.1080/07418825.2010.498383

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.