Prison, Re-entry, Reintegration and the ‘Star Gate’: The Experience of Prison Release
Notice bibliographique
Résumé
Prison, Re-entry, Reintegration and the 'Star Gate':The Experience of Prison Release Jeffrey Bliss M any people are asking 'why do ex-offenders continue to re-offend or violate the conditions of their release supervisions usually within a 90 day period after release?'But more importantly, many more are saying that this is because individuals 'choose to continue to live the lifestyle of lawlessness, and opt to act and behave in ways that violate the conditions of their release supervision'.However, is it not possible that this type of thinking could not be further from the truth, and that in fact, for many of the criminalized like myself, there could be different reasons altogether?Our nation's recidivism rate has dropped a lot in recent years but it is still holding at approximately 34 percent (Glaze and Bonzcar, 2010).In New York, where I am serving my sentence, of the 24,605 ex-prisoners released between 2011 to 2013, a total of 10,217 (42 percent) of parolees were taken back into custody (Department of Corrections and Community Supervision, 2014).Interestingly, only 9 percent of these men and women were convicted of a new felony, while 32 percent were returned to prison for violating terms of their parole (ibid, 2014).Recidivism rates vary by State, so to give the reader a sense of the magnitude of the problem, consider the following rates of recidivism from jurisdictions who, according to the Council of State Governments Justice Center (2014) have actually lowered their return rates: Colorado (49 percent); Connecticut (40 percent); Georgia (26 percent); North Carolina (28.9 percent); Pennsylvania (40.8 percent); Rhode Island (48.9 percent); South Carolina (27.5 percent); and Wisconsin (51.1 percent).Some States have more disturbing statistics.In Washington State, the recidivism rate in 2007 was 63.3 percent (Sentencing Guidelines Commission, 2008).There are many factors that contribute to the current rate of re-incarceration.Academics and researchers have identifi ed social economic poverty, alcohol and drug addiction, lack of educational/vocational training, mental health disorders, family dysfunction, childhood trauma and/or abuse, and lack of adequate transitional service housing programs and resources, as some of the contributing factors to recidivism.These factors contribute not only to the small number of parolees who commit new crimes, but also to the thousands who return for technical violations of their parole.For example, of the 24,520 men and women paroled in New York in 2008, 29 percent had their parole revoked and were returned to prison.Twenty-three percent of the time these
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,023 | 0,027 |
| Communication savante | 0,013 | 0,009 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,006 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».