Challenge for Rehabilitation Counselors: Serving Individuals with Disabilities Involved in Gang Activity
Notice bibliographique
Résumé
When street gang was first thought to be a major issue of concern within United States, issue was considered relevant only to major, urban environments (Hauck & Peterke, 2010; U.S. Attorney General, 2008). More recently, however, attention has been directed toward spread of gang to suburban and rural regions (Hauck & Peterke, 2010; Osgood & Chambers, 2000; U.S. Attorney General, 2008). As reported by National Gang Center (2009), distribution of gangs nationwide was as follows: 44.4% in larger cities; 29.1% in smaller cities; 21.4% in suburban counties; and 5.4% in rural counties. Further exploration into ethnicity of individuals in gangs shows that in 2008, 50.2% were Hispanic or Latino; 31.8% were Black or African American; 10.5% were White; and 7.6% identified as (National Gang Center). This serves as a reminder that no areas or ethnicities are immune to impact of gang violence. In fact, research illustrates increasing gang problem in United States (Burch & Chemers, 1997; National Gang Intelligence Center, 2011; Okamoto, 2001). For example, in a survey conducted by Office of Juvenile Justice and Delinquency Prevention, 49% of law enforcement agencies responded that gang activity in their jurisdiction was getting worse (Burch & Chemers, 1997). A similar perception was also noted more recently in 2011 Gang Threat Assessment. The assessment reported a sizable increase in gang membership and collaboration with other gangs or criminal enterprises to conduct larger scale criminal activities (National Gang Intelligence Center, 2011). Specifically, Federal Bureau of Investigation (2011) estimates that there are approximately 33,000 gangs, encompassing 1.4 million active members in United States. Furthermore, these gangs are responsible for approximately 48% of violent crimes and 90% of many other crimes, not considered violent (Federal Bureau of Investigation, 2011). Important to remember is that not all violent crime assaults were sustained by random victims of gang violence. Interestingly, Peterson, Taylor, and Esbensen (2004) note that in gangs can come from a variety of sources including other members of same gang in form of beat ins and violations. This is known as intragang conflict (Hunt & Laidler, 2001). For example, a member of a gang who violates rules of their own gang may experience violent retaliation from other members within same gang (Peterson, Taylor, & Esbensen). In other instances, gang rivalry between competing gangs may also result in negative consequences and injuries to members (Egly & Howell, 2011). Intergang conflict, also known as gang-on-gang has been shown to result from defense of gang's reputation, trespassing, retaliation, and gangs defending their identity (Egly & Howell). These violent acts can result in disabling conditions (Cook & Ludwid, 2000). However, literature fails to cover rehabilitation outcomes of gang involved populations in aftermath of injury. Intergang conflict is a form of interpersonal violence. Historically, World Health Organization (2002), provided a widely used comprehensive definition of interpersonal which encompasses inflicted, generally outside home, by an unrelated individual whom victim may or may not know for the intentional use of physical force or power, threatened or actual ... that either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment or deprivation (p. 4). The Canadian Red Cross (2012) elaborates on this definition by stating that encompasses child abuse, family violence, gender-based violence, bullying and harassment, elder abuse, and community such as gang violence (pg. 8). Interpersonal involving gangs has been known to lead to victim's death (National Spinal Cord Injury Statistics Center, 2003; Center for Disease Control and Prevention, 2012). …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».