Legal Systems Involvement and Mental Health: The Challenges for Young People Engaged in the Family Law and Criminal Justice Systems
Notice bibliographique
Résumé
Young people who are engaged with the child welfare and youth criminal justice systems are being severely harmed by their involvement with these and other legal systems. This crisis is particularly pronounced for young people who experience mental health issues. A significant majority of the young people engaged with the child welfare and youth criminal justice systems experience mental health issues, yet despite their engagement with state systems mandated to protect them and promote their well-being, few receive the supports and services they need. In this dissertation I explore the mutually constitutive role of legal rules in the child welfare, youth criminal justice, civil mental health, and education systems; particularly how these rules, through their interpretation and implementation in practice, create, contribute to, and/or compound the barriers to service use experienced by young people with mental health issues. Using legal doctrinal analysis, original empirical data gathered through qualitative semi-structured interviews with legal and mental health professionals, scholarly literature, and secondary sources which relay the lived experiences of these young people, I illuminate how, in practice, the complex, intersecting challenges they experience are more often compounded, exacerbated, and multiplied rather than ameliorated, by their engagement with the state systems mandated to protect them and promote their well-being. I discuss how this systemic failure results in severe short- and long-term difficulties and outcomes for the young people involved; and how it comes with significant costs and consequences for these young people, their families, and society more generally. I then examine and analyze the reforms needed to overcome the barriers to service use experienced by these young people and to facilitate their access to and engagement with needed supports and services. I recommend specific changes to legislation, policies and practices, funding, and service delivery and discuss how these changes could curb the harms currently experienced by young people with legal systems involvement. Finally, I consider the significant investments required to develop and implement these changes as well as the human and financial costs of continuing the state’s failure to meet the needs of this underserved and often overlooked population of young people.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».