The Spatial Concentration, Stability, and Specialization of Mental Health Calls for Service: Evidence in Support of Proactive, Place-Based Interventions
Notice bibliographique
Résumé
For many decades the police have been the de facto responders to persons with perceived mental illness (PwPMI). However, having the police in this role has come with negative repercussions for PwPMI, such as disproportionately experiencing criminalization and use of force. In recognizing these issues, the police—and more recently, the community—have developed responses that either seek to improve interactions between the police and PwPMI or remove the police from this role altogether. However, in either case, these efforts are reactive in nature, responding to crises that arguably could have been prevented had a timelier intervention taken place. Further, evidence on certain police responses to PwPMI, such as Crisis Intervention Teams (CIT) and co-response teams, suggests that they endure deployment-related challenges, thus limiting their reach to PwPMI.\nDrawing from the Criminology of Place and existing place-based policing strategies, the present dissertation argues that efforts focused on responding to PwPMI should instead be proactively deployed, targeting areas where interactions between police and PwPMI concentrate spatially. Doing so would not only result in efficient deployment of scarce resources but would permit police- and community-based efforts to have a greater reach to PwPMI and thus prevent future interactions with police. To-date, however, there have been few empirical and theoretical investigations into the spatial patterns of PwPMI calls for service that could inform such proactive, place-based efforts. Specifically, we do not currently understand: (1) the degree to which PwPMI calls for service concentrate within certain geographical contexts (such as a small city); (2) whether the degree of PwPMI call concentration and the location of these calls remain stable over time; and (3) what theoretical frameworks explain why PwPMI calls for service occur where they do. Drawing on seven years (2014-2020) of calls for service data from the Barrie Police Service and data from the 2016 Canadian Census, the present dissertation employs various methods of spatial analysis to fills these specific knowledge gaps.\nAlthough the theoretical investigation confirmed the findings of previous work that found no association between social disorganization theory and the spatial patterns of PwPMI calls for service, the present dissertation revealed: (1) PwPMI calls for service are highly concentrated within the context of a small city, even more so than what has previously been uncovered in larger jurisdictions; (2) the degree of PwPMI call concentration is stable over time, falling within a narrow proportional bandwidth of spatial units; and (3) PwPMI calls for service, and their concentrations, occur in the same places over time—even during the COVID-19 pandemic—and are thus spatially stable. As such, though more scholarship is needed on theories that might help explain why PwPMI calls occur where they do, the findings of the present dissertation strongly support the proactive, place-based deployment of resources to PwPMI.
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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 | 0,011 | 0,085 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,006 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,005 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».