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Enregistrement W150102863

Changing through Clusters: Vermont's Policy Clusters

2003· article· en· W150102863 sur OpenAlexaboutno aff
Will Lindner

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueEvaluation and Performance Assessment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPopulationCommissionLegislatureState (computer science)CriminologyPsychiatryLawPolitical sciencePsychologySociologyDemography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Let's acknowledge at the outset that Gloria is fictional. But there are real-life Glorias even in Vermont, a state known for its picturesque villages, ski slopes, and green pastures. They are abuse victims whose husbands or boyfriends are serving time in jail. In this scenario, says Dr. Thomas Powell, director of clinical services with the Vermont Department of Corrections, let's place Gloria's husband at the Northern State Correctional Facility, one of Vermont's highest-security prisons, within hailing distance of the Canadian border in Vermont's rugged Northeast Kingdom. Traveling to see him on visitors' day is an arduous proposition. So what do we do when she gets there, with her children in tow? asks Powell. We greet her with security apparatus and security officials who are large males, and who make her go through metal detectors and contraband-detection procedures. If this is a woman with a history of traumatic abuse, she feels threatened, intimidated, and controlled from the moment she enters our facility. The same holds for her children, who may have been abused, or have witnessed abuse, themselves. But the Glorias and their children aren't the only ones affected by trauma in Vermont. Trauma appears across the spectrum of the human services client population. A legislative Commission on Psychological Trauma reported in 2000 that perhaps 70 percent of people in Vermont's outpatient mental health treatment programs, and up to 72 percent in inpatient facilities, had traumatic abuse histories. Seventy percent of the participants in substance abuse treatment programs experienced physical or sexual abuse. The trend holds even for PATH (the Department of Prevention, Assistance, Transition and Health Access, formerly Social Welfare). one primary reason they end up in (need of) our agency's says Susan Besio, commissioner of Vermont's Developmental and Mental Health Services. To address the high incidence of trauma, in April 2001, Jane Kitchel, Vermont's then secretary of human services, designated trauma as the Agency of Human Services' (AHS) seventh, and most recent, cluster. Kitchel appointed Besio cochair of a cross-departmental working group. In September 2002 the cluster hosted a three-day, agency-wide training with nationally recognized trauma experts Maxine Harris and Roger D. Fallot. The objective was to make the disparate departments operating under AHS' wide umbrella trauma-informed, modifying procedures to lessen the chances of alienating people with trauma histories, and to become more knowledgeable about referrals for treatment. It's an important step because long-term trauma, with its pernicious emotional consequences, can subvert the best efforts of human services providers. Once we start screening effectively for trauma throughout the agency, it might be the cross-cutting issue that allows us an understanding of families' systems and provides new perspectives on how to treat them, says Powell. Agency administrators have similar ambitions for all seven policy clusters (though the cluster concept itself is fluid, so more clusters could be created while existing clusters tail off as their work is completed or morph into some variation on their original theme.) Besides Trauma, there are clusters for Integrated Service Delivery, the High-Risk Pool, Coordinating the Caregiver Process, Connecting Better with Communities, Crisis and Family Stabilization, and a Coordinated Approach to Home Visits. Adaptable and Fluid The goal of transforming not just a department or two, but the entire agency; into a trauma-informed social services organization suggests the potential dimensions of Vermont's policy cluster concept. If AHS tried to address trauma in the pre-policy cluster mode, one might almost imagine the creation of a Department of Trauma, replete with bureaucracy, budget, and reporting requirements. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,022
score de la tête « metaresearch » (Gemma)0,040
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,548
Score d'incertitude au seuil0,910

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0220,040
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0480,014
Communication savante0,0270,023
Science ouverte0,0090,038
Intégrité de la recherche0,0330,023
Charge utile insuffisante (le modèle a refusé de juger)0,0450,003

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.

Tête enseignante Opus0,206
Tête enseignante GPT0,494
Écart entre enseignants0,288 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2003
Routes d'admission1
Résumé présentoui

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