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Caregivers, Young People with Complex Needs, and Multiple Service Providers: A Study of Triangulated Relationships

2012· article· en· W1965694992 on OpenAlexaff
Michael Ungar, Linda Liebenberg, Nicole M. Landry, Janice Ikeda

Bibliographic record

VenueFamily Process · 2012
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsService providerEmpowermentPsychosocialMental healthPsychologyPsychological interventionQualitative researchService (business)Service delivery frameworkNursingMedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

Five patterns of service provider-caregiver-adolescent interaction are discussed using qualitative interviews and file review data from 44 youth with complex needs who were clients of more than one psychosocial service (child welfare, mental health, addictions, juvenile justice, and special education). Findings show that young people and their families become triangulated with service providers, either engaging with, or resisting, interventions. For young people with complex needs involved with multiple service providers, both positive and negative patterns of interaction contribute to the complexity of caregiver-child interactions. According to young people themselves, the most functional of these patterns, empowerment, was experienced as protective when it helped them to meet their personal needs and enhance communication. In contrast, four problematic patterns produced triangulations described as conflictual or unsupportive. The implications of these patterns for family therapy are discussed with an emphasis on the therapist as both clinician and advocate for better services from multiple providers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.052
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0110.006
Scholarly communication0.0050.005
Open science0.0020.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.108
GPT teacher head0.343
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2012
Admission routes1
Has abstractyes

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