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Record W2802179115

The Lives of Young Adults Who Have Graduated from Residential Children's Mental Health Programs (SUMMARY REPORT)

2015· article· en· W2802179115 on OpenAlexaboutno aff
Gary Cameron, Karen Frensch

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychologyGerontologyMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

What happens to children and youth after they leave residential mental health treatment? How do these youth navigate normative developmental transitions like finishing school, getting a job, and finding a place to live? What types of assistance might facilitate these transitions? Despite the critical importance of these questions for youth themselves, for the educational, justice, and mental health systems, and for the development of more appropriate transitions to community programming, surprisingly little is known about what happens to these children and youth over time.\nThis report presents the results of a research process in which 59 young adults who had received residential mental health treatment in the past were sorted into descriptive profiles based on the information they shared about their lives and personal functioning with researchers. Five different groups of young adults emerged from this process and represent the clearest categorizations for understanding this particular sample of young adults from across Southern Ontario who received residential treatment.\nSorting young adults into distinct groups based on their functioning within key life domains (like education, employment, social connections, personal functioning) is useful to understanding the long term community adaptation of youth previously involved in children’s residential mental health treatment. Through a process of describing the defining characteristics of particular groups of young adults we can begin to think about adapting services and supports to meet the unique needs of distinct groups of youth as they transition into young adulthood.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.721
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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