MétaCan
Menu
Back to cohort
Record W6996688645

Stories of Children, Youth, and Familiesâ Adaptation to Community Living in the First Year after Involvement with Childrenâs Residential Mental Health Programs

2019· article· en· W6996688645 on OpenAlexaffabout

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNucleofectionTSG101HyporeflexiaGestational periodCircumstantial evidenceProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Twenty-two youth between the ages of 14 and 18 years old who were involved with residential programs from participating children’s mental health organizations in Southern Ontario, Canada during 2015 to 2017 participated in a study of adaptation to community living in the first year following program exit. Youth, parents, child welfare workers, and mental health workers took part in qualitative interviews up to three times during the study period. Interview comments were used to construct a narrative or “story” of the year following program exit that integrated multiple informants’ perspectives of how each youth was functioning within that timeframe. Stories for youth who returned home to live with their families (12 youth) were examined together to explore any common experiences or processes that described the post-discharge daily living of this group of youth and their families. Similarly, the stories of youth who resided in the care of the Children’s Aid Society following program exit (10 youth) were explored for commonalities that could offer insight into their community adaptation experiences. Study findings underscore the need for proactive and flexible aftercare programming to improve community living outcomes for youth leaving residential mental health programs.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.003
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 head0.018
GPT teacher head0.232
Teacher spread0.215 · 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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueScholars Commons (Wilfrid Laurier University)Same topicChild Welfare and AdoptionFrench-language works237,207