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Record W4236689232 · doi:10.32920/ryerson.14654604.v1

The Impact Of A Program For Crossover Youth In Ontario On Stakeholder Collaboration, Knowledge, Skills, and Attitudes

2021· preprint· en· W4236689232 on OpenAlexaffabout
Amy Beaudry

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsThematic analysisStakeholderPsychological interventionWelfareCrossoverEconomic JusticePositive Youth DevelopmentPsychologyPublic relationsPolitical scienceMedical educationDevelopmental psychologySociologyQualitative researchMedicineSocial scienceComputer science

Abstract

fetched live from OpenAlex

Crossover youth, those involved in both the child welfare and youth justice systems, are more likely to receive detention and harsher sentences than youth with no child welfare involvement. In Ontario, the Crossover Youth Project (COYP) was formed to ameliorate these systemic issues. To evaluate the success of a Toronto pilot site, a convergent parallel mixed methods study was completed. A total of 19 stakeholders, mostly from youth justice and child welfare, were interviewed at the closure of the pilot and 15 nine months later. Interviews were analyzed qualitatively using thematic analysis and interpreted alongside quantitative data from questionnaires. Themes indicate that stakeholders’ knowledge of crossover youth and skills in advocacy increased, as well as their ability to collaborate. While their learning was maintained at follow-up, their ability to collaborate was impaired by loss of the case coordinator who was essential to facilitating conferences. Results can inform future interventions.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0010.001
Open science0.0010.003
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 head0.097
GPT teacher head0.448
Teacher spread0.351 · 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 designObservational
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
Published2021
Admission routes2
Has abstractyes

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