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Record W4214756718 · doi:10.7179/psri_2022.40.01

Leaving care in Quebec: The EDJeP Longitudinal Study

2022· article· en· W4214756718 on OpenAlexaffabout
Alexandre Blanchet, Martín Goyette

Bibliographic record

VenuePedagogia Social Revista Interuniversitaria · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsGraduation (instrument)Vulnerability (computing)Longitudinal studyLongitudinal dataPopulationDemographic economicsPolitical sciencePsychologySociologyDemographyMedicineEconomicsComputer securityEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract This article reports results from the first longitudinal and representative study of a cohort of youth leaving care in Quebec (EDJeP study). Focusing on education and residential stability, we show that youths from youth protection services accumulate important vulnerabilities that make their transition out of youth protection services very challenging. In particular, compared to their peers in the general population, youth leaving care have significant educational delays that complicate their integration into the labor market. Our data suggest that a system that better encourages school perseverance and success would limit these academic delays and promote graduation. We also find that nearly half of the youths from the protection system experienced residential instability in the months following their release from placement and that 20% of them experienced at least one episode of homelessness. These last elements clearly show the extent of the vulnerability of youth leaving the protection system. We suggest some areas of reflection to improve this situation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.088
GPT teacher head0.429
Teacher spread0.341 · 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 teacher head, not a consensus.

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

Citations13
Published2022
Admission routes2
Has abstractyes

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