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Record W2134455291 · doi:10.5093/in2013a20

Overview of out of home care in the USA and Canada

2013· article· en· W2134455291 on OpenAlexaffabout
Mark E. Courtney, Robert J. Flynn, Joël Beaupré

Bibliographic record

VenuePsychosocial Intervention · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsCentre for Community Based ResearchUniversity of Ottawa
Fundersnot available
KeywordsFoster careNeglectKinship careChild protectionWelfareWelfare reformPopulationEconomic growthNursingPsychologyMedicinePolitical scienceEnvironmental healthLaw

Abstract

fetched live from OpenAlex

The paper begins by suggesting that child welfare systems in North America and selected European and Scandinavian countries have converged functionally over the last two decades from a focus on child protection or family service to a more comprehensive child development orientation. The overview of the US in-care system covers the topics of mandatory reporting of child maltreatment, permanency planning, foster care funding, and decentralized service provision. It also portrays the current US foster care population and describes recent research on efforts to reduce the number of children in care, differential response, practice and policy reform, subsidized guardianship, Casey Family Programs, transitions to adulthood, and racial disparities in placements in out-of-home care. The overview of the Canadian in-care system notes the responsibility of the 10 provinces and three northern territories for child welfare and the concomitant lack of national data on child protection or out-of-home care. Estimates of the number of children in care are presented, and a review of research describes the following topics: rates and types of maltreatment, over-representation of Aboriginal children in care, prevention of the recurrence of neglect and physical abuse, effects of placement into care, differential response, resilience, educational achievement, and transitions from care. The paper concludes by noting certain differences and similarities between the US and Canadian in-care systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

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

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 head0.034
GPT teacher head0.346
Teacher spread0.312 · 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.

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

Citations29
Published2013
Admission routes2
Has abstractyes

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