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Record W2518029106 · doi:10.18584/iipj.2016.7.3.2

Indigenous Young People Transitioning from Out-of-Home Care (OOHC) in Victoria, Australia: The Perspectives of Workers in Indigenous-Specific and Non-Indigenous Non-Government Services

2016· article· en· W2518029106 on OpenAlexvenueno aff
Philip Mendes, Bernadette J. Saunders, Susan Baidawi

Bibliographic record

VenueInternational Indigenous Policy Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousExploratory researchWelfareGovernment (linguistics)Focus groupSociologyMedicineNursingPolitical scienceEconomic growthSocial scienceLawAnthropology

Abstract

fetched live from OpenAlex

Indigenous children and young people are overrepresented in the Australian out-of-home care (OOHC) system. To date, specific research has not been undertaken on workers' perspectives regarding the Indigenous-specific and non-Indigenous supports and services available to Indigenous young people exiting the system. This exploratory research involved focus group consultations with workers from seven child and family welfare agencies to examine the current support services available to Indigenous young people who are in or will be leaving out-of-home care in the State of Victoria. Findings suggest that Aboriginal Community Controlled Organisations (ACCOs) play a positive role in working with non-Indigenous agencies to assist Indigenous care leavers. Participants identified some key strategies to improve outcomes, such as facilitating stronger relationships between Indigenous and non-Indigenous services, and improving the resourcing of ACCOs.

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)0.003
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 score0.383
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.003
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 head0.011
GPT teacher head0.289
Teacher spread0.278 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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