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Record W2954256438 · doi:10.1080/0312407x.2019.1624795

Pathways of Children Reported for Domestic and Family Violence to Australian Child Protection

2019· article· en· W2954256438 on OpenAlexaff
Aron Shlonsky, Jennifer Ma, Colleen Jeffreys, Arno Parolini, Ilan Katz

Bibliographic record

VenueAustralian Social Work · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Toronto
FundersAustralian GovernmentAustralia's National Research Organisation for Women's SafetyDepartment for Child Protection and Family SupportU.S. Department of Health and Human Services
KeywordsPsychological interventionDomestic violenceChild protectionChild abusePoison controlPsychologySuicide preventionEnvironmental healthMedicineDevelopmental psychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

Child protection systems often contend with domestic and family violence (DFV) as a maltreatment concern, yet few large-scale studies have explored how child protection services (CPS) systems respond to DFV compared with other concerns. Secondary longitudinal analysis of administrative data from three Australian State CPS systems finds that the number of DFV reports increased faster than notifications for other concerns, and children reported for DFV also tended to be reported for emotional and physical abuse. Children reported for DFV were slightly less likely to transition from report to formal child maltreatment investigation. Overall, system responses to maltreatment concerns appear to be similar across concern types despite substantial differences in their aetiologies and options for effective 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.744

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 studies0.0010.000
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 head0.043
GPT teacher head0.325
Teacher spread0.282 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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