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Record W3011039205

Child Protective Service Referrals Involving Exposure to Domestic Violence: Prevalence, Associated Maltreatment Types, and Likelihood of Formal Case Openings

2019· book-chapter· en· W3011039205 on OpenAlexaboutno aff
Bryan G. Victor, Colleen Henry, Terri Ticknor Gilbert, Joseph P. Ryan, Brian E. Perron

Bibliographic record

VenueAuthor eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsChild protectionChild abuseNeglectWelfarePoison controlHarmMedicineDomestic violencePsychiatryQuarter (Canadian coin)PsychologyReferralOccupational safety and healthSuicide preventionInjury preventionClinical psychologyEnvironmental healthFamily medicineNursingSocial psychologyGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Childhood exposure to domestic violence (CEDV) is widely understood as potentially harmful to children. Accordingly, many child welfare systems in the United States construe CEDV as maltreatment when the exposure results in or threatened to the child. The purpose of the current study was to investigate substantiated child welfare referrals directly related to CEDV to better understand the prevalence and patterns of CEDV-related maltreatment and how child welfare workers respond under the or threatened harm standard. Data were drawn from 23,704 substantiated referrals between 2009 and 2013 in a large Midwestern child welfare system. Approximately 20% of substantiated referrals were CEDV related. A plurality of CEDV-related referrals included both a male caregiver and female caregiver who were co-substantiated for maltreatment. The most common maltreatment types substantiated for these referrals were neglect based rather than abuse based, and just under a quarter (23%) of CEDV-related referrals were formally opened for services. Referrals involving co-occurring substance abuse were most likely to be opened for services based on predicted probabilities derived from multilevel modeling. Implications for policy and practice are considered.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.306
Teacher spread0.276 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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