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Record W4321494811 · doi:10.1093/bjsw/bcad079

Social Work Interventions with Children under 5 in Scotland: Over a Quarter Referred and One in Seventeen Investigated with Wide Variations between Local Authorities

2023· article· en· W4321494811 on OpenAlexaboutno aff
Andy Bilson, Marion Macleod

Bibliographic record

VenueThe British Journal of Social Work · 2023
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionQuarter (Canadian coin)LegislationSocial deprivationReferralIntervention (counseling)Work (physics)Social workDemographyPsychologyMedicinePolitical scienceFamily medicineLawGeographySociologyNursingEngineering

Abstract

fetched live from OpenAlex

Abstract This article uses information from freedom of information requests to find the rate of children who were subject to social work interventions in Scotland before the age of 5. It finds that more than one in every four children were referred to social work and provides the rates for other types of interventions including children investigated for child protection, becoming looked after and being adopted. Despite differences in legislation and the judicial system, the study shows many similarities in rates of intervention in Scotland to similar longitudinal studies in England. The study found wide variations between local authorities in rates of these different interventions, which for most interventions was moderately correlated with deprivation and, in the case of the high disparities in rates of referral and child protection investigation, had little correlation with deprivation. The likelihood of children’s involvement with social work varied markedly depending on where they lived.

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 score0.051
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.306
Teacher spread0.264 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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