SCOPING REVIEW OF PROFESSIONAL JUDGMENT AND REPORTING CRITERIA IN PEDIATRIC SUPERVISORY NEGLECT
Bibliographic record
Abstract
Background: Supervisory neglect is among the most frequently identified forms of child maltreatment, yet definitions and reporting practices vary widely. Clinicians and child-protection professionals often rely on professional judgment without standardized criteria, resulting in inconsistencies in decisions to report or intervene. Objectives: (1) Describe how supervisory neglect is defined and operationalized in the literature. (2) Map criteria/indicators and professional decision-making processes guiding reporting or intervention. (3) Identify contextual factors (clinical, legal, cultural) and tools that influence decisions, and highlight gaps to inform guidance. Methods: Scoping review following JBI methodology and reported per PRISMA-ScR. Databases: PubMed, Cochrane Library, Web of Science, EMBASE, Scopus, and Google Scholar (through July 2025). PCC framework: Population children/adolescents <18y; Concept professional judgment, reporting criteria/indicators for supervisory neglect; Context healthcare/child-protection settings. English-language original studies only (reviews of any kind, case reports/series excluded). Two reviewers will conduct duplicate screening and data charting (study characteristics; definitions; criteria/indicators; decision factors; tools; outcomes). Synthesis will use descriptive statistics and thematic analysis with concept mapping. Preliminary findings: Included studies (predominantly US/Canada; retrospective, cross-sectional, and administrative data analyses) show: • Variable definitions of supervisory neglect and heterogeneous operationalization; • Decision factors commonly include child age/development, caregiver capacity, supervision continuity/proximity, environmental hazards, and prior CPS involvement; • Tools/approaches referenced include RASS and LOSCS, but uptake is inconsistent; • Reporting practices often hinge on clinician/CPS judgment with limited standardized criteria; Several studies call for clearer guidance and supportive, context-sensitive responses for lower-risk cases. Conclusion: The evidence demonstrates substantial variability in definitions and reporting criteria for supervisory neglect, as well as a heavy reliance on professional judgment. A consolidated map of indicators and contextual drivers can inform the development of clearer guidance, training, and decision-support tools to promote consistent, child-centered reporting practices.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.247 | 0.601 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.042 | 0.045 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".