Patterns of reporting by health care and nonhealth care professionals to child protection services in Canada
Bibliographic record
Abstract
BACKGROUND: All Canadian jurisdictions require certain professionals to report suspected or observed child maltreatment. The present study examined the types of maltreatment, level of harm and child functioning issues (controlling for family socioeconomic status, age and sex of the child) reported by health care and nonhealth care professionals. METHODS: χ(2) analyses and logistic regression were conducted on a national child welfare sample from the 2003 Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-2003), and the differences in professional reporting were compared with its previous cycle (CIS-1998) using Bonferroni-corrected CIs. RESULTS: Analysis of the CIS-2003 data revealed that the majority of substantiated child maltreatment was reported to service agencies by nonhealth care professionals (57%), followed by other informants (33%) and health care professionals (10%). The number of professional reports increased 2.5 times between CIS-1998 and CIS-2003, while nonprofessional reports increased 1.7 times. Of the total investigations, professional reports represented 59% in CIS-1998 and 67% in CIS-2003 (P<0.001). Compared with nonhealth care professionals, health care professionals more often reported younger children, children who experienced neglect and emotional maltreatment, and those assessed as suffering harm and child functioning issues, but less often reported exposure to domestic violence. CONCLUSION: The results indicate that health care professionals play an important role in identifying children in need of protection, considering harm and other child functioning issues. The authors discuss the reasons why under-reporting is likely to remain an issue.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".