Placement Decision-making in Child Welfare: A Provincial Profile of Associated Factors
Bibliographic record
Abstract
INTRODUCTIONOut-of-homeplacement is described as being the most costly and intrusive response to achild protection investigation [2]. Out-of-home care is the largest singleexpenditure for many child welfare organizations in Canada [1]. There islimited understanding on the benefits of this costly intervention, and forwhich children placement is best suited for. Children in care are reported toexperience greater behavioural problems [5], hinder youths’ willingness toengage in relationships [6], and decrease cognitive skills [5]. Alberta has seen an increase in child welfareplacements from 2003 when 7% of all child investigations noted a formal childwelfare placement compared with 9% in 2008 [4]. The Alberta Incidence Study of Reported Child Abuse and Neglect 2008(AIS-2008) is the second cycle of a provincial study that examines reportedincidents of child abuse and neglect [4]. Based on a secondary data analysis of the AIS-2008 dataset, this poster will providea provincial profile of factors associated with child welfare placement cases,and no child welfare placement cases in Alberta in 2008.METHODSThisposter is based on 27,417 child maltreatment investigations from the AIS-2008dataset comparing characteristics of cases where placement was noted (n=2,383),and cases where no placement was noted (n=24,764). Bivariate analysis andPearson’s chi-squared tests were conducted to compare select child, household,and case characteristics of these two types of cases.RESULTSA higherpercentage of placement investigations involved children younger than 1 yearold (14%) compared to no placement investigations (8%). At least one childfunctioning concern was noted in 76% of placement child investigations and in42% of no placement child investigations. Ninety-three percent of placementinvestigations noted at least one caregiver risk factor, and 75% of noplacement investigations. Placement cases noted varied percentages ofcategories of maltreatment investigations, with neglect as the most frequent(54%), followed by physical abuse (15%), emotional maltreatment (14%), exposureto intimate partner violence (7%), and sexual abuse (3%). Of no placementcases, neglect was most noted (29%), followed by exposure to intimate partnerviolence (24%), physical abuse (17%), emotional maltreatment (10%), and sexualabuse (3%). Forty percent of placement cases noted emotional harm requiringtherapeutic treatment, compared to a significantly lower percentage for noplacement cases (12%). Placement cases noted a higher percentage where physicalharm was severe enough to require treatment (7%), compared to no placementcases (1%). Seventy-four percent of placement cases noted the duration of asuspected or substantiated maltreatment event occurring over multipleincidents, compared to 41% for no placement investigations. DISCUSSION AND CONCLUSIONSThisanalysis shows the multi-faceted nature of casework placement decision-making,and the breadth of factors caseworkers consider while attempting to balancecompeting child welfare orientations [3]. Findings are consistent with currentliterature where placement cases were noted as having a higher percentage ofchildren younger than 1 year old, and factors which create a greater level ofrisk to the child such as increased child functioning concerns, increasedcaregiver risk factors, and poorer household conditions. Placement cases notedhigher percentages for physical abuse, neglect, and emotional maltreatment.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".