This paper explores how the propensity of social workers to make a direct and unmitigated connection between good intentions, rationale thought and good outcomes forms a white noise barrier that substantially interferes with our ability to see negative outcomes resulting directly or indirectly from our works. The paper begins with outlining the harm experienced by Aboriginal children before moving to explore how two fundamental philosophies that pervade social service practice impact Aboriginal children: 1) an assumption of pious motivation and effect and 2) a desire to improve others. Finally, the paper explores why binding reconciliation and child welfare is a necessary first step toward developing social work services that better support Aboriginal children and families.

Fluke et al. (2010) analyzed Canadian Incidence Study on Reported Child Abuse and Neglect (CIS) data collected in 1998 to explore the influence of clinical and organizational characteristics on the decision to place Aboriginal children in an out-of-home placement at the conclusion of a child maltreatment investigation. This study explores this same question using CIS data collected in 2003 which included a larger sample of Aboriginal children and First Nations child and family service agencies. The decision to place a child in an out-of-home placement was examined using data from the Canadian Incidence Study of Reported Child Abuse and Neglect-2003 and a reanalysis of CIS-1998 data (Fluke et al., 2010). The CIS-2003 dataset includes information on nearly 12,000 child maltreatment investigations from the time of report to case disposition. The CIS-2003 also captures information on the characteristics of investigating workers and the child welfare organizations for which they work. Multi-level statistical models were developed to analyze the influence of clinical and organizational variables using MPlus software. MPlus allows the use of dichotomous outcome variables, which are more reflective of decision-making in child welfare and facilitates the specific case of the logistic link function for binary outcome variables under maximum likelihood estimation. Final models revealed the proportion of investigations conducted by the child welfare agency involving Aboriginal children was a key single agency level predictor of the placement decision. Specifically, the higher the proportion of investigations of Aboriginal children, the more likely placement was to occur. Contrary to the findings in the first paper (Fluke et al., 2010), individual Aboriginal status also remained significant in the final model at the first level. Further analysis needs to be conducted to further understand individual and organizational level variables that may influence decisions regarding placement of Aboriginal children. There is also a need for research that is sensitive to differences among, and between, Métis, First Nations and Inuit communities. Results are not generalizable to Québec because data from this province were excluded.

First Nations children experience service delays, disruptions and denials due to jurisdictional payment disputes within and between federal and provincial/territorial governments. The House of Commons sought to ensure First Nations children could access government services on the same terms as other children when it unanimously passed a private members motion in support of Jordan's Principle in 2007. Jordan's Principle states that when a jurisdictional dispute arises regarding public services for a First Nations child that are otherwise available to other children, the government of first contact pays for the service and addresses payment disputes later. Unfortunately, the federal government adopted a definition of Jordan's Principle that was so narrow (complex medical needs with multiple service providers) that no child ever qualified. This narrow definition has been found to be unlawful by the Federal Court of Canada and the Canadian Human Rights Tribunal. The present commentary describes Jordan's Principle, the legal cases that have considered it and the implications of those decisions for health care providers.