Â鶹AV

National Outcomes Matrix (NOM): Phase V

CRCF Members in this Project: Nico Trocmé

Principal Investigator:ÌýNico Trocmé
Co-Investigators: ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý A. Shlonsky
Period: ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý 2010-2012
Award:ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý $95,000 ($ 20,000 allocated 10-11)
Funding Source: ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý Provincial/Territorial Directors of Child Welfare

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The National Child Welfare Outcome Matrix (NOM) was developed in consultation with provincial, territorial, and First Nations service providers as an initiative of the provincial and territorial Directors of Child Welfare (DCW) and Human Resources Development Canada. The NOM provides a framework for tracking outcomes for children and families receiving child welfare services that can be used as a common set of indicators across jurisdictions. For the past five years, a team of researchers from Â鶹AV and the University to Toronto has collaborated with the Federal/Provincial/Territorial [FPT] Child Welfare Outcomes Committee to provide support in operationalizing and testing the NOM indicators. Each participating province and territory has contributed significant staff time to support this operationalization and pilot testing phase, in addition to contributing funds to support travel to FPT Child Welfare Outcomes Committee meetings. In order to continue with further testing the indicators, provinces and territories have contributed funding to support the ongoing work required. A total of 8 indicators have been tracked from 2003/04 to 2009/10, with up to 10 jurisdictions providing partial to complete data for each. The research team has continued work on NOM through the development of a secure website to allow for centralization of working documents to facilitate the next phase of data collection and analysis. Further, an inter-jurisdictional thesaurus has been developed to track differences in terminology and the organization of child welfare service in Canada for the purposes of better comparing data collected.

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