Data asset mapping for youth in care: why it matters
This guest post was co-authored by Kody Crowell and McGill University Professor, Naomi Nichols. It is the second blog post in a series of two describing the collaboration between Powered by Data and Dr. Nichols in identifying and outlining the data assets and processes used by Ontario’s child welfare system. We are excited to share the future findings our research will yield and invite your feedback on this project. Questions and comments may be directed to the principal investigator, Naomi Nichols, at <naomi.nichols@mcgill.ca>. We are particularly interested in feedback and comments related to our data asset map, which can be found here.
This post expands on the previous, explaining why studying the technological and data infrastructure used in the child welfare system could enable equitable monitoring activities and systemic changes to improve the life experiences of young people in and leaving the child welfare system. Click here for the first part of the series, where we define the concept of ‘data justice’ and outline our research activities.
One outcome of the data justice project has been the identification of all of the data assets and data processes used by Ontario’s child welfare system (click here to see the the most up-to-date version). This initiative is part of a larger five-year Social Sciences and Humanities (SSHRC) project called Data Justice: Fostering equitable data-led strategies to prevent, reduce and end youth homelessness. The project is investigating data-led governance and service delivery processes in Canada, paying particular attention to the ways that data-driven reforms influence the lives and well-being of young people living in poverty and experiencing housing instability.
Why does this work matter?
In order to begin to understand how data is mobilized in the child welfare sector to affect the lives of youth so deeply, we need to begin by understanding the data landscape more broadly. In particular, we need to know, quite simply, what data exists. What data is collected on children and youth and when? Who owns this data? Who uses this data besides the owner? Who else has access to the data? How does this data inform or structure other data collection and service delivery processes? How do the data inform governance processes and to what ends? From here, we begin to understand the quality-related aspects of the data: how is this data generated? How frequently is the data updated? At what level does the data identify the individual?
These questions are not easily answered. But as governments and public service delivery organizations begin to systematically generate and use data as part of their everyday operations, it is important to pay attention to how these processes influence policy-making, government oversight, service delivery and reporting processes. It is also critical that we track how these shifts in workplace technologies and practices influence the lives and well-being of the children, youth, and families who participate in provincial government systems.
For example, in Ontario, Children’s Aid Societies (CAS) agencies enjoy a large degree of autonomy. That autonomy has historically extended to their information management systems. Through our research, we have learned that data has historically been collected using a number of different instruments and collated using a number of different legacy systems. More recently, the CAS agencies of Ontario have been required to use the Child Protection Information Network (CPIN), an information system designed to standardize data collection and use practices and facilitate easier access and sharing of case files within individual societies. But because of the significant autonomy afforded to CAS agencies, precisely how they use this system is not mandated by the province. The result is increased potential for variation in how individual agencies report on their activities and young people’s experiences in care. A lack of standardization in terms of data entry practices, for example, makes it difficult to use CPIN to effectively identify and monitor regional and provincial trends.
Drawing on interviews with practitioners and advocates in child welfare and reviews of the open data inventories associated with the Ontario government, to date, we have systematically mapped the data assets for youth in and leaving care (YILC), including sources, owners, and users of the data. We have shown how and where various institutions may intervene in a young person’s life and thus open up a file and begin to collect data about the youth who is the focus of their intervention. But we have yet to see evidence that these data are being systematically used to track and improve intervention system outcomes for youth.
We anticipate there are places where this is happening, and we hope to identify these in the next phase of our research. We are also keenly aware that young people have few opportunities to engage with and officially contribute to the collection of data about their experiences in and leaving care. We hope to identify concrete opportunities for them to do just this.
How will our work change things?
In 2017, Dr. Naomi Nichols was part of the team that produced the Child Welfare and Youth Homelessness in Canada: A Proposal for Action, based on results from the first pan-Canadian study on youth homelessness, Without a Home: The National Youth Homelessness Survey (2016). This research found that almost 60% of homeless youth reported some type of involvement with child protection services over their lifetime. Compared to national data indicating that 0.3% of the general public receive child welfare services, youth experiencing homelessness are 193 times more likely to report interactions with the child welfare system. We think that our research will help identify important sources of data within the child welfare system that can be used to better understand and track this problem.
Professor Nichols is also a lead researcher and Powered by Data is a key collaborator on a pan-Canadian initiative called, Making the Shift Youth Homelessness Social Innovation Lab: A Network of Centres of Excellence. Through our involvement in this initiative, we hope to contribute to the prevention of youth homelessness through effective system reforms and just uses of data. We hope our research will lead to opportunities to reduce the risk of young people “slipping through the cracks” due to inefficiencies in data sharing and transparency (e.g., between the education, child welfare and youth justice systems, for example). We anticipate working with collaborators in government, service delivery organizations, young people with lived experiences of homelessness, and academics across Canada to effectively mobilize and use our findings to identify opportunities to improve systems monitoring and accountability processes so that young people in and transitioning out of the provincial care systems are able to lead the lives they desire.
We will also continue to advocate for legislation that centres youths’ rights to access their own personal information, as well as annotate or correct the data collected about them; standardized practices to ensure greater accuracy and better oversight for retention, data security, and sharing/integration; and opportunities to centre youth in their own data management, enabling increased self-determination over data collection and sharing.
Concluding remarks
Data are produced and used by people, as part of institutionally organized sequences of activity. Generating data about social life involves interpretive practices on the parts of those asking the questions, designing the methodologies and participating in data collection practices. All social data must be understood in relation to the social practices of their production and the actual social relations they are meant to represent (e.g., the caregiving relationship between children and their foster parent). Furthermore, the ways that data are used to make decisions about interventions and other activities depends on institutional priorities, economies and reporting practices as well as the professional practices and values of the individual practitioners who produce and use the data assets associated with a particular system.
It is thus essential to understand how people “negotiate” with and navigate information systems: how, for example, they convey their complex work with young people and families into a static set of categories for systemic monitoring and tracking. Subjective decisions about what to record and what to exclude are made daily by workers, influenced by the design of the systems they use. Our own suspicion is that these seemingly mundane aspects of contemporary social work might actually prove to be powerful organizers of social practices, particularly insofar as they render the lives of youth observable and thus governable. The next phase of this project will centre upon this inquiry. Through it, we hope to build on our existing knowledge of the data-led practices of the Ontario child welfare system to better intervene in those systems to promote more equitable outcomes for youth.