International Journal of Population Data Science (Dec 2020)
Embracing Sensitivity, Enhancing Impact: Developing A Co-Production Model of Public Engagement for Administrative Data Research
Abstract
Introduction Public engagement and impact are important to research funders. But how these are done successfully in administrative data research is less established than in research where engagement mechanisms are more embedded. As admin data research is a relatively new field in public understanding, questions arise around how to utilise potentially sensitive datasets, or to utilise ‘ordinary’ data sets to illuminate issues around vulnerable or marginalised communities. Objectives and Approach Our objective was to develop an approach to maximise engagement with NGOs, data owners and policymakers; and research impact. We will use a series of case studies to demonstrate how we employed principles of public engagement in a model of co-production with stakeholders using project Steering Committees, targeted events and involvement workshops. Steering Committees comprised of governmental policymakers, data owners, and NGO representatives have a key role in shaping the research questions, responding to results, and incorporating findings into their work. Results Engagement on several of our projects have been key to accessing data previously unavailable for researchers, shepherding findings towards government initiatives in need of evidence, helping to interpret findings, and directing future research. This has been particularly true of research on potentially sensitive topics. Conclusion / Implications Governments have traditionally been cautious about data-sharing. Their default position is inertia, fearing public backlash. However, proactive and robust engagement is possible with complex and sensitive datasets. It enhances research and is demonstrates to data owners the potential for generating new evidence from datasets that have previously been unused for research. Engagement and impact strategies have to work with, rather than around, the sensitivities in data research to deepen and maintain the social license and impact on policy and practice.