It always begins with a story… How to (and why) work collaboratively with administrative data
The truth about stories… We are story tellers The language we use should align with the language of those we want to influence The language of policy is numbers: translation Vulnerable organizations
What data is “out there”? Held by different government agencies Each have rules related to stewardship
The paradox How to identify those living in marginalized circumstances in datasets: SES, ethnicity Rural and remote communities’ reality are swallowed by urban numbers Datasets not designed to answer research questions Small samples mean high level analyses Risk: essentializing, distorting, reducing…
Many breakfast meetings… Long term relationships Continuous informal discussions (stories) Policy vigilance Translation of stories into policy relevant research questions
The possible, the likely and the potential Planning stage Conceptual work Data extraction Analysis plan Review of findings Crafting of the “story” (reporting)
Supporting participation Staff position within the organization Purchased time on Board meeting agenda Assisting with fact sheets, resolutions, summaries Facilitating partnerships Community organizations telling their own story at conferences
Beyond academic expertitis… Multiple forms of expertise Multiple messages to be carried forward Being continuously alert to concerns: risk, fear, inaccessible language, relevance Multiple opportunities for collaboration Valuing and integrating the knowledge contributed Partial stories best woven with qualitative and other data