Maggie Walter
Maggie Walter (PhD; FASSA) is Palawa, a member of the Tasmanian Briggs family, Distinguished Professor of Sociology (Emerita) at the University of Tasmania. Her research challenges standard explanations of Indigenous disadvantage and she has published six books and over 100 journal articles and research chapters in the fields of Indigenous sociology, Indigenous Data Sovereignty and Indigenous methodologies. Maggie’s 2013 co-authored book Indigenous Statistics: a quantitative methodology (Taylor & Francis with Chris Andersen) has been cited more than 900 times. A new version of this book is due for publication in 2025. Recent publications include Indigenous Data Sovereignty and Policy (Routledge 2020, lead editor with T. Kukutai, S. Russo-Carroll and D. Rodriguez Lonebear) and Indigenous Sociology (Oxford 2023, lead editor with T. Kukutai, A. Gonzales and R. Henry). This latter book was the 2024 category winner of the Association of American Publishers annual PROSE Awards best Single Volume Reference Work. Maggie continues to work in the area of Indigenous Data Sovereignty. She is a founding member of the Australian Indigenous Data Sovereignty Collective (Maiam nayri Wingara), an executive member of the Global Indigenous Data Alliance (GIDA) and frequently presents on this topic, nationally and internationally. Since 2021, Maggie has been a commissioner with the Yoorrook Justice Commission in Victoria, Australia’s first truth telling inquiry.
Session
The field of Indigenous methodologies has grown strongly since Tuhiwai Smith’s 1999 groundbreaking Decolonizing Indigenous Methodologies. Contributions to scholarship and practice have emerged from First Peoples’ researchers across the globe including my own co-written (with Chris Anderson) 2013 book Indigenous Statistics: A Quantitative Methodology (Routledge). In this presentation I build on the two central premises of that writing. First, statistics are culturally embedded phenomena not neutral data. Across the Anglo colonized world, Indigenous data reflect the purposes and assumptions of those who commission, analyse and interpret them, not their subject. The result is a trope of deficit rather than the robust complexity of Indigenous lived realities. Second, methodology, rather than statistical methods, create these (non-Indigenous) culturally loaded data. The common failure to name up the methodology, as opposed to the method, used, normalises deficit data outcomes. I then use Indigenous Lifeworlds theory and the foundational principles of Indigenous Data Sovereignty to make the case for a fundamental disturbance of Western data logics via a mandatory recognition of methodology in Indigenous quantitative research.