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Background and objectives:‘Race’ and ethnicity data have become increasingly institutionalised within health research about indigenous peoples. While these data are critical to monitoring the differential distribution of risks and benefits in racialised societies, their uncritical and under-theorised use can perpetuate harmful biologically-deterministic and essentialist approaches to indigenous health. Additionally, indigenous rights and interests in data about us are often overlooked, with issues of indigenous data governance unresolved. The workshop objectives are to: Develop skills to critique uncritical use of ‘race’/ethnicity in indigenous health researchProvide examples from Aotearoa/New Zealand of frameworks or principles of indigenous data sovereignty
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In Aotearoa New Zealand (Aotearoa NZ), Māori (the Indigenous peoples of New Zealand) have long been objects of surveillance by state institutions and agents. State representations have centred on constructions of difference and deviance, on understandings of Indigenous peoples as dangerous, and on the management of Indigenous resistance to colonialism. This chapter considers how contemporary state surveillance practices in Aotearoa NZ, enabled by the expanded use of big data and linked government datasets, function to regulate and manage Māori. Through this lens, we explore continuities of current data practices for Indigenous peoples with the racialised logics and social orders set in place as part of global systems of imperialism and colonialism. Recognising that resistance has always been a part of Indigenous responses to colonialism, we also explore how Māori Data Sovereignty (MDSov), as part of broader Indigenous Data Sovereignty (IDS) movements globally, provides opportunities to counter and disrupt prevailing data relations and to imagine alternative futures.
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Indigenous Data Sovereignty (IDS) and Indigenous Data Governance (IDG) art terms increasingly being used across community, research, policy and in practice. The IDS movement has emerged in response to poor data practices, from the conceptualisation of data items through to reporting of data about Indigenous peoples. This chapter aims to provide clarity concerning the definitions of IDS and IDG; provide an overview of the historical context in which IDS has emerged; and provide examples of IDS and IDG across the spectrum of community, policy and practice.
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Colonization fundamentally disrupted Indigenous knowledge systems, establishing epistemic hierarchies that privilege Eurocentric colonial epistemologies and methodologies. In this chapter, the authors explore how epistemic hierarchies are (re)produced in the current context of “big data” and datafication, in particular for mokopuna Māori in the nation-state known as New Zealand (NZ). (We use the concept of “mokopuna Māori” to refer to and position Māori babies, children, and young people within the Māori world as the sacred reflection of our ancestors and a blueprint for future generations.) The chapter then considers the possibilities for Indigenous epistemic justice in the “zone of nonbeing” or beyond the “abyssal line.”
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Global disease trackers quantifying the size, spread, and distribution of COVID-19 illustrate the power of data during the pandemic. Data are required for decision-making, planning, mitigation, surveillance, and monitoring the equity of responses. There are dual concerns about the availability and suppression of COVID-19 data; due to historic and ongoing racism and exclusion, publicly available data can be both beneficial and harmful. Systemic policies related to genocide and racism, and historic and ongoing marginalization, have led to limitations in quality, quantity, access, and use of Indigenous Peoples' COVID-19 data. Governments, non-profits, researchers, and other institutions must collaborate with Indigenous Peoples on their own terms to improve access to and use of data for effective public health responses to COVID-19.
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