Appendix 1.1
Preamble
This section goes over the concepts and language used in the book. It starts with stating that data is a living taonga (meaning good or possession) and Maori data includes things like data from organisations and businesses and data used to describe Maori collectives. Indigenous data sovereignty perceives data as subject to the laws of the nation from which the data was collected, meaning Maori data should be subject to Maori governance.
Purpose
Te Mana Raraunga (the Maori Data Sovereignty collective) seeks to promote Maori aspirations and wellbeing through protecting the collection and use of Maori data, in favour of the Maori people (iwi) and their rights. This includes Maori involvement in the governance of the data and the development of Maori data infrastructure. This includes through: data rights and interests as they relate to the Mataatua Declaration, the WAI262 claim, and the UNDRI; data governance as the state already collects a lot of data on Maori people through the OSS but only a small proportion of this is accessible to Maori people; data storage and security which includes the legal and privacy frameworks regarding cloud storage of data ; and data collection, access and control which is about the fundamental decisions to collect data on Maori people and how this data is analysed. Maori research ethics (Te Ara Tika) mandate that data mandates that the Maori people must be able to use it to meet their own needs.
Guiding principles
Maori Data Sovereignty requires discussions about data at the governance (mana) and operational (mahi) levels.
Mana-Mahi framework
Whanaungatanga and Whakapapa: the former is that Maori thinking states that the relation between man, the world, and spiritual powers are everything. The latter evidences the linkages.
Rangatiratanga: this speaks to the hapu, or Maori aspiration for self determination, particularly in relation to actions which impact their people or environment. This relates to data ownership and control here.
Kotahitanga: this speaks to collective vision and unite while recognising individualism. The recognition of collective aspirations for data is vital.
Manaakitanga: this is the responsibility to provide hospitality to iwi, the community, and the environment. This requires Maori people being able to live as Maori, as well as being able to live the ‘good life’.
Kaitiakitanga: this is about the iwi responsibility to be a steward for a sustainable future for all people.
Data and the United Nations Declaration on the Rights of Indigenous Peoples – Megan Davis
Introduction
It is recognised that in order to deal with inequalities, we generally need data on who these inequalities pertain to and how. This is often not as easy as it sounds as ethnic groups may not be fully or properly recognised in data collection. This chapter examines this issue from the perspective of the UN Declaration on the Right of Indigenous Peoples (UNDRIP) and the UN Permanent Forum on Indigenous Issues (UNPFII).
The problem of data and indigenous peoples of the United Nations
The UNPFII is an advisory body to the Economic and Social Council (ECOSOC) within the UN. basically, they’re intended to provide advice to the ECOSOC on how to aid indigenous peoples and this requires data on indigenous peoples to begin with. The make up of the committee comes from a combination of indigenous populations and state representatives, giving it a better understanding of indigenous issues through the actual inclusion of indigenous people in the conversation.
While there are positives to the UNPFII, it is also met with scepticism by some indigenous peoples, who believe that it institutionalises indgienous issues within Western spheres of governance and so rejects indigenous self-determination. Another issue is that of recognition, as not all states acknowledge indigenous populations. States do not always recognise the self identification of indigenous peoples, which poses issues.
At the beginning of the UNPFII, it was recognised that data collection was a problem. Culturally specific data and standardised data was to be collected and made available for the benefit of indigenous populations. Both qualitative and quantitative data was collected and combined to conceptualise issues and underlying causes. It was deemed important that case studies conducted in partnership with indigenous people were important to emphasise the voice of these people, for example. However, case studies should not be seen in comparison with standard non-indigenous data and should not be the only form of data collection. Issues such as the political aspect of data collection needed to be recognised then, as well as the varying definitions of ‘indigenous’. Different forms of transience within indigenous communities (belonging to more than one, moving country, fleeing countries, etc) also posed issues for data collection. The fleeing of countries was generally due to warrior conflict, which in itself poses issues for data collection. Health issues and economic issues pose issues for data collection as they were often more ‘informal’ which are reported inadequately and difficult to translate to formalised data. There is also the obvious concern that this data could be used in racialised or racist ways despite being presented as neutral.
States have been called to commit to collecting data about and alongside indigenous populations by the UN, in ways which address the well-being of these populations, but there have been few examples of this being done so far (not none but limited) and no genuine global effort to do so.
UNDRIP and data collection
This provides the framework for normative content of the rights of indigenous peoples so is important for data sovereignty, albeit as a non-binding ‘soft’ international law. Some of the elements of the UNDRIP have been reflected in other international instruments as new norms but others are not commonly accepted as binding legal standards.
UNDRIP is a human rights instrument and there will always be issues quantitatively measuring the enjoyment of human rights. Qualitative data is important then but quantitative data can still be useful. It covers civil, political, economic, and social rights but also fundamental indigenous rights such as right to land and self-determination. Several identifiable themes are included: the rights to: self-determination; life, integrity and security; cultural, religious, spiritual and linguistic identity; education and public information; participatory rights; lands and resources. These are dealt with in more detail on pages 33 and 34. Articles 3 and 4 are the most important here, which deals with the right to self determination but the UNDRIP was developed with participation from indigenous peoples so as to accurately reflect their concerns and desires. The UNDRIP shows that universal standards for measurement for cross-country comparisons are possible and can be done positively but does require both ‘objective’ and ‘subjective’ data. Objective data is normally related to legal documents and is generally done as a desk review but should also be conducted by indigenous populations as the collection of this objective data is not objective. Both indigneous people and the states they live in must be trained to collect data properly and within their local contexts, with this data being compiled and made available by a supranational body like the UN.
Data politics and indigenous representation in Australian statistics – Maggie Walter
Introduction
Numbers, and so data as a result, may be real but it is worth asking who is making them real and for what purpose? Numbers like population statistics should not be seen as neutral but as human artefacts which are imbued with meaning, generally from dominant norms. This means that colonised societies and their population statistics inherently have racialised aspects to them. The non-neutrality of statistics is normally hidden by their numerical nature. These statistics then go on to influence social norms in a cycle, determining what is included and excluded. This chapter looks at how this plays out in Australia.
Five-D data and the statistical Indigene
Data on indigenous statistics that comes up on Google generally points to socioeconomic inequities suffered by Aboriginal and Torres Strait Islanders peoples. These are called the 5Ds here: disparity, deprivation, disadvantage, dysfunction and difference. When researchers attempt to look past these 5Ds, the data (such as that held by the HILDA) is small and groups Aboriginal and Torres Strait Islanders peoples as one homogeneous group. There is a lot of 5D data in contrast, which creates a trope around the statistical Indigene but there is little to no research on household functioning, for example. This does not mean it is unimportant to collect and record data on the existing inequities here (it is necessary) but it points out that there is no recording of data for indigenous people outside of this. This raises questions about why these statistics are not being recorded by projects such as HILDA. HILDA was viewed as a large scale, longitudinal study for policy makers but did not record much about indigenous populations beyond as a social problem.
5D data and the deficit data/problematic people correlation
Current data practices for Aboriginal and Torres Strait Islanders peoples come from data imperatives of colonialism which suggest racial unfitness, which goes as far as to challenge even the right to be indigenous. The suggestion through this data is that racial inequality is connected to social and cultural (racial) differences. This is not in itself controversial but it suggests that these inequalities are caused by the ‘problematic people’. This is used, for example, to advocate for closing Aboriginal communities ‘for their own good’. This is a form of ‘new racism’ which tries to explain why racial inequalities exist despite the consensus that racism is socially unacceptable. Now, instead of racial inferiority, cultural and moral inferiority is suggested of non-white populations. This permates systematically while the notion of individual racism is seen as being ‘defeated’.
This is complicated in colonial states as opposed to the black/white binary of America. Colonisation pervades Australian racial/social hierarchies which then facilitates and rationalised racialised discourses in society. These portrayals of Aboriginal and Torres Strait Islanders peoples are fed by statistics to justify the settler culture. Politics of the data is therefore important for the nation state/indigenous population relations. ‘5D data provide
an infinitely variable circular rationale for Aboriginal and Torres Strait Islander inequality, to the convenient exclusion of other less palatable explanations’. This justifies further settler mindsets and state action upon Aboriginal and Torres Strait Islanders peoples, including the silencing of their voices within the discourse through their victimisation. This is often legitimated by academic research, essentially suggesting that the indigenous people are at fault for their higher arrest rates (including socioeconomic issues within these groups) while failing to look at the root causes of these issues. This ignores that these phenomena are outcomes from longstanding racial inequalities from the colonial settler nation
How 5D data construct the dominant discourse on indigeneity
‘Problematic people’ discourses are often framed through statistics which reduce social and cultural phenomena to numerical values. This suggests impartiality and neutrality in whatever findings come from these statistics, even suggesting full objectivity. ‘Once social phenomena are perceived as ‘data’, it is an easy step to regard these data points as social facts – a dispassionate representation of Aboriginal and Torres Strait Islander reality.’ This serves to reproduce unequal power relations by defining what indigenous people are and can be/cannot be. Relentless remeasurements of these 5D factors, and a refusal to measure other factors, only serves to reify these ideas, furthered by Big Data which further distances numbers from the lived reality in which they are collected.
When the only Aborigine you know is the 5D statistical Aborigine
This data deficit/problematic people correlation is made worse by the disjuncture between Aboriginal and non-Abordiginal lives (in the day to day sense). Aboriginal lives are generally treated in an out of sight, out of mind manner so we live in different places even when living next to each other (Atkinson et al, 2010). This means Aboriginal people often only exist as statistics, including in the nation-state’s conception of self, which includes ignoring that they are Australia’s first nation people. This results in pervasive, negative stereotypes about Aboriginal people being responsible for their disparate socioeconomic position and also being overly entitled, despite evidence to the contrary.
Data that Walter collected in the AuSSA survey (2007) is given here and shows that large chunks of the non-Indiginous population don’t recognise contemporary racial inequality. However, even with the slight majority who did recognise it, little was done because the 5D data allows for a rationalisation of inequality through blaming those who suffer from it. This is furthered by a majority of non-Indiginous Australians not knowing an Aboriginal person (Walter, 2012). There is not a statistically significant relation between attitudes towards Aboriginal people and interaction with Aboriginal people, which Walter puts down to this lack of knowing Aboriginal people giving more power to discourses and stereotypes around Aboriginal people.
Disrupting the paradigm of Indigenous statistics
Even forgoing the question of if these numbers are real, it is important to ask how they are deployed, what do they say they portray, and who benefits from this? They portray an Indigineous deficit, contrasted with the non-Indigenous majority. These numbers support the status quo which means to disturb this discourse, we must disturb established tropes of data on Indigenous peoples.
This begins ontologically, as the Indigenous way of seeing the world is not the dominant one. Bourdieu’s (1984) concept of capital (social, cultural, and economic) is used here in the creation of a synthetic unity of the world, which leads to the assumption that this is how the world is. Habitus impacts world-view, basically and this includes in the collection of data about the world. It is a Euro-Australian and middle class view which has shaped how Indigenous statistics are understood and ‘done’. The fact that a majority of these middle class Euro-Australians are unlikely to know any Aboriginal people only makes this issue worse. They are likely only to know the 5D data Indigenous people which reinforces the Euro-Australian synthetic unity.
World view shapes how data is conducted and understood, including giving the idea that the questions asked here are the ‘only’ questions. Who has the power to make assumptive determinations in data shapes how the data is both collected and understood. Data drawn from the indigenous way of seeing the world will inherently change Indigenous statistics. This does not mean that these statistics are in opposition to Western derived statistics or that differences from Western derived statistics is what makes them ‘Indigenous statistics’. Instead, Indigenous data would make apparent the gaps in current data, such as the terrain of what is problematic or what should be measured and even who should be measuring. This is needed for the ‘recognition gap’ in statistics on Indigenous people to be rectified. Expanding the recognition space between Indigenous and non-Indigenous understandings allows for Indignenous people to speak back to the state using their own, statistical, recognised language, making it effective in reframing narratives around Indigenous people.
Platform Pedagogies 