In Indigenous Statistics: A Quantitative Research Methodology, Maggie Walter and Chris Andersen examine how methodology shapes the questions researchers ask, the information they collect, and the meanings they draw from it. They distinguish methods, the tools used to collect and analyze information, from methodology, the broader framework of assumptions, values, and perspectives guiding their use. This framework reflects the researcher’s positionality, including their social background, race, class, gender, and experiences. It also includes epistemology, what counts as knowledge and whose knowledge is recognized; axiology, the values and priorities guiding research; and ontology, how reality, identity, and relationships are understood.
The authors develop these ideas across the book’s six chapters. Chapter 1 examines how mainstream statistics produce narrow pictures of Indigenous life. Chapters 2 and 3 explain methodology and develop Indigenous approaches to quantitative research. Chapters 4 and 5 show these approaches in practice through Australian and Canadian examples. Chapter 6 calls for stronger statistical skills and Indigenous leadership, enabling communities to shape research around their own priorities and goals.

Introduction

We often think of statistics as a straightforward way to describe the world, but they also shape how we see it. Researchers decide what to count, how to group people, and what to leave out, drawing on their own backgrounds and the priorities of governments and institutions. For Indigenous peoples, these decisions influence funding, public services, and how their communities are understood. Official statistics often highlight poverty, poor health, and other disadvantages. Although these inequalities are real, focusing on them can leave much of Indigenous life out of view and make non-Indigenous ways of living seem like the natural standard.
The authors argue that we need to look beyond statistical techniques to the broader approach guiding their use. They distinguish methods, such as statistical analysis, from methodology, which includes the questions, values, categories, and assumptions shaping the research. Statistical tools can produce different understandings when Indigenous perspectives and priorities guide these choices. The same attention is needed in qualitative research, since interviews and storytelling are also shaped by researchers’ positions and academic expectations. Research becomes Indigenous through the approach guiding the whole process, rather than simply through the identity of the researcher.
Drawing mainly on Australian and Canadian examples, the book explores how Indigenous peoples can use statistics to tell fuller accounts of their lives and advance their own goals. It recognizes shared experiences of colonization while respecting differences between peoples and communities. It also emphasizes that Indigenous knowledge continues to develop through contemporary life, including life in cities, and can guide statistical research. The invitation extends to Indigenous and non-Indigenous researchers alike, asking them to examine their assumptions and help create research that supports communities’ priorities and self-determination.

Deficit Indigenes

When governments measure Indigenous lives mainly through gaps in health, education, employment, and income, they create a picture centred on disadvantage. This chapter explores how that picture takes shape in Canada and Australia. Although the inequalities are real, treating non-Indigenous life as the standard can make Indigenous communities appear to be the problem. Policies then focus on changing their behaviour, while giving less attention to unequal resources, government decisions, and colonial relationships. Statistics and policy reinforce each other, repeatedly measuring the problems that existing policies already recognize.
The Canadian example shows how the definition of a population changes the picture produced. Census questions shifted from a focus on ancestry toward self-identification within official categories. In the data discussed, people reporting Indigenous ancestry formed a larger, more urban, and economically better-off population than those identifying within the specified categories. Government reporting increasingly relied on the latter group. The authors question how a category useful for targeting services became accepted as the main account of Indigenous identity. In Australia, they show how Indigenous people were included within statistical systems whose priorities remained largely government-controlled. National averages combined diverse Indigenous nations, while reports sometimes highlighted improvements without clearly showing whether inequalities were narrowing.
The authors’ concern is that technically accurate statistics can still offer a limited understanding. Categories determine whose experiences become visible, while presentation and interpretation shape how responsibility is assigned. Comparisons can reveal inequality, but they can also reinforce stereotypes when they leave out history, local circumstances, or the advantages of the dominant population. An Indigenous approach would ask why these inequalities exist and persist, while making room for communities’ own priorities and fuller accounts of contemporary life. This requires examining the assumptions guiding statistical research alongside the accuracy of its calculations.

Conceptualizing Quantitative Methodologies

Before explaining what makes research Indigenous, the authors ask what a methodology actually includes. They describe three connected parts, consisting of a researcher’s standpoint, the theories they use, and their methods for collecting and analyzing information. Standpoint shapes how researchers choose and use theories and methods. It includes their social position, what they recognize as knowledge, the values guiding their decisions, and how they understand reality. These influences help explain why researchers notice different problems, ask different questions, and interpret the same information differently.
All researchers bring these influences into their work, although some are more often asked to explain them than others. Indigenous scholars are frequently expected to account for their identities and commitments, while dominant Western approaches are treated as neutral. The authors argue that researchers, universities, and funders all shape which knowledge receives attention and whose voices are overlooked. Theories also reflect their creators’ circumstances. Feminist scholars, for example, challenged earlier accounts that treated unequal household roles as natural. Recognizing these influences can strengthen careful research by making its assumptions open to examination.
Indigenous methodologies make Indigenous perspectives, relationships, and priorities central throughout the research process. They can use statistical techniques and adapt Western theories while examining whose interests these serve. Sharing tools or a common methodological structure does not erase meaningful differences between approaches. The authors also caution against defining Indigenous research only as the opposite of Western research, since this keeps Western approaches at the centre. Indigenous methodologies should be understood through Indigenous peoples’ own lives, knowledge, values, and relationships with land and community.

The Paradigm of Indigenous Methodologies

Indigenous methodologies begin with the knowledge, relationships, and priorities of Indigenous peoples. They shape the whole research process, including which questions matter, who makes decisions, how findings are understood, and who benefits. Researchers have responsibilities to communities, land, and the people sharing knowledge with them. These responsibilities include respecting collective rights and community control over knowledge. Although Indigenous methodologies share some principles, they vary across peoples and places. The authors focus on communities in wealthy settler states with related colonial histories, while recognizing important differences within and between them.
The chapter argues that statistical research can express Indigenous perspectives just as interviews and storytelling can. What matters is how the research is guided and used. Indigenous knowledge also includes what people learn through contemporary life, such as living in cities, using technology, and dealing with government institutions. Restricting Indigenous research to inherited traditions can reinforce the colonial expectation that Indigenous peoples must remain unchanged. Quantitative methods can help communities address present concerns and challenge official accounts that reduce their lives to disadvantage.
Indigenous researchers can also turn their attention toward settler societies, examining how institutions, racial assumptions, and privilege sustain inequality. Using familiar statistical tools does not make their approach identical to mainstream research, nor must Indigenous methodologies be its complete opposite. The authors call for greater Indigenous authority throughout the statistical process, from defining categories to interpreting results. They also remind researchers that academic work reshapes community knowledge and carries its own privileges and responsibilities. Chapters 4 and 5 develop these ideas through practical examples from Australia and Canada.

nayri kati ("Good Numbers") - Indigenous Quantitative Methodology in Practice

This chapter shows how statistics can change when Indigenous perspectives guide the research through nayri kati, meaning “good numbers” in the palawa Tasmanian Aboriginal language. The approach grows from the author’s experiences as a trawlwoolway woman, including her community’s survival of colonial violence, the denial of Aboriginal identity, poverty, and political resistance. These experiences shape her interest in race, class, gender, and power. Her theoretical framework, the “domain of Aboriginality”, examines how material poverty, exclusion, everyday disrespect, and continuing dispossession reinforce one another. It connects Indigenous disadvantage with the advantages held by the settler majority and questions the assumption that mainstream statistical approaches are neutral.
Nayri kati places Indigenous people in positions of authority over research questions and interpretation. In one study, Indigenous researchers used official data to assess 37 universities individually, finding that about two-thirds scored below half the available points for Indigenous participation and governance. This directed attention toward universities’ responsibilities and actions. Its values also require research to offer meaningful benefits and respect continuing relationships. A study following Indigenous children therefore invested in trust, repeated community visits, and informed agreement about its purpose. Another study examined non-Indigenous attitudes, revealing a gap between recognizing inequality and supporting action to address it. Together, these examples show how Indigenous research can examine institutions and dominant groups as well as Indigenous communities.
The approach also changes how researchers understand the lives represented by numbers. Asking how Indigenous children grow up strong brings different relationships and resources into view from asking only about their disadvantages. Similarly, studying communities in Maningrida, Dubbo, and Perth through their particular histories and connections to the country revealed differences hidden by national averages. Housing and education figures became more meaningful when interpreted alongside local resources, dispossession, and community life. Shared inequalities across these different places then raised questions about why disadvantage persists and how settler privilege is maintained. The chapter shows that familiar statistical tools can produce fuller accounts when Indigenous knowledge, values, relationships, and priorities shape their use.

Indigenous Quantitative Methodological Practice-Canada

The way a census groups people shapes what we can learn about their lives. This chapter uses three Canadian examples to show how official categories can miss important forms of Indigenous belonging. The first concerns membership in particular Indigenous nations, whose different languages, histories, political systems, and relationships with land disappear within broad labels. Colonial rules helped establish these categories, and funding systems continue to rely on them. More accessible information about particular nations could support language revitalization, health services, cultural programs, and political representation.
The second example explores urban Indigenous communities. Counting Indigenous people within city boundaries reveals only part of their lives. It can miss relationships across nations, local organizations, experiences of racism, class differences, and continuing connections with home communities. The author argues that communities should help decide which questions and categories reflect their circumstances. Edmonton’s Wicihitowin initiative illustrates this possibility. Through extensive community discussions, Elders’ guidance, and surveys, residents identified their own concerns and priorities, producing information that existing census categories could not easily provide.
The third example examines how the census combines different meanings of Métis identity. Some respondents identify with the historically rooted Métis nation, while others use the term to describe mixed Indigenous and non-Indigenous ancestry. Without distinguishing these meanings, the figures cannot clearly describe the Métis nation or support its particular claims. Across all three examples, the problem lies in what the categories are designed to capture, even when the calculations are accurate. Different questions, developed with Indigenous communities and guided by their purposes, could produce equally valid statistics that better support their needs and self-determination.

Conclusion - Indigenous Peoples and Statistics

The book ends by asking how Indigenous peoples can gain greater influence over the statistics shaping their lives. Distrust of quantitative research is understandable given its history of treating people as specimens, supporting colonial control, and portraying communities mainly through disadvantage. These harms continue when research serves outside priorities and gives Indigenous peoples little authority. However, the authors argue that the problem lies in the framework guiding statistical tools. Interviews and other qualitative methods can also cause harm when used within unequal relationships.
Governments will continue producing statistics whether Indigenous researchers participate or not. Without their involvement, others will decide what to measure, which categories to use, and how to explain the findings. Because numbers carry considerable weight in policy decisions, the authors encourage Indigenous communities to develop the skills and resources to influence the whole statistical process. Statistical methods can be adapted to Indigenous values and priorities, helping communities challenge narrow portrayals and make stronger cases for change.
The authors also call for Indigenous researchers to take leadership across a broad range of research fields. Historically, they often helped outsiders access communities while receiving little recognition, control, or benefit. Growing research expertise creates opportunities to change these relationships, although some established researchers resist sharing authority. Supportive non-Indigenous colleagues remain important partners. Building quantitative skills is part of a wider effort toward research self-determination, allowing Indigenous peoples to direct knowledge production and work with their communities as partners.