6.5 Data in the Social Sciences

Natalie Boldt and Loren Gaudet

Writing in the social sciences involves not only citing other scholarship, but also presenting and communicating primary data. “Primary Data” is a term that describes quantitative or qualitative information that has been gathered, collected, generated, observed, or created by researchers to validate research findings. “Quantitative” refers to information that can be counted and measured (usually represented in numerical form), and “qualitative” refers to information that is represented in non-numeric form, such as text, audio, or images. In the social sciences, researchers use both kinds of data to provide evidence for their claims, and sometimes they use both quantitative and qualitative together (called mixed-measures or mixed-methods).

Data takes many forms. Some examples include:

  • laboratory or field notebooks
  • diaries
  • surveys and questionnaires
  • transcripts
  • audiotapes
  • raw measurements (like government statistics)
  • videotapes
  • photographs
  • films
  • blogs
  • emails
  • spatial data

The kinds of data that a researcher obtains will depend on the kinds of questions that they seek to answer, and the means available to them. Part of writing in the social sciences involves explaining and sometimes justifying the choices that you’ve made in terms of gathering data. For instance, if you wanted to research how many first-year undergraduate students living in campus housing were accessing mental health supports, you might seek ethics approval to distribute a questionnaire to first-year students living in residence, asking if they’ve accessed mental health support in the past year, and what kinds of support they accessed (for more on ethics in research, see Chapter 4.2). The answers to this questionnaire would comprise data that you could then analyze in order to explain its significance.

Because data is information that is gathered, collected, generated, observed, or created, this means that it is inherently bound up with power. Gathering data about something, someone, or someones (such as a group of people) means that the researcher is setting out to produce knowledge about that something, someone, or someones. We discuss the ethics of research and knowledge production, as well as its potential to be invasive, unethical, and occasionally criminal, in Chapter 4.2 of this book, but it’s important to mention the ethical dimensions of research again here.

When gathering data about people (human subjects), it’s important to obtain approval from a university research ethics board before starting your research. These structures are in place to support researchers and to protect people and groups of people who may be involved in research as participants. For example, in the course of gathering data for this chapter, we wanted to get a sense of what instructors teaching in the Social Sciences perceived as strong student writing. So, we reviewed UVic’s Human Rights and Ethics Board guidelines and decided that we needed to seek approval to do a survey and interviews. We needed to explain what we wanted to ask and if our questions would cause any potential harm to our research participants. This process ensures that researchers are critical of their own practices and that human participants are protected from potential harm. In some cases, groups have created their own research protocols. The Indigenous Innovation Initiative, for example, has created an Indigenous Knowledges and Data Governance Protocol that provides an overview of ways to protect Indigenous data and ensure data sovereignty:

Why do Indigenous Knowledges and data need to be protected?”

“Through centuries of colonization, oppression and undermining of First Nation, Inuit and Metis Worldviews and Peoples, they continue to face challenges with collection and use of their Knowledges and data. This includes the following examples:

Appropriation: Indigenous Knowledges or data are applied in non-Indigenous contexts without consent, and misrepresent or mock Indigenous ways of knowing and being.

Misrepresentation: The health status of Indigenous Peoples is misrepresented through data that focus on Western concepts of well-being, often excluding spiritual, emotional and mental well-being that comes from access to ceremonies, traditional medicine and languages, community and other non-physical components of well-being. Indigenous data that is used out of context also perpetuates false stereotypes about Indigenous Peoples.

Lack of transparency: Indigenous Knowledges or data are used without consent or in ways that are not consented to or known about.

Lack of reciprocity: Indigenous Knowledges or data are not shared back with the community or Knowledge Keepers.

Lack of stewardship: Indigenous Knowledges or data are stored in databases that communities and Knowledge Keepers do not have control of or access to.

Aggregate data: Indigenous Knowledges or data are only made available in an aggregate way which can misclassify or combine information about First Nation, Inuit and Metis Peoples, making it impossible for them to use their own information and misrepresenting them as homogenous which can erase unique histories and ways of knowing and being.

Legislation: Indigenous Knowledges or data collected by publicly-funded work is property of the government and can be made public through privacy, access and archival laws without consent. As well, once a non-Indigenous person receives rights to use Indigenous Knowledges, terminology, intellectual property etc., for example as the name of a product, this information no longer belongs to or can be protected by Indigenous Peoples.

Patriarchy: Patriarchal systems have replaced traditional governance systems in many communities, and the traditional role of women, Two Spirit, queer, trans and gender diverse people as leaders and decision makers has been threatened or lost entirely.

Imposition: Data collection requirements are imposed on communities through funding agreements, and the resulting data are not relevant to or mutually supportive of their planning and decision-making needs.[1]

The Indigenous Knowledges and Data Governance Protocol reminds us of the multiple ways that data can harm people and groups, and that the production of knowledge is always political. Let’s turn to an example to make this clear. Historically, museums have been the source of many, if not all, of the challenges that the authors of this protocol describe. Many museums continue to appropriate, misrepresent, and poorly steward Indigenous knowledge and culture in the form of valuable artifacts, ancient remains, and cultural narratives. When museums collect, catalogue, or display Indigenous knowledge without the express permission, input, or oversight from the cultures and communities from which those materials come, they perpetuate colonialism and do harm to those communities. Fortunately, more and more museums are attempting to reverse these harms through a practice called “repatriation”: a process by which both human remains and stolen treasures are returned to their rightful owners, families, and communities more broadly. By way of example, in recent years, the Royal BC Museum in Victoria, BC has been involved in efforts to return many of the items it has collected without permission.[2]

The point that we’re trying to make here is that it’s crucial that researchers think critically about gathering data and producing knowledge. These practices are not a universal good—that is, these are not activities that are always unproblematically a good thing—and they can have repercussions for different groups. You may have heard the slogan “Nothing About Us Without Us.” This slogan has been adopted by the United Nations Convention on the Rights of Persons with disabilities, and emphasizes that people with disabilities need to be involved in the production of knowledge, research, and policies from the beginning (as opposed to being included as an afterthought). This slogan has been taken up by other groups who have been historically excluded from having a say in how they’re represented or in making decisions, including sex workers, people who are unhoused, people living with HIV/AIDS, and people who use drugs. This motto reminds researchers, policy makers, government officials, and others in positions of power to produce knowledge with instead of about people. So, before asking how to gather data, it’s always important to ask if you should be gathering data. But if the answer is yes, and you’ve gathered the data, knowing how to represent this data is an important part of writing in the social sciences!

  1. Indigenous Innovation Initiative, Indigenous Knowledges and Data Governance Protocol (Indigenous Innovation Initiative, 2021), 11, https://indigenousinnovate.org/discover-i3/resources/indigenous-knowledges-and-data-governance-protocol.
  2. If you’d like to learn more about what repatriation and ethical data collection look like, you might consider reading this incredible Indigenous Repatriation Handbook prepared by Jisgang Nika Collison, Sdaahl K’awaas Lucy Bell, and Lou-ann Neel and published by the Royal BC Museum.


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Why Write? A Guide for Students in Canada 2nd Edition Copyright © 2022 by Natalie Boldt and Loren Gaudet is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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