In Braiding Sweetgrass, Robin Wall Kimmerer tells a number of stories that challenge the ways Western science constructs knowledge, and therefore understands nature. In one example, she discusses the ways trees help and communicate with each other through symbiotic mycelia. Because experts study individual trees, or via Darwinism, competition for survival/reproduction, it was impossible for them to see the collaboration right before their eyes! While Kimmerer’s ideas might be debated by some scientists, as an outsider to forest ecosystem biology, I find the ideas compelling and the epistemology that enables them even moreso.
Epistemology is a weird word, deployed in many ways by different parties. I tend to think of epistemology as a concept grasping at the ways we relate to knowledge, typically unconsciously. In the example Kimmerer explains, a particular set of biases for how we conduct science and experiments meant that we saw what we were looking for: individual trees competing for precious, limited sunlight and water resources. Attempts to silence Kimmerer (and there seem to be many) might be charaterized as a type of epistemic injustice; that certain concepts and categories for understanding the world have been given automatic power and preference over others.
Philosopher Miranda Fricker gave us two categories of epistemic injustice: testimonial and hermeneutical. The first relates to unfairnesses in trusting someone’s word. The latter relates to the concepts and categories through which people interpret their lives and the world. Epistemic injustice is, in other words, a way of describing a certain way in which oppression takes place, making certain ways of knowing, understanding, and communicating one’s experiences difficult or impossible.
There are many ways this applies to data work. Here’s a few:
- Whoever defines the concepts and categories for data collection also defines which concepts and categories of knowledge and experience are given priority.
- Concepts and categories for data collection are built from Western scientific priorities only, often on a medical model. We know in human service work that these concepts/categories are too narrow for what we do.
- The concepts/categories given by our data systems are the ones we spend time talking to clients about, and shape what does/doesn’t count in our listening to clients.
- Rigidly determined concepts and categories mean that clients become a source of data, rather than participants in diagnosis/treatment and that experiences must fit an existing mold.
Our concepts and categories come from some problematic places! This article discusses the ways the “fathers” of statistical analysis were deeply embedded in eugenics. Stephen Jay Gould, Nancy Lesko and others trace the ways that developmental theories were also created by eugenicists and have given shape to our confident characterizations of young people. Many are also embedded in the work of colonialism – in trying to define one group as the top and remake others in their image.
This prompt thus opens two questions:
- What are the concepts and categories that give shape to existing approaches to data collection, and where do they come from?
- Are there ways to create data that subvert single concepts and categories, or make room for others?
Books like The Routledge Handbook of Epistemic Injustice might help data workers trace and deconstruct the concepts and categories shaping existing approaches to data collection.
Regarding the second question, I think there are some great examples! The Indigenous Mapping Collective shows that even mapping geography has a particular epistemology – and that mapping from other ways of understanding the world can help see and reclaim knowledge and relationship to land. The Reggio Emilia approach to documentation (prompt 1) is based in a model that tries to recognize the “hundred languages of children” (“language” is partly a metaphor for epistemologies). Anastasia Philippa Scrutton suggests that we might attend to the epistemic privileges of our clients – to seek to understand the world from a point of view that only they have privvy to (Routledge Handbook of Epistemic Injustice, 2019, p. 351). Participatory Action Research (Prompt 3) work is strongest when it recognizes the epistemic privileges of co-researchers, and works to relate to their knowledges in ways that help other participants move beyond their default epistemological stances.
As is becoming clearer, each of the Prompts in this series is connecting to the others. They form an interrelated web of ideas, and work best in concert with each other. Other prompts / methodologies can be used to challenge epistemological injustice (and should be!). Only doing Reggio documentation of PAR work, without challenging epistemological injustices, weakens the power of the work to build more just data work.