Doctor of Philosophy
Myrvold, Wayne C.
Neurodivergent people experience epistemic injustice, injustices that harm them in their capacity as knowers, but so far the epistemic injustice literature has mostly ignored this. This dissertation addresses this gap in knowledge in a novel way, using tools of formal epistemology. Bayesian network learning models that include modeled bias, communication style gaps, exclusion, and difference between people, are used to investigate testimonial injustice. Novel simultaneous Lewis-Skyrms signal games that include modeled bias, focus on success, gaps in way of thinking, exclusion, and difference in material interests are used to investigate hermeneutical injustice, the subset of epistemic injustice that involves concepts important to an identity group being obscured both in and out of that identity group, due to the model's ability to track formation of meaning over time. The model results indicate that improvement first requires neurodivergent people be integrated into social networks with mixed neurotypes, but that this must be done with care to not isolate neurodivergent people among neurotypical people, and without tokenizing. Additionally, the models give evidence of social evolutionary forces that would contribute towards the presence of ableism in norms of communication, so it is recommended that action to combat ableism should include actions that create countervailing cultural evolutionary pressure, and aim to benefit anyone whom the action hopes to win over.
Summary for Lay Audience
There is a specific kind of injustice that changes how good someone is at holding knowledge, and, in an unfair way, how good others consider them to be at holding knowledge. It is called "epistemic injustice." Previous discussion of this kind of injustice has paid attention to how someone's identity, such as race or gender, is at the root of the injustice, and how different identity groups experience it differently. However, researchers have mostly not paid enough attention to how people identified as "neurodivergent" have experienced it, such as autistic people and people with ADHD. I aim to investigate the way this injustice works for neurodivergent people by creating computer simulations of unjust situations based on their experiences. There are two main kinds of simulation I look at. The first creates networks of individuals working on their own and communicating with each other. I use the networks to investigate epistemic injustice by changing how the individuals in the network communicate with each other, and observe the results when they become biased or have trouble communicating. The second kind of simulation has individuals sending signals to each other that initially do not have a meaning, but can gain meaning as the individuals learn to associate them with events. Again, I change how the individuals are able to signal each other and observe the results. I then argue for some conclusions based on these simulations. For example, that we need to bring neurodivergent people into the mainstream, but in a way that helps them connect to each other too. If they are not connected to each other, there is a risk of not actually helping them because they are seen as tokens of progress instead of people to connect to. As well, I conclude that we should aim to make it easier to support neurodivergent people than not, either by making things easier for everyone, or getting in the way of people who want to harm them.
Marcotte, Mackenzie, "Using Formal Epistemology to Model Epistemic Injustice Against Neurodivergent People" (2023). Electronic Thesis and Dissertation Repository. 9229.
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