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 gam…
Read moreNeurodivergent 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.