Epistemic Injustice Scorer

This research tool in computational philosophy uses advanced AI to score text excerpts against 10 criteria for epistemic injustice drawn from the philosophical work of Miranda Fricker (2007) and Seunghyun Song (2021).

This original research tool in computational philosophy uses advanced AI to identify occurrences of epistemic injustice in text and evaluate them against 10 criteria proposed Miranda Fricker (2007) and Seunghyun Song (2021). The relevant terms are identified automatically from a given text, so just paste the text you're interested in analyzing into the excerpt box and click "Score This Excerpt."

This remains a research prototype, not a production moderation system. Every criterion and weight is inspectable and editable in classifier.py. It recommends a review band and does not auto-remove content.

Primary References

  • Fricker, M. (2007). Epistemic Injustice: Power and the Ethics of Knowing. Oxford University Press.
  • Song, S. (2021). Denial of Japan's military sexual slavery and responsibility for epistemic amends. Social Epistemology, 35(2), 160-172.

Relevant Empirical Research

  • Beach, M. C., et al. (2021). Testimonial injustice: Linguistic bias in the medical records of Black patients and women. Journal of General Internal Medicine, 36(6), 1708-1714.
  • Zhou, Y., Hu, D., Lyu, T., et al. (2025). Understanding stigmatizing language lexicons: A comparative analysis in clinical contexts. arXiv:2509.07462.