2023
Measuring Intersectional Biases in Historical Documents
Nadav Borenstein, Karolina Stanczak, Thea Rolskov, Natacha Klein Käfer, Natália da Silva Perez, Isabelle Augenstein
ACL 2023findings
Data-driven analyses of biases in historical texts can help illuminate the origin and development of biases prevailing in modern society. However, digitised historical documents pose a challenge for NLP practitioners as these corpora suffer from errors introduced by optical character recognition (OC…