CAUSATION AND RACE

By Paul Holland. 2003

97 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/394430242a68f838ad1c02788614c1da9dce97bf

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Impartial Predictive Modeling: Ensuring Fairness in Arbitrary Models (2016, background): “While different protected groups can clearly have different experiences and outcomes, treating s as a casual variable is fraught with difficulties (Holland, 2003).”
Can You Really Measure That? Combining Critical Race Theory and Quantitative Methods (2018, background): “While there is some concern that causal modeling may misinterpret racial issues (Holland, 2008), predictive, experimental/quasi-experimental,”
Towards a critical race methodology in algorithmic fairness (2019, background): “y of manipulating race, thus precluding its use as a causal variable. Several additional, more sociologically-grounded objections to the use of race asacausalvariablehaveemerged withinsocialstatistics[55],antidiscriminationlegalscholarship[67],andhealthresearch[46].These objections point to the fund”
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation (2022, background): “Their permissibility of use, however, for addressing class imbalance has been contested because of the infeasibility of manipulating demographic categories [62, 74, 110] and inaccurate conceptualizations of causality of demographic categories [64, 83].”
Engaging rational discrimination: exploring reasons for placing regulatory constraints on decision support systems (2010, unknown): “32 Koomey et al. (2002) 33 Kleindorfer et al. (1993) 34 Holland (2008).”