Commentary: race and sex are causes.
By Clark Glymour, Madelyn Glymour. 2014
84 citations recorded by the source corpus.
Subfields: Statistics and Probability, AI Ethics, Fairness & Society
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Sander Greenland
- James F. Woodward
- Andrew Smart
- Matt J. Kusner
- Chris Russell
- Ricardo M. A. Silva
- Joshua R. Loftus
- P. Cummings
In AI Ethics, Fairness & Society
- Atoosa Kasirzadeh
- Sander Greenland
- James F. Woodward
- Andrew Smart
- Matt J. Kusner
- Chris Russell
- Ricardo M. A. Silva
- Joshua R. Loftus
Citations in the corpus
- Counterfactual Fairness (2017, background): “It is the plausibility of complex, even if impossible to practically manipulate, causal chains fromA to Y that allows us to claim that unfairness is real [11].”
- The problem of variable choice (2016, background): “For the opposite view with respect to race and gender, see Glymour and Glymour (2014).”
- For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates (2017, background): “Their triumph in this regard has generated a new wave of concerns and criticisms (e.g., King and Zeng 2007; Glymour and Glymour 2014; Vandenbroucke et al. 2016; Krieger and Davey Smith 2016; Schwartz et al. 2016, 2017), a few of which I discuss below.”
- The Use and Misuse of Counterfactuals in Ethical Machine Learning (2021, background): “There has been a long standing debate among several disciplines such as philosophy, sociology, law and epidemiology about the causal effects of social categories such as race and gender [12, 16, 34, 41].”