Fair Test Use in Selection1

By R. Linn. 1973

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ben Hutchinson
2. Margaret Mitchell
3. N. Dorans
4. M. Zieky
5. Emily L. Denton
6. Xinlei Chen
7. Inioluwa Deborah Raji
8. Jiasen Lu

Citations in the corpus

• 50 Years of Test (Un)fairness: Lessons for Machine Learning (2018, background): “In other words: What causes the disparities? (2) Drawing from earlier insights of Guion [30], Thorndike [62], Cole [14], Linn [43], Jones [37], and Peterson & Novick [52] to expand fairness criteria to include model context and use.”
• The New Faces of Fairness (2001, background): “Linn's model (Linn, 1973) indicates that a selection is fair if the proportion of those accepted who succeed is the same in all relevant groups.”
• Using Subpopulation Invariance to Assess Test Score Equity (2004, background): “Petersen and Novick (1976), in the lead article in a special issue dedicated to fair selection, compared several models for assessing fair selection, including the Regression model (Cleary, 1968), the Constant Ratio Model (Thorndike, 1971), the Conditional Probability Model (Cole, 1973), and the Con”