Abstract
Choosing between candidates for a position can be tricky, especially when the selection test is affected by irrelevant characteristics (e.g., reading speed). One can correct for this irrelevant attribute by penalizing individuals who have unjustifiably benefited from it. Statistical models do so by including the irrelevant attribute as a suppressor variable, but can people do the same without the help of a model? In three experiments (total
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