 Solution

Yes: replacing the observed statistic by a significance label loses information. The binary positive event has Bayes factor $(1-\beta )/\alpha \simeq 16$, but the observed-statistic Bayes factor varies continuously with $y$. A result just at the threshold has $B_{10}(1.65)\simeq 2.74$, while $B_{10}(3)\simeq 79.0$. Both would receive the same positive label.

The binary calculation is correct for that deliberately coarsened observation; its problem is treating it as the whole evidence when the statistic is available. This is the point developed in Goodman and Greenland's response.