Privacy-preserving data mining has concentrated on obtaining valid results when the input data is private. An extreme example is Secure Multiparty Computation-based methods, where only the results are revealed. However, this still leaves a potential privacy breach: Do the results themselves violate privacy? This paper explores this issue, developing a framework under which this question can be addressed. Metrics are proposed, along with analysis that those metrics are consistent in the face of apparent problems. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications-Data mining; H.2.7 [Database Management]: Database Administration--Security, integrity, and protection General Terms Security Keywords Privacy, Inference