The Walkerville Weekly Reader

National Desk: Hard-hitting journalism from your completely un-biased (pinky swear!) reporters in Walkerville, VA.

Walkerville, VA
Monday, June 10, 2024
Carolyn Purcell, Editor

New York Times secret evidence

The New York Times pioneers secrecy as an advanced new tool in criminological scholarship.

The New York Times, charged with fabricating data about mass murders, responded that “the data we presented in our series is not the data we used to reach our conclusion, and we pointed that out in the series. We very clearly stated that our data did not support our conclusions. Really, they were separate articles, merely under the same headline. We find it surprising that our critics did not recognize this.” According to Times spokesperson Dean Baquet, the Times used super-secret data from the FBI which they were unable to print. “The FBI told us that if we ever let this information out, they would hunt us down and kill us like dogs,” said Baquet. “So of course we had to show other evidence in place of it.” He further said that while there is a requirement in all research to present both data and conclusions, there is no requirement that the two be related. “Anyone who says otherwise is probably biased,” said Baquet.

According to Baquet, most experts praised their series as aggressive and objective. When asked which experts these were, Baquet responded that “we can’t tell you that either. If we did, we’d have to kill you.” Baquet further stated that the Times’ secret experts definitely outnumbered any opposing experts. “Just tell us how many experts think we fabricated the data or made specious conclusions,” said Baquet, “and I can guarantee that I will be able to say that a larger number support our data and conclusions.”

Yale University Professor John Lott is one of those who claim the Times lied, but according to Baquet, “John is just jealous of our data. He doesn’t have any secret data or any secret experts, so what good can his conclusions be? He makes all of his data public, and discusses it directly when making conclusions, so you know it must be wrong. The only good data is secret data. How else can you make your data say what you want it to say?”

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