One reason why classification is an unreliable guide as to what should or should not be published by the press is that classification policy is implemented erratically by the government.
In a new report for Congress, the Government Accountability Office found numerous problems in classification activity at the Department of Defense.
“Our review of a … sample of 111 classified DOD documents from five OSD offices shows that, within these offices, DOD personnel are not uniformly following established procedures for classifying information, to include correctly marking classified information,” the GAO report said.
“In our review of the OSD documents, we questioned DOD officials’ classification decisions for 29 documents–that is, 26 percent of the sample.”
“The majority of our questions centered around two problems: the inconsistent treatment of similar information within the same document, and whether all of the information marked as classified met established criteria for classification.”
See “Managing Sensitive Information: DOD Can More Effectively Reduce the Risk of Classification Errors” (pdf), June 30, 2006.
A companion report reviewed classification activity at the Department of Energy.
See “Managing Sensitive Information: Actions Needed to Ensure Recent Changes in DOE Oversight Do Not Weaken an Effective Classification System” (pdf), June 30, 2006.
When the U.S. government funds the establishment of a platform for testing hundreds of behavioral interventions on a large diverse population, we will start to better understand the interventions that will have an efficient and lasting impact on health behavior.
The grant comes from the Carnegie Corporation of New York (CCNY) to investigate, alongside The British American Security Information Council (BASIC), the associated impact on nuclear stability.
We need to overhaul the standardized testing and score reporting system to be more accessible to all of the end users of standardized tests: educators, students, and their families.
Integrating AI tools into healthcare has an immense amount of potential to improve patient outcomes, streamline clinical workflows, and reduce errors and bias.