Data on classification activity of the United States government.
Fitzpatrick (2013) notes that the dramatic jump
in derivative classification activity
DerivClassActivity) that occurred in 2009
coincided with "New guidance issued to include
electronic environment". Apart from the jump in
DerivClassActivity tended to
increase by roughly 12 percent per year (with a
standard deviation of the increase in the natural
DerivClassActivity of 0.18).
A dataframe containing :
the calendar year
Number of people in the government designated
as Original Classification Authorities for
Original classification activity for the indicated year: These are the number of documents created with an original classification, i.e., so designated by an official Original Classification Authority.
OCActivity covered by the
10 year declassification rules.
Derivative classification activity for the indicated year: These are the number of documents created that claim another document as the authority for classification.
The lag 1 autocorrelation of the first
difference of the logarithms of
DerivClassActivity through 2008 is
-0.52. However, because there are only
13 numbers (12 differences), this negative
correlation is not statistically significant.
Fitzpatrick, John P. (2013) Annual Report to the President for 2012, United States Information Security Oversight Office, National Archives and Record Administration, June 20, 2013. Information Security Oversight Office (ISOO) of the National Archives.
## ## 1. plot DerivClassActivity ## plot(DerivClassActivity~year, USclassifiedDocuments) # Exponential growth? plot(DerivClassActivity~year, USclassifiedDocuments, log='y') # A jump in 2009 as discussed by Fitzpatrick (2013). # Otherwise plausibly a straight line. ## ## 2. First difference? ## plot(diff(log(DerivClassActivity))~year[-1], USclassifiedDocuments) # Jump in 2009 but otherwise on distribution ## ## 3. autocorrelation? ## sel <- with(USclassifiedDocuments, (1995 < year) & (year < 2009) ) acf(diff(log(USclassifiedDocuments$ DerivClassActivity[sel]))) # lag 1 autocorrelation = (-0.52). # However, with only 12 numbers, # this is not statistically significant.
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