Description Usage Format Details Source Examples
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 2009, the DerivClassActivity
tended to increase by roughly 12 percent per year (with a standard deviation of the increase in the natural logarithm of DerivClassActivity
of 0.18).
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A dataframe containing :
the calendar year
Number of people in the government designated as Original Classification Authorities for the indicated year
.
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.
Percent of 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 autocorrrelation 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 (https://www.archives.gov/isoo/reports)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ##
## 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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