gml_mid_ddlydisps | R Documentation |
These are directed leader-dyadic dispute year data derived from the Gibler-Miller-Little (GML) Militarized Interstate Dispute (MID) project. Data are from version 2.2.1 (GML-MID) and version 4.1 (Archigos). These were whittled to where there is no duplicate dyad-years. Its primary aim here is merging into a dyad-year data frame.
gml_mid_ddlydisps
A data frame with 10708 observations on the following 12 variables.
dispnum
a numeric vector for the dispute number
ccode1
a numeric vector for the focal state in the dyad
ccode2
a numeric vector for the target state in the dyad
obsid1
a character vector for the leader of the focal state in the dyad, if avialable
obsid2
a character vector for the leader of the target state in the dyad, if avialable
year
a numeric vector for the dispute-year
gmlmidongoing
a numeric vector for whether there was a dispute ongoing in that year
gmlmidonset
a numeric vector for whether it was the onset of a new dispute (or new participant-entry into a recurring dispute)
sidea1
is ccode1
on side A of the dispute?
sidea2
is ccode2
on side A of the dispute?
orig1
is ccode1
an originator of the dispute?
orig2
is ccode2
an originator of the dispute?
obsid_start1
the ID of the leader at the dispute onset for ccode1
obsid_start2
the ID of the leader at the dispute onset for ccode2
obsid_end1
the ID of the leader at the dispute conclusion for ccode1
obsid_end2
the ID of the leader at the dispute conclusion for ccode2
The process of creating these is described at one of the references below. Importantly, these data are somewhat
"naive." That is: they won't tell you, for example, that Brazil and Japan never directly fought each other during World War II.
Instead, it will tell you that there were two years of overlap for the two on different sides of the conflict and that the highest
action for both was a war. The data are thus similar to what the EUGene
program would create for users back in the day. Use these
data with that limitation in mind.
Data were created by first selecting on unique onsets. Then, where duplicates remained: retaining highest fatality, highest hostility level, highest estimated minimum duration, reciprocated observations over unreciprocated observations, and, finally, the lowest start month.
Be mindful that Archigos' leader data are nominally denominated in Gleditsch-Ward states, which are standardized to Correlates of War state system membership as well as the data can allow. There will be some missing leaders after 1870 because Archigos is ultimately its own system.
Miller, Steven V. 2021. "How to (Meticulously) Convert Participant-Level Dispute Data to Dyadic Dispute-Year Data in R." URL: http://svmiller.com/blog/2021/05/convert-cow-mid-data-to-dispute-year/
Gibler, Douglas M., Steven V. Miller, and Erin K. Little. 2016. βAn Analysis of the Militarized Interstate Dispute (MID) Dataset, 1816-2001.β International Studies Quarterly 60(4): 719-730.
Goemans, Henk E., Kristian Skrede Gleditsch, and Giacomo Chiozza. 2009. "Introducing Archigos: A Dataset of Political Leaders" Journal of Peace Research 46(2): 269β83.
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