gml_mid_ddlydisps: Directed Leader-Dyadic Dispute-Year Data with No Duplicate...

gml_mid_ddlydispsR Documentation

Directed Leader-Dyadic Dispute-Year Data with No Duplicate Leader-Dyad-Years (GML, v. 2.2.1, Archigos v. 4.1)

Description

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.

Usage

gml_mid_ddlydisps

Format

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

Details

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.

References

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. β€œAn Analysis of the Militarized Interstate Dispute (MID) Dataset, 1816-2001.” 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): 269–83.


peacesciencer documentation built on March 31, 2023, 8:37 p.m.