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Scientific Study War

by: Pierre Huel

Scientific Study War POL 121

Pierre Huel
GPA 3.56

Kyle Joyce

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Kyle Joyce
Class Notes
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This 27 page Class Notes was uploaded by Pierre Huel on Tuesday September 8, 2015. The Class Notes belongs to POL 121 at University of California - Davis taught by Kyle Joyce in Fall. Since its upload, it has received 6 views. For similar materials see /class/187554/pol-121-university-of-california-davis in Political Science at University of California - Davis.


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Date Created: 09/08/15
BREMER 1992 amp CEDERMAN 2 Kyle A Joyce Department of Political Science University of California Davis October 1 6 2009 HWTIRQDHGENEN n Argues that previous research on the causes of war suffer from n Inappropriate unit of analysis 1 Limited spatialtemporal domain a Faulty case selection eg selecting on the dependent variable a Bivariate statistical methods D Questionable measures of war D As a result it is difficult to compare findings on the causes of war 1 The goal is to overcome the problems listed above and come to a conclusion about which factors are most likely to produce war a Two schools balance of power and power preponderance a The power preponderance school argues that states that are radically different in power eg one side has a preponderance of power should not engage in war because it is clear the weaker state would lose I The balance of power school argues that when two states are relatively equal in power neither can be certain of victory and they therefore deter each another from war n In short power parity promotes war power preponderance school or power parity promotes peace balance of power school 7 PREDK I Dyads that contain one or more major powers should be more war prone than those that do not I However are states considered major powers because they fight many wars If so the claim that major powers are more war prone would be tautological Dmmmongi Dam U1 D Unit of Analysis dyad year specifically non directed dyad year because the 7 propositions do not speak to who initiates a war and who is the target a Non directed Dyad US UK 1865 n Directed Dyad US UK1865 UK US 1865 1 Spatial Domain Any pair of states that are members of the interstate system COW definition 1 Temporal Domain 1816 1965 B Observations 202778 non directed dyad years between 1816 and 1965 DEWNEWQNSE 1 The 7 propositions deal with the likelihood of wars between states and do not deal with the duration severity or size of those wars that do occur Thus measures of war that are based on the duration severity or size of wars are inappropriate to test the 7 propositions Cl D A distinction must be made between the initial combatants originators in a war and those states that become involved in a war after it starts joiners because the propositions do not deal with the likelihood that a state will join an ongoing war D Only examines the original participants in a given war DEFINITIONS I Do all wars begin with only one participant on each side DEFINITIONS I R I Do all wars begin with only one participant on each side No I A decision needs to be made to deal with wars that have multiple originators on a side I The solution is to treat wars with multiple originators on a side as independent dyadic war onsets I 85 total war dyads INDEPENDENT VARIABLES RELATIVE POWER I Measured the year prior to the onset of a war Why INDEPENDENT VARIABLES RELATIVE POWER Measured the year prior to the onset of a war Why I Uses COW CINC data I For each dyad computes CINC Capability Ratio CINCsmaHer I Next classifies the dyads into three categories Capability Ratio g 3 small power difference 3 lt Capability Ratio g 10 medium power difference Capability Ratio gt 10 large power difference I Capability Ratio is an example of a categorical variable INDEPENDENT VARIABLES POWER STATUS I Each dyad was coded as having a power status of major major major minor or minor minor using the COW designations BIVARIATE I Compares the conditional probabilities of war in a dyad year given the presence of the conditions specified by each proposition I The degree to which the conditional probabilities relevant to a proposition vary from one another is then used as evidence for the proposition I See Table 1 RESULTS BIVARIATE RELATIVE F I The conditional probabilities for each of the three power categories are not that different from one another I The effect of a difference in relative power is small at best I War is more likely between dyads that have small or medium power differences than dyads that have large power differences RESULTS BIVARIATE P I Major major dyads have the highest probability of war followed by major minor dyads and then by minor minor dyads BIVARIATE I Ranking from strongest to weakest Proximity Power status Alliance Militarization Democracy E Development Power difference RESULT I Bivariate analyses assumes that the 7 independent variables are uncorrelated ie do not vary with one another I Thus strong relationships between an independent variable and war onset may be spurious and weak relationships may become strong when the effects of other variables are removed I Additionally the direction of the effect as well as the strength may be affected Creates a binary measure for each variable Relative Power was coded low medium high now1 if smallmedium power difference 0 otherwise Power status was coded major major major minor minor minor now1 if major majorminor minor 0 otherwise I 27 128 possible dyad types Creates a new dependent variable that equals a count of the number of war onsets that a particular dyad type experienced I See Tables 3 and 4 I Small or medium difference in relative power increases the likelihood of war I Overwhelming preponderance ceteris paribus is a pacifying condition I Presence of a major power increases the likelihood of war I Ranking from strongest to weakest the conditions that characterize a dangerous dyad Presence of contiguity Absence of more advanced economy Absence of democratic polity Absence of overwheirning preponderance E Presence of a major power INT RC D U C I The goal is to explain Richardson39s finding that the severity of interstate wars is power law distributed I Power laws describe events wars strikes city sizes earthquakes terrorist attacks etc whose frequency are inversely proportional to their size I Among earthquakes there are many with few casualties fewer large ones and very few huge disasters C If S is a random variable of war sizes then P5 gt 5 gives the probability that there are wars of greater severity than 5 1 Thus whereas for small wars the likelihood of larger wars has to be close to 1 this probability approaches 0 for very large wars because it is very unlikely there will be any larger wars a It can be postulated that the cumulative probability scales as a power law P5 gt s C50 where C is a positive constant and D is a negative number m Figure 1 shows the cumulative probability P5 gt s as a function of s the severity of interstate wars on double logarithmic scales 1 If wars follow a power law the fit should be linear logP5 gt s logC Dlogs where the intercept is logC and the slope coefficient is D l i b amp mm Elma 3 jams Mammal Wail L39 QlPSJTiF HC t JLJIT D Selforganized criticality connotes slowly driven threshold systems that exhibit a series of metastable equilibria interrupted by disturbances with sizes scaling as power laws In this context thresholds generate noninearities that allow tension to build up Per Bak using a sandpile as a metaphor constructed a model that produces power laws If grains of sand trickle down slowly on the pile power lawdistributed avalanches will be triggered from time to time In short a steady linear input generates tensions inside a system that in turn lead to nonlinear and delay output ranging from small events to large events quot1 amp awn rim 3 1mm mam WE AGENT BASED lv lODELING I Uses agent based modeling to examine the macro patterns of war I Agent based modeling is a computational methodology that allows scientists to create analyze and experiment with artificial worlds population by agents that interact in non trivial ways and that constitute their own environment U D U 50x50 square lattice or grid populated by 200 statelike agents that interact locally In each time period agents allocate resources to each of their borders and then choose whether or not to fight with their territorial neighbors All agents use the same grimtrigger strategy which means they normally reciprocate their neighbors39 behavior but should one of their neighbors attack the respond by fighting until the battle is won or there is a draw There is also the possibility of unprovoked attacks if an agent is sufficiently stronger than its neighbor If fighting involves neighboring states contextual activation occurs and an agent attempts unprovoked attacks every period Ewing Wlulg ix ll imzmmm Mail Giwgtrm 1 When the local capability balance tips decisively in favor of an agent conquest results and the more powerful agent absorbs the targeted agent which produces territorial expansion D Territorial expansion produces more resources for the victorious agent 1 The capitals of the victorious agent can then extract more resources and project power farther away I Technological change increases the ability of agents to project power farther away C MPUTER b MULATIONS I Computer simulations show that systems lacking contextual activation are unlikely to generate power laws I Technological change and contextual decision making play crucial roles in generating progressively larger conflicts C NCLUSIONS I Technological change and contextually activated decision making go a long way toward explaining why power laws emerge in political systems


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