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statistical analyses of war and peace


Trends in climate and civil war in Africa (1960–2005), arguably showing a lack of linkage, from Buhaug13 mean annual precipitation; deviation from mean annual temperature; Low and high estimates14 Africa with outbreak and incidence of civil wars at Richardson Scale ≥1.415


are, objectively speaking, not dichotomous opposites at all but shades of a continuum. Richardson was (statistically) concerned


with death rates as a standard comparator, but there are other variables. On the humanitarian end of the spectrum, the number of wounded (particularly if disabled) are of equal concern, if less often mentioned. On the hard-nosed side come economic costs. The two approaches are not, in fact, so far removed as they might seem: a significant proportion of a population killed or disabled, displaced or suffering from post-traumatic stress, has implications for production capacity, medical overhead, social disruption, and so on. Equally, the chreodic mathematics of state change in politics7


are not only relevant to similar


jumps within conflict data, but can also pinpoint connection vectors between one and the other, and the often fatally rapid transition between them. Full scale warfare amounts to a total


audit of its participants’ economic capacity. It is comparatively rare, but so is unqualified peace. Most of the time, various degrees of partial or latent warfare absorb a significant proportion of resources which is therefore unavailable for other purposes and so becomes a focus of intense analytic attention. Globally, according to SIPRI’s Military Expenditure database, that proportion is about 2.7 per cent of GDP; in Europe somewhat less. In the US 4·3 per cent; in the Middle East, several economies maintain it at levels from seven per cent


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to more than eight per cent. These figures are, in almost every case, greater than the science budget which illustrates the scale of economic commitment which they represent (though spending on warfare and R&D interpenetrate to a considerable degree). Since war is, as Clausewitz8


bluntly put it, an ‘instrument of policy, a continuation


Measuring deadly quarrels Richardson’s ‘scale of deadly quarrels’ places conflicts on a logarithmic range from pub brawl to global annihilation. The intention was to remove as much vagueness as possible from comparisons so the gradation refers to loss of human life directly resulting from the conflict, without taking into account, for example, deaths attributable to disrupted medical services or sanitation. Points on the scale correspond to the order of decimal magnitude. A single murder, therefore, registers zero on the scale. There is no theoretical upper limit but, at present population levels, a global all out war resulting in complete elimination of the human race would currently come in at just over 9·8. Between those extremes, the First World War ranked around 7·6, the Second World War somewhere between 7·8 and 7·9, the 2003 invasion of Iraq almost exactly five, the 1979 to 1988 Soviet campaign in Afghanistan six. By way of comparison, the Sumatra-


Andaman tsunami of 2004 would on the same scale record as just under 5·4, the Sichuan earthquake two years ago as nearly 4·9.


. In clockwise order from top left: deviation from of annual war deaths in Africa; frequency of countries in


of political intercourse by other methods’, computation is (see box: Gambling on military economic odds) often concentrated on balancing minimised cost against maximised benefit.


The scale of war Since Richardson’s death, and particularly since the advent of plentiful scientific computing power, his work has been built upon by others and there is now a sizable academic community contributing to this field. The largest current collection of databases is probably the Correlates of War project (CoW), started by J David Singer in 1963. Though it starts, like Richardson’s, in the Napoleonic era, it continues to the present day, is considerably more extensive, and has expanded to include a more sophisticated range of variables. Another prominent example is the Conflict Barometer9


published by the Heidelberger


Institut für Internationale Konfliktforschung (HIIK), which extends its conflict analyses to ‘crises... coups d’état, negotiations, mediations, peace settlements...’ HIIK also maintains the Conflict Simulation Model (KOSIMO) designed by the University of Heidelberg’s Frank R Pfetsch. Richardson demonstrates that


distribution of armed conflicts follows a Poisson distribution, with many conflicts at the lower points of his scale and few at the higher – a conclusion which remains solid today. One researcher currently working in Libya comments that ‘I have been mapping


APRIL/MAY 2011 9


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