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System stability and transformation: a global system approach

Published online by Cambridge University Press:  26 October 2009

J. David Singer
J. David Singer
Affiliation:
Professor of Political Science, University of Michigan, Ann Arbor
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Extract

THERE are several reasons why we understand so much less about social processes and conditions at the global level than we do about comparable processes and conditions at lower levels of aggregation. One is, of course, that we are dealing with a larger empirical domain and one that is apparently more heterogeneous and complex. Another might be that the behaviour of nations – the key actors at this level of aggregation – has been shrouded more in mystery and taboo than the behaviour of other classes of social entity. By keeping diplomacy and military strategy in the category of the arcane, elites have inhibited serious inquiry, even if there were those unpatriotic enough to ask. A third and related factor may be the extent to which the national state has been the major source of material and psychic sustenance for the world's people over the past century or so and thus not an agency whose external behaviour will be questioned or examined closely. Others might be added to our list, but one that surely merits closer attention may be the way in which we conceptualize world affairs.

Type
Research Article
Information
Review of International Studies , Volume 3 , Issue 3 , October 1977 , pp. 219 - 232
Copyright
Copyright © British International Studies Association 1977

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References

page 220 note 1. In an earlier paper, the case is made for attending to such other actors, territorial or not, from the longer range viewpoint. See Singer, J. David, ‘The Global System and its Sub-Systems: A Development View’, in Rosenan, James (ed.), Linkage Politics: Essays in and International Systems, (New York, 1969), pp. 21–43.Google Scholar

page 221 note 1. Campbell, Donald T., ‘Common Fate, Similarity and Other Indices of the Status of Aggregates of Persons as Social Entities’, Behavioral Science, iii (1958), pp. 14–25.Google Scholar

page 221 note 2. Singer, J. David, ‘Escalation and Control in International Conflict: A Simple Feedback Model’, General Systems Yearbook, xv (1970), pp. 163–73.Google Scholar

page 221 note 3. Milsum, John (ed.), Positive Feedback, (Oxford, 1968).Google Scholar

page 221 note 4. Cannon, Walter B., Wisdom of the Body, (New York, 1939).Google Scholar

page 222 note 1. Deutsch, Karl W., Nerves of Government, (New York, 1963).Google Scholar

page 223 note Small, Melvin and Singer, J. David, ‘Diplomatic Importance of States, 1816–1970: An Extension and Refinement of the Indicator’, World Politics, xxv (1973), pp. 577–99.CrossRefGoogle Scholar

page 223 note 2. These clusters can be identified through a variety of matrix decomposition algorithms in which the cells of a nation-by-nation matrix reflect the presence, absence, or strength of each dyadic bond. Among the algorithms that we have used are direct factor analysis, Johnson's hierarchical cluster technique and the Guttman and Lingoes smallest space analyses.

page 225 note 1. Sabrosky, Alan, ‘The War-Time Reliability of Interstate Alliances, 1816–1965’ (Washington, D.G.: ISA Meetings, 1975).Google Scholar

page 226 note 1. For a summary of the project's rationale, progress, and publications, see Singer, J. David, ‘The Correlates of War Project: Interim Report and Rationale’, World Politics, xxiv (1972);Google Scholar and Singer, J. David, The Correlates of War Project: Continuity, Diversity and Convergency, in Hoole, Francis and Zinnes, Dina (ed.), Quantitative International Politics: An Appraisal, (New York, 1976), pp. 21–66.Google Scholar

page 226 note 2. As a project such as ours unfolds, there will be changes in our coding rules and measuring procedures as well as the spatial-temporal domain, and as a result, the findings reported here cannot be interpreted as strictly comparable and thus cumulative. But we have selected out those indicators from each study that at least maximize their comparability. Further, time and again, we have found that such changes in indicators or domains produce very little change in our results.

page 226 note 3. Singer, J. David and Small, Melvin, ‘Alliance Aggregation and the Onset of War, 1815–1945’, in Singer, (ed.), Quantitative International Politics: Insights and Evidence, (New York, 1968), pp. 247–86.Google Scholar

page 227 note 1. One of the most direct ways of measuring the entropy score of the system would be to measure the extent to which it deviates from pure bipolarity; the greater the deviation, the higher the entropy score. There are, in turn, several ways in which polarity/bipolarity can be measured, but here we used a very simple algorithm reflecting the extent to which alliance bonds had removed, in any given year, the normal interaction opportunities among the major powers. For some more complex algorithms, see Wallace, Michael D., ‘Alliance Polarization, Cross–Gutting and International War, 1815–1964: A Measurement Procedure and Some Preliminary Evidence’, Journal of Conflict Resolution, xvii (1973), pp. 575–604CrossRefGoogle Scholar; de Mesquita, Bruce Bueno, ‘Measuring Systemic Polarity’, Journal of Conflict Resolution, (1975), PP. 187–216CrossRefGoogle Scholar.

page 228 note 1. The version of power used here is that of military-industrial-demographic capability, or more literally, the nation's power base. It rests, in varying combinations and weightings, on: total population, urban population, iron and steel production, energy consumption, military personnel, and military expenditures. The raw data, derived indicators, and theoretical rationale will be available in Melvin Small, et al., The Strength of Nations, forthcoming.

page 228 note 2. Singer, J. David, Bremer, Stuart A. and Stuckey, John, ‘Capability Distribution, Uncertainty and Major Power War, 1820–1965’, in Russett, Bruce (ed.), Peace, War, Numbers, (Beverley Hills, California: Sage Publications, 1972), pp. 19–48.Google Scholar