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[[Complexity]], you cannot. | [[Complexity]], you cannot. | ||
[[Complexity]] | [[Complexity]] describes the ''limits'' of the [[narrative]]. [[Complexity]] is the wilderness ''beyond'' the [[rules of the game]]. [[Complexity]] inhabits the noise, not the signal. Where there is complexity, ''algorithmic rules do not work''. Here ''data'' is relegated to ''noise''.<ref>Provisional theory: “information” is [[data]] framed with a hypothesis.</ref> | ||
This is why physical sciences apparently have a greater success than social sciences | This is why physical sciences apparently have a greater success than social sciences: they ask themselves easier questions: Physical sciences generally address behaviours of independent events — rolling balls, [[Coin flip|flipping coins]], waves [[and/or]] particles of light. But rolling balls are not autonomous agents. They act independently. The behaviour of one will not influence that of another. Each [[coin flip]] is, as a condition of probability theory — independent.<ref>The technical term: “platykurtic”.</ref> Independent events obey Gaussian principles. They may be modelled. That is to say, they may be [[complicated]] but they remain predictable, at least in theory. When physical systems inexplicably go bang — Chernobyl, the Shuttle ''Challenger'', the ''Torrey Canyon'' — the [[root cause]] will not be a failure of the physical science underlying the engineering, but some supervening cause invalidating the underlying assumptions on which the physical science was based. Things go bang because of [[non-linear interaction|''non-linear'' interactions]]. | ||
[[Social science]]s don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, ''un''predictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who ''are'' influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.<ref>physical sciences set up closed logical systems within which their rules will work, and often these systems are dramatically simplified as compared with anything you see in the real world: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and ''cannot'' not exist. {{author|Nancy Cartwright}} calls these structures “[[nomological machine]]s”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to [[falsification]], but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial [[crisp packet blowing across St Mark’s Square]].</ref> | [[Social science]]s don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, ''un''predictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who ''are'' influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.<ref>physical sciences set up closed logical systems within which their rules will work, and often these systems are dramatically simplified as compared with anything you see in the real world: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and ''cannot'' not exist. {{author|Nancy Cartwright}} calls these structures “[[nomological machine]]s”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to [[falsification]], but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial [[crisp packet blowing across St Mark’s Square]].</ref> |