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By Peter T. Manicas

This advent to the philosophy of social technology presents an unique notion of the duty and nature of social inquiry. Peter Manicas discusses the position of causality noticeable within the actual sciences and gives a reassessment of the matter of clarification from a realist viewpoint. He argues that the basic aim of thought in either the typical and social sciences isn't, opposite to common opinion, prediction and keep an eye on, or the reason of occasions (including behaviour). as a substitute, concept goals to supply an realizing of the tactics which, jointly, produce the contingent results of expertise. delivering a bunch of concrete illustrations and examples of serious principles and matters, this obtainable e-book can be of curiosity to scholars of the philosophy of social technology, and social scientists from various disciplines.

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Extra resources for A Realist Philosophy of Social Science: Explanation and Understanding

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1 There is hardly a textbook in quantitative methods in the social sciences that does not repeat some version of this. Compare the example in the previous chapter from Frankfort-Nachmias and Nachmias (1992). They write: Often the empirical attributes or events that are represented by concepts cannot be observed directly . . In such cases, the empirical existence of a concept (sic) has to be inferred. Inferences of this kind are made with operational definitions. ” So “T” has been “reduced”: for all practical purposes, it has been eliminated.

She makes things happen which otherwise would not have happened. Putting aside what might be called “exploratory experiments,” such as anatomical dissection, the aim of an experiment is to isolate or make constant all those properties except those one wants to study. Put roughly, the experimenter has a theory about some generative mechanism / causal process which, once initiated, has a predictable (in theory) outcome. Her aim, accordingly, is to trigger the mechanism, but to preclude anything which would have an effect on the outcome so predicted.

There is a sense in which this is true, but another in which it is not. It is true as regards the typical experiment, but despite much mythology to the contrary, predictions are not, in general, a reliable test of theory. To clarify this, we need first to introduce the concept of closure. This discussion leads to a sketch of the implications of the fact that in the real world, all the countless generative mechanisms are operating open-systemically. The upshot is radical contingency and, with it, critical limits on our ability to make predictions.

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