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Analysis of Scientific Prediction from Language

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Pragmatic Idealism and Scientific Prediction

Part of the book series: European Studies in Philosophy of Science ((ESPS))

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Abstract

Within the system of pragmatic idealism, the viewpoint of language is used for the analysis of prediction, in general, and scientific prediction, in particular. This chapter initially offers the general coordinates of a pragmatic idealist approach to language. Thereafter, it seeks to shed light on the semantic features of scientific prediction. First, Rescher’s characterization of prediction is analyzed. This leads to us to consider the distinction between “scientific” and “non-scientific” prediction, as well as the differences between “prediction” and “retrodiction.” Secondly, his contribution to the analysis of scientific prediction as a statement is made explicit. In this regard, the distinction between “qualitative prediction” and “quantitative prediction” is relevant, but we also need the distinction between “prediction,” “foresight,” “forecasting,” and “planning.” Finally, the limits of language are seen with regard to prediction, where the distinction between “non predictability” and “unpredictability” is highlighted.

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Notes

  1. 1.

    On the differences between the semantic and pragmatic approaches to reference , see Gonzalez (1986).

  2. 2.

    These two different usages of language appear in various authors, among them Michael Dummett . Within his large intellectual production on philosophy of language, it could be highlighted Dummett (1981). G. Frege and L. Wittgenstein, including his latter conception, reject a psychologist approach to language. Thus, concepts cannot be reduced to pure mental acts or mere psychological thoughts. Cf. Dummett (1985). Rescher shares with them the viewpoint of language conceived from a non-psychologist perspective. This explains why he is pragmatic on language and, at the same time, he accepts elements of the semantic view.

  3. 3.

    On realism and meaning two papers of M. Dummett can be highlighted. Cf. Dummett (1963, 1982). However, Dummett’s personal philosophy endorses a semantic anti-realism .

  4. 4.

    In this regard, Rescher writes that “blood circulated in the human body well before Harvey ; substances containing uranium were radioactive before Becquerel. The emergence at issue relates to our cognitive mechanisms of conceptualization, not to the objects of our consideration in and of themselves. Real-world objects must be conceived of as antecedent to any cognitive interaction—as being there right along, ‘pregiven’ as Edmund Husserl put it. Any cognitive changes or innovations are to be conceptualized as something that occurs on our side of the cognitive transaction, not on the side of the objects with which we deal” (1992a, p. 247).

  5. 5.

    On the differences between use conditions and truth conditions , as well as on the primacy that Rescher gives to the former over the later, see Rescher (1998d).

  6. 6.

    On the primacy of the pragmatic approach in his philosophical proposal on language, see Rescher (1998c).

  7. 7.

    He maintains that one of the reasons to accept the assumption that there is an objective and mind-independent reality is “to preserve the distinction between true and false with respect to factual matters and to operate the idea of truth as agreement with reality,” Rescher (2006, p. 390).

  8. 8.

    When he analyses prediction from language, his approach is also pragmatic, since predictive statements do not usually refer to an objective existing reality, but they has to do with the possible future.

  9. 9.

    On the economic features of communication , cf. Rescher (1989; especially, chapter 2, pp. 47–68).

  10. 10.

    On reliance and cooperation as principles that make it possible to minimize the costs of research and communication see Rescher (1989, pp. 33–46).

  11. 11.

    This is especially important in the case of scientific prediction, because it is not possible to determine now if what the predictive statement says is true or not.

  12. 12.

    What is expected can be in an ontological, epistemological, or heuristic sense.

  13. 13.

    From this perspective, an inductive inference is required, which allows us to obtain statements about the future on the basis of past experience. See Chap. 3, Sects. 3.2 and 3.3.

  14. 14.

    On this distinction, see Chap. 6.

  15. 15.

    From this perspective, it seems that Rescher considers that the methodological dimension is more relevant than the language when the demarcation between scientific and non-scientific prediction is at stake.

  16. 16.

    However, according to A. Grünbaum (1962), Hempel defends the possibility that “retrodiction ” and “prediction” can be equivalent. See Chap. 3, Sect. 3.5.2.

    .

  17. 17.

    This involves a difference between prediction and scientific explanation , which can be understood as an argument. Cf. Gonzalez (2010 , p. 260).

  18. 18.

    Prediction involves some kind of novelty . In fact , it is possible to claim that it is a “research on novel facts ,” Gonzalez (2010, p. 11).

    The philosopher who gave most importance to the notion of “novel facts ” was Imre Lakatos . See Lakatos (1978). On the notion of “novel facts ” in Lakatos ’ conception, see Gonzalez (2001, 2010, pp. 179–184, 2014).

  19. 19.

    Cf. Rescher, N., Personal Communication , 15.7.2014.

  20. 20.

    The differences between “prediction” and “retrodiction ” are addressed from a logical perspective in Chap. 3,, Sect. 3.5.2.

  21. 21.

    On the different senses of the notion of “novel facts ,” cf. Gonzalez (2001, pp. 505–508).

  22. 22.

    This feature is connected with the role of prediction as a guide for discovery , which is one of the roles of prediction that Rescher points out. Cf. Rescher (1998a, p. 160).

  23. 23.

    This has been analyzed by B. G. Malkiel in the case of financial and stock markets. Cf. Malkiel (1973).

  24. 24.

    The main features of this predictive procedure, which is developed on the basis of predictor’s expertise, already appear in one of the first papers on prediction by Rescher (1967).

  25. 25.

    For example, in economics qualitative prediction has been seen as complementary to quantitative prediction : “En general, podemos decir que el único procedimiento de predicción que se presta a ser analizado y evaluado de acuerdo con unos criterios científicos es el de los modelos econométricos. Sin embargo, estos procedimientos coexisten con una pléyade de instrumentos subjetivos, paneles de opinión, encuestas, valoraciones de expertos, etc., que muchas veces complementan o son complementados por los resultados de las predicciones basadas en modelos,” Fernández Valbuena (1990, p. 386).

  26. 26.

    On Kuhn ’s approach to prediction, see Gonzalez (2010, chap. 4, pp. 127–159).

  27. 27.

    Quoted in Gonzalez (2015, p. 69).

  28. 28.

    Rescher also addresses the ethical limitations to scientific activity and technological endeavor (1999a, pp. 151–203). His approach to the ethical limits of science and their incidence to scientific prediction are analyzed in Chap. 9, Sect. 9.3.

  29. 29.

    On the epistemological limits to prediction, see Chap. 4, Sect. 4.4.

  30. 30.

    In fact , Rescher uses the notions of “unpredictability” and “impredictability.” In his judgment, “an important difference is neatly marked in English usage by the difference between unpredictable and impredictable, the former being geared to volatility , the latter to intractability . In London weather conditions are unpredictable in March: one minute it can be clear and sunny and ten minutes later there may be clouds and rain. Here instability is at work. On the other hand, the future of the American poetry is impredictable: we simply have no grip on any laws or regularities that provide for rational prediction . Both cases alike frustrate the project of prediction,” Rescher (1998a, p. 137).

    It seems to me that the terms used by Rescher can lead to confusion. For this reason, the notions chosen in this monograph are different, in order to distinguish something that we cannot predict now from something that will never be predicted. “Non predictability” is used here instead of what Rescher calls “unpredictability.” Thus, a phenomenon is not predictable when there is a current impossibility of predicting it (either through a generic prediction or through a specific prediction). Meanwhile, “unpredictability” is used instead of “impredictability,” when there is a complete impossibility of predicting a phenomenon or event (either in the short, middle, or long run). See Gonzalez (2015, p. 56).

  31. 31.

    On chaos as an obstacle to scientific prediction, see Werndl (2009) .

  32. 32.

    This can be seen in the case of economics, where stable elements are sought in order to overcome the obstacles to predictability, such as human rationality in decision-making. Cf. Gonzalez (2003).

  33. 33.

    Moreover, the possibility of predicting the future depends on both epistemological and ontological issues. Regarding what we can predict or not in science, Rescher thinks that the best source of information we have comes from science itself: it is not an external issue. Moreover, only science itself can inform us about the achievable degree of precision for scientific prediction. This depends on circumstances such as the scope—short, medium or long run—, the available technology, etc. Additionally, it also depends on the question we want to ask. In principle, the more concrete the question is, the more complicated it will be to answer it accurately. Rescher, Personal communication , 17.6.2014.

  34. 34.

    In addition, Rescher considers that only science can inform us about its own limits, and this is always with regard to each particular moment. Cf. Rescher, N., Personal communication , 17.6.2014.

    Further details on the problem of “insolubilia ” have been developed in Sect. 1.3.2. of this book. See also Guillán (2016).

  35. 35.

    The characterization of his own epistemology in terms of fallibilism can be seen in Rescher (1999b, ch 3, pp. 29–42).

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Guillán, A. (2017). Analysis of Scientific Prediction from Language. In: Pragmatic Idealism and Scientific Prediction. European Studies in Philosophy of Science. Springer, Cham. https://doi.org/10.1007/978-3-319-63043-4_2

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