Abstract
Theory-building is the engine of the scientific enterprise and it entails (1) the generation of new hypotheses, (2) their justification, and (3) their selection, as well as collecting data. The orthodox views maintain that there is a clear logical and temporal order, and distinction, between these three stages. As a matter of fact, not only is this tenet defective, but also there is no way to solve these three issues in the way advocated by traditional philosophy of science. In effect, what philosophy of science tells us is that (a) there is not an infallible logic, in the sense of a simple set of logical rules, to justify and confirm a hypothesis, and (b) the process of generation of hypotheses is not unfathomable, but can be rationally investigated, learned and transmitted. So, as an alterative, I discuss the heuristic approach to theory-building, especially the one based on problems, and I argue that it offers a better way of accounting for theory-building than the traditional ways.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See in particular: Cellucci (2013), Ippoliti (2006, 2008, 2016), Ippoliti and Cellucci (2016), Magnani (2001), Magnani et al. (2010), Clement (2008), Jaccard and Jacobi (2010), Grosholz (2007), Grosholz and Breger (2000), Lakatos (1976, 1978), Laudan (1977, 1981, 1996), Nersessian (2008), Nickles (1980a, b, 1981, 2014), Nickles and Meheus (2009), Gillies (1995), Darden (2006), Ulazia (2015).
- 2.
See Cellucci (2013) for a discussion of these points.
References
Cartwright, N. (1983). How the laws of physics lie. New York: Oxford University Press.
Cartwright, N. (1996). Models and the limits of theories: Quantum Hamiltonians and the BCS model of superconductivity. In M. Morgan & M. Morrison (Eds.), Models as mediators: Perspectives on natural and social science (pp. 241–281). Cambridge: Cambridge University Press.
Cartwright, N. (1999). The dappled world: A study of the boundaries of science. Cambridge: Cambridge University Press.
Cartwright, N., Shomar, T., & Suarez, M. (1995). The toolbox of science. In W. Herfel, W. Krajewski, I. Niiniluoto, & R. Wojcicki (Eds.), Theories and models in scientific processes (pp. 137–149). Amsterdam: Rodopi.
Cellucci, C. (2008). Le ragioni della logica. Bari-Roma: Laterza.
Cellucci, C. (2013). Rethinking logic. Dordrecht: Springer.
Clement, J. J. (2008). Creative model construction in scientists and students: The role of imagery, analogy, and mental simulation. New York: Springer.
Darden, L. (Ed.). (2006). Reasoning in biological discoveries: Essays on mechanisms, interfield relations, and anomaly resolution. New York: Cambridge University Press.
Einstein, A. (2002). Induction and deduction in physics. In Albert Einstein (Ed.), Collected papers (Vol. 7, pp. 108–109). Princeton: Princeton University Press.
Einstein, A. (2010). Ideas and opinions. New York: Crown.
Frege, G. (1960). The foundations of arithmetic. A logic-mathematical enquiry into the concept of number. New York: Harper.
Gigerenzer, G., & Todd, P. M. (1999). Simple heuristics that make us smart. New York: Oxford University Press.
Gillies, D. (1995). Revolutions in mathematics. Oxford: Clarendon Press.
Gillies, D. (1996). Artificial intelligence and scientific method. Oxford: Oxford University Press.
Grosholz, E. (2007). Representation and productive ambiguity in mathematics and the sciences. New York: Oxford University Press.
Grosholz, E., & Breger, H. (2000). The growth of mathematical knowledge. Dordercht: Springer.
Hadamard, (1945). An essay on the psychology of invention in the mathematical field. Princeton: Princeton University Press.
Hempel, Carl Gustav. (1966). Philosophy of natural science. Englewood Cliffs: Prentice-Hall.
Ippoliti, E. (2006). Il vero e il plausibile. Morrisville (USA): Lulu.
Ippoliti, E. (2008). Inferenze ampliative. Morrisville (USA): Lulu.
Ippoliti, E. (Ed.). (2014). Heuristic reasoning. Berlin: Springer.
Ippoliti, E. (Ed.). (2016). Models and inferences in science. Berlin: Springer.
Ippoliti, E., & Cellucci, C. (2016). Logica. Milano: EGEA.
Jaccard, J., & Jacoby, J. (2010). Theory construction and model-building. New York: Guilford Press.
Kantorovich, A. (1993). Scientific discovery: Logic and tinkering. New York: State University of New York Press.
Lakatos, I. (1976). Proofs and refutations: The logic of mathematical discovery. Cambridge: Cambridge University Press.
Lakatos, I. (1978). The methodology of scientific research programmes. Cambridge: Cambidge Univesity Press.
Laudan, L. (1977). Progress and its problems. Berkeley and LA: University of California Press.
Laudan, L. (1981). A problem-solving approach to scientific progress. In I. Hacking (Ed.), Scientific revolutions (pp. 144–155). Oxford: Oxford University Press.
Laudan, L. (1996). Beyond positivism and relativism: Theory, method, and evidence. Oxford: Westview Press.
Magnani, L. (2001). Abduction, reason, and science: Processes of discovery and explanation. New York: Kluwer Academic.
Magnani, L., & Magnani, W. (Eds.). (2010). Model-based reasoning in science and technology: Abduction, logic, and computational discovery. Heidelberg: Springer.
Nersessian, N. (2008). Creating scientific concepts. Cambridge (MA): MIT Press.
Nickles, T. (Ed.). (1980a). Scientific discovery: Logic and rationality. Boston: Springer.
Nickles, T. (Ed.). (1980b). Scientific discovery: Case studies. Boston: Springer.
Nickles, T. (1981). What is a problem that we may solve it? Scientific method as a problem-solving and question-answering technique. Synthese, 47(1), 85–118.
Nickles, T. (2014). Heuristic appraisal at the frontier of research. In E. Ippoliti (Ed.), Heuristic reasoning (pp. 57–88). Berlin: Springer.
Nickles, T., & Meheus, J. (Eds.). (2009). Methods of discovery and creativity. New York: Springer.
Poincaré, H. (1908). L’invention mathématique. Enseignement mathématique, 10, 357–371.
Polya, G. (1954). Mathematics and plausible reasoning (Vol. I e II). Princeton : Princeton University Press.
Popper, K. (1999). All life is problem solving. London: Routledge.
Popper, K., & Miller, D. (1983). A proof of the impossibility of inductive probability. Nature, 302, 687–688.
Quarantotto, D. (2017). Aristotle’s problemata style and aural textuality. In R. Polansky & W. Wians (Eds.), Reading aristotle (pp. 75–122). Leiden: Brill.
Reichenbach, H. (1938). Experience and prediction: An analysis of the foundations and the structure of knowledge. Chicago: The University of Chicago Press.
Schippers, M. (2014). Probabilistic measures of coherence: From adequacy constraints towards pluralism. Synthese, 191(16), 3821–3845.
Shelley, C. (2003). Multiple analogies in science and philosophy. Amsterdam: John Benjamins B.V.
Simon, H. (1977). Models of discovery. Dordrecht: Reidel.
Simon, H., Langley, P., Bradshaw, G., & Zytkow, J. (1987). Scientific discovery: Computational explorations of the creative processes. Boston: MIT Press.
Suarez, M., & Cartwright, N. (2008). Theories: Tools versus models. Studies in History and Philosophy of Modern Physics, 39, 62–81.
Talalay, L. E. (1987). Rethinking the function of clay figurine legs from neolithic Greece: An argument by analogy. American Journal of Archaeology, 91(2), 161–169.
Ulazia, A. (2015). Multiple roles for analogies in the genesis of fluid mechanics: How analogies can cooperate with other heuristic strategies. Foundations of Science, https://doi.org/10.1007/s10699-015-9423-1.
Weisberg, R. (2006). Creativity: Understanding innovation in problem solving, science, invention, and the arts. Hoboken: Wiley.
Acknowledgements
I would like to thank David Danks, Carlo Celluci, and the two anonymous referees for their valuable comments on an early version of the paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Ippoliti, E. (2018). Building Theories: The Heuristic Way. In: Danks, D., Ippoliti, E. (eds) Building Theories. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-72787-5_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-72787-5_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-72786-8
Online ISBN: 978-3-319-72787-5
eBook Packages: Religion and PhilosophyPhilosophy and Religion (R0)