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Scientific Processes and Social Processes

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Abstract

We clarify the notions scientific process and social process with structuralist means. Three questions are formulated, and answered in the structuralistic, set-theoretic framework. What is a scientific process, and a process in science? What can be meant by a non-social process? In which sense a non-social process can be a part of a scientific process in social science? We are specifically interested in social processes. Our answers use the notion of the generalized subset relation applied to set-theoretical structures, and the set of structuralistically reconstructed empirical theories.

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Notes

  1. This means that we do not reserve the term ‘science’ to the natural sciences, as this is done in the Americas. For this narrow referent, we will always use the term ‘natural science(s)’.

  2. The term ‘theory of science’ is only known in the German language (‘Wissenschaftstheorie’). In German-speaking regions, this term is firmly established.

  3. We cannot discuss here the differences.

  4. See Balzer et al. (1987, Chap. 1.2).

  5. In Balzer (1985) a variant, heretical to ZF, was used.

  6. As an example we describe the potential models and the ECSs of the theory of classical collision mechanics CCM (Balzer et al. 1987, Chap. III.1) in a semi-formal and very brief way in the "Appendix".

  7. Ulises Moulines (personal communication) argued that the notion of cause just can be omitted structuralistically without loss. At the moment, we, the authors, are undecided.

  8. For instance Rott (2006), Salmon (1984), Suppes (1970).

  9. Westermann (2000), see in Balzer et al. (2000).

  10. See, for instance, Wooldridge and Jennings (1999), Wooldridge (2009).

  11. Balzer et al. (1987, Chap. VII).

  12. Balzer and Zoubek (1994).

References

  • Balzer, W. (1985). Theorie und Messung. Berlin: Springer.

    Book  Google Scholar 

  • Balzer, W., & Manhart, K. (2011). A social process in science and its content in a simulation programm. Journal of Artificial Societies and Social Simulation, 14(4).

  • Balzer, W., Moulines, C. U., & Sneed, J. D. (1987). An architectonic for science. Dordrecht: Reidel.

    Book  Google Scholar 

  • Balzer, W., Lauth, B., & Zoubek, G. (1993). A model for science kinematics. Studia Logica, 52, 519—548.

    Article  Google Scholar 

  • Balzer, W., Sneed, J. D., & Moulines, C. U. (eds.) (2000). Structuralist knowledge representation—paradigmatic examples. Poznan studies in the philosophy of the sciences and humanities, Vol. 75. Amsterdam: Atlanta.

    Google Scholar 

  • Balzer, W., & Zoubek, G. (1994). Structuralist aspects of idealization. In: Kuokkanen, M. (ed.) Idealization VII: Structuralism, idealization and approximation. Poznan studies in the philosophy of the sciences and the humanities, Vol. 42 (pp. 57–79). Amsterdam: Rodopi.

  • Beth, E. W. (1948/49). Analyse Sémantique des théories physiques. Synthese, 7(3), 206–207.

    Google Scholar 

  • Bloor, D. (1996). Scientific knowledge. Chicago: University of Chicago Press.

    Google Scholar 

  • Bourbaki, N. (2004). Theory of sets. Berlin: Springer (first printing of the softcover edition: 1968).

  • Burt, R. S. (1982). Toward a structural theory of action. Network models of social structure, perception, and action. New York: Academic Press.

    Google Scholar 

  • Coldony, R. G. (ed.) (1972). Paradigms and paradoxes. Pittsburgh, PA: University of Pittsburgh Press.

    Google Scholar 

  • Diederich, W., Ibarra, A., & Mormann, T. (1989). Bibliography of structuralism 1971–1988. Erkenntnis, 30, 387–407.

    Article  Google Scholar 

  • Diederich, W., Ibarra, A., & Mormann, T. (1994). Bibliography of structuralism II 1989–1994 and additions. Erkenntnis, 41, 403–418.

    Article  Google Scholar 

  • Gärdenfors, P. (1990). Induction, conceptual spaces and AI. Philosophy of Science, 57, 78–95.

    Article  Google Scholar 

  • Gärdenfors, P. (2000). Conceptual spaces. Cambridge, MA: MIT Press.

    Google Scholar 

  • Genesereth, M. R., & Ketchpel, S. P. (1994). Software agents. Communications of the ACM, 37, 48–53.

    Article  Google Scholar 

  • Giere, R. (1988). Explaining science. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • González-Ruiz, A. (1998). Die Netzwerktheorie der Handlung von R. S. Burt: Eine strukturelle und epistemologische Analyse. Frankfurt/M: Peter Lang.

    Google Scholar 

  • Krantz, D. H., Luce, R. D., Suppes, P., & Tversky, A. (1971). Foundations of measurement, Vol. 1. New York.

  • Krohn, W., & Küppers, G. (1987). Die Selbstorganisation der Wissenschaft. Wissenschaftsforschung, Report 33, Bielefeld.

  • Lauth, B. (2002). Transtheoretical structures and deterministic models. Synthese, 130, 163–172.

    Article  Google Scholar 

  • Ludwig, G. (1991). Die Grundstrukturen einer physikalischen Theorie. Berlin: Springer. (1. ed. 1978).

  • Rott, H. (2006). Revision by comparison as a unifying framework: Severe withdrawal, irrevocable revision and irrefutable revision. Theoretical Computer Science, 355(2), 228–242.

    Article  Google Scholar 

  • Salmon, W. (1984). Explanation and the causal structure of the world. Princeton.

  • Searle, J. R. (1995). The construction of social reality. London: Free Press.

    Google Scholar 

  • Suppes, P. (1970). A probabilistic theory of causality. Amsterdam.

  • van Fraassen, B. C. (1970). On the extension of Beth’s semantics of physical theories. Philosophy of Science, 37, 325–339.

    Article  Google Scholar 

  • Westermann, R. (2000). Festinger’s theory of cognitive dissonance: A structuralist theory-net. In W. Balzer, J. D. Sneed, C. U. Moulines (Eds.), Structuralist knowledge representation—paradigmatic examples. Poznan studies in the philosophy of the sciences and humanities, Vol. 75 (pp. 189–217). Amsterdam: Atlanta.

  • Wooldridge, M. (2009). An introduction to multiagent systems (2nd ed.). Chichester: Wiley.

    Google Scholar 

  • Wooldridge, M., & Jennings, N. R. (1999). The cooperation problem—solving process. Journal of Logic and Computation, 9(4), 563–592.

    Article  Google Scholar 

  • Woolgar, S. (1981). Interests and explanation in the social study of science. Social Studies of Science, 11, 365–394.

    Article  Google Scholar 

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Correspondence to Wolfgang Balzer.

Appendix

Appendix

x is a potential model of collision mechanics (\(x \in M_{p}({\bf CCM})\)) iff x has the form \(\langle P,T,\hbox{I}{\bf R},v,m \rangle\), and (1) P is a set (of particles), (2) T is a set (of points of time), (3) IR is the set of real numbers, (4) \(v: P \times T \rightarrow \hbox{I}{\bf R}^{3}\) is a function (the velocity function) and (5) \(m: P \rightarrow \hbox{I}{\bf R}\) is a function (the mass function).

Omitting formal details, we define three ECSs τ1, τ2, τ3 for the base sets and auxiliary sets for CCM as follows. τ1(P, T, IR) = P, τ2(P, T, IR) = T, and τ3(P, T, IR) = IR. We define two ECSs for the base relations for CCM as follows. \(v \in \tau_{4}(P,T,\, \hbox{I}{\bf R}) = \wp (P \times T \times \hbox{I}{\bf R}^{3})\) and \(m \in \tau_{5}(P,T,\hbox{I}{\bf R}) = \wp (P \times T \times \hbox{I}{\bf R})\).

The formal expression \(\langle p,t,\alpha_{1},\alpha_{2},\alpha_{3} \rangle \in v\) says that \(\langle \alpha_{1},\alpha_{2},\alpha_{3} \rangle\) is the function value of \(v: v(p,t) = \langle \alpha_{1},\alpha_{2},\alpha_{3} \rangle\), and \(\langle p, \alpha \rangle \in m\) says: m(p) = α.

  • D1 Let \(x = \langle D_{1},\ldots,D_{m},R_{1},\ldots,R_{n} \rangle \in M_{p}\) be a potential model of T typified by the list \(\langle \tau_{1},\ldots,\tau_{m},\tau_{m+1},\ldots,\tau_{m+n} \rangle\) of basic ECSs.

    1. a.

      y is a structure of states in x typified by a state signature \(\langle \tau_{1}^{\prime},\ldots,\tau_{t}^{\prime},\tau_{t+1}^{\prime},\ldots,\tau_{t+u}^{\prime} \rangle\) iff there exist \(D_{1}^{\prime},\ldots,D_{t}^{\prime},R_{1}^{\prime},\ldots,R_{u}^{\prime}\), there exist an injective function \(\xi : \{1,\ldots,t\} \rightarrow \{1,\ldots,m\}\) and there exist an injective function \(\zeta : \{1,\ldots,u\} \rightarrow \{1,\ldots,n\}\) such that the following holds:

      1. 1.

        \(\forall i \leq t \exists a_{i} (a_{i} \in D_{\xi(i)} \wedge D_{i}^{\prime} = \{ a_i \})\)

      2. 2.

        \(\forall j \leq u \exists r_{j} (r_{j} \in R_{\zeta(j)} \wedge R_{j}^{\prime} = \{ r_j \})\)

      3. 3.

        \(\forall j \leq u ( r_{j} \in \tau_{j}^{\prime}(D_{1}^{\prime},\ldots,D_{t}^{\prime}))\)

      4. 4.

        \(y = \langle D_{1}^{\prime},\ldots,D_{t}^{\prime},R_{1}^{\prime},\ldots,R_{u}^{\prime} \rangle\).

    2. b.

      s is a state in x typified by state signature \(\sigma = \langle \tau_{1}^{\prime},\ldots,\tau_{t}^{\prime},\tau_{t+1}^{\prime},\ldots,\tau_{t+u}^{\prime} \rangle\) iff there exists a structure y of states in x typified by σ such that y has the form \(\langle U_{1},\ldots,U_{t+u} \rangle\), and for all ju exists r j such that

      1. 1.

        U t+j  = {r j }, and

      2. 2.

        \(s = \langle r_1,\ldots,r_u \rangle\).

    3. c.

      S(x, σ) is the class of states (or the state space) in x typified by σ.

    4. d.

      S(T) is the class of all possible states in T.

  • D2

    1. a.

      KP is a kind of process iff there exist S, S b , S e and caus such that the following conditions hold:

      1. 1.

        \(KP = \langle S,S_{b},S_{e},caus \rangle\)

      2. 2.

        S is a non-empty set, (a set of states)

      3. 3.

        \(\emptyset \neq S_{b} \subseteq S\) and \(\emptyset \neq S_{e} \subseteq S\), (sets of ‘beginning-’ and ‘end-states’ of processes)

      4. 4.

        \(caus \subseteq S \times S, (caus(s,s^{\prime})\) means: s is a direct cause of \(s^{\prime}\))

      5. 5.

        \(\forall s,s^{\prime}(caus(s,s^{\prime}) \rightarrow s \in S_{b} \wedge s^{\prime} \in S_{e})\)

      6. 6.

        for all \(s,s^{\prime},s_{o}\), if \(s,s^{\prime},s_{o}\) are pairwise different, then \(caus(s,s^{\prime}) \rightarrow \neg (caus(s,s_{o}) \wedge caus(s_o,s^{\prime}))\)

      7. 7.

        \(\forall s,s^{\prime}( (s \neq s^{\prime} \wedge caus(s,s^{\prime})) \rightarrow \neg caus(s^{\prime},s))\).

    2. b.

      p is a process of kind \(\langle S,S_{b},S_{e},caus \rangle\) iff

      1. 1.

        \(\langle S,S_{b},S_{e},caus \rangle\) is a kind of process

      2. 2.

        there exist s b , s e such that

        1. 2.1.

          \(s_{b} \in S_{b}\) and \(s_{e} \in S_{e}\)

        2. 2.2.

          \(\langle s_{b},s_{e} \rangle \in caus\)

        3. 2.3.

          \(p = \langle s_{b},s_{e} \rangle\).

  • D3 Let \(T = \langle \langle M_{p},M,M_{pp},L,\ldots\rangle, A, I \rangle\) be a theory, x a model of M and \(\sigma = \langle \tau^{1},\ldots,\tau^{r} \rangle\) a state signature in T.

    1. a.

      p is a theoretical process in x typified by σ iff there are sets S b , S e , caus and S(x, σ) and the following holds

      1. 1.

        S(x, σ) is a state space for x typified by σ

      2. 2.

        \(\langle S(x,\sigma),S_{b},S_{e},caus \rangle\) is a kind of process

      3. 3.

        p is a process of kind \(\langle S(x,\sigma),S_{b},S_{e},caus \rangle\).

    2. b.

      PC(T) is the class of theoretical processes in T iff \(PC(T) = \{ p / \exists x \in M \exists \sigma \in E(T)^{*}( p\) is a theoretical process in x typified by σ)}.

  • D4 Let T be a theory, \(x= \langle D_{1},\ldots,D_{m},R_{1},\ldots,R_{n} \rangle \in M_{p}\) and let \(\langle \tau_{1},\ldots,\tau_{m+n} \rangle\) be the list of basic ECSs for T.

    1. a.

      \(x^{\prime}\) is a generalized substructure of \(x, x^{\prime} \sqsubseteq x\), iff there are \(D_{1}^{\prime},\ldots,D_{m}^{\prime}, R_{1}^{\prime},\ldots,R_{n}^{\prime}\) such that

      1. 1.

        \(x^{\prime} = \langle D_{1}^{\prime},\ldots,D_{m}^{\prime},R_{1}^{\prime},\ldots,R_{n}^{\prime} \rangle\)

      2. 2.

        \(\forall i \leq m ( D_{i}^{\prime} \subseteq D_i)\)

      3. 3.

        \(\forall j \leq n ( R_{j}^{\prime} \subseteq R_{j} \wedge R_{j}^{\prime} \in \tau_{j}(D_{1}^{\prime},\ldots,D_{m}^{\prime}) )\).

    2. b.

      z is a generalized partial model iff there exist \(y \in M_{pp}\) such that \(z \sqsubseteq y\). The class of generalized partial models is denoted by M gen pp .

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Balzer, W., Manhart, K. Scientific Processes and Social Processes. Erkenn 79 (Suppl 8), 1393–1412 (2014). https://doi.org/10.1007/s10670-013-9574-9

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