Can the Socio-Cognitive Process of Science be Simulated?

1. Can the Socio-Cognitive Process of Science be Simulated? Loet Leydesdorff University of Amsterdam, Amsterdam School of Communication Research (ASCoR) loet@leydesdorff.net

2. Context of Justification (Popper) Intellectual Organization of the Sciences (Whitley) knowledge claims validation Contexts of Discursive Mediation Context of Discovery; Social Organization of the Sciences

3. Content; theories Philosophy of science;artificial intelligence selection Sociology of science Texts; journals knowledge claims; variation Scientometrics People; institutions

4. Discursive knowledge is developed in communications  codified knowledge • Reflected in texts  potentially entertained by agency • Reproduced in terms of knowledge claims An order of expectations

5. Proceed to the simulation • Computation of Anticipatory Systems - weak versus strong anticipation - incursive and hyper-incursive (Daniel Dubois; Sander Franse) • Potential Generation of Negative Entropy in Triple-Helix Relation (Klaus Krippendorff; Inga Ivanova)

6. Example: The logistic curve recursive: x(t) = ax(t -1) [1 – x(t -1)] incursive: x(t) = ax(t -1) [1 – x(t)] hyper-incursive: x(t) = a x(t +1) [1 – x(t +1)] Example of an incursive system: Technologies develop historically with reference to their previous state; but are selected on the market in the present

8. xt+1 = ½ ± ½ √[1 – (4/a) xt]

9. xt+1 = ½ ± ½ √[1 – (4/a) xt] NetSci07

10. simulation Interaction of meaning: one interface Self-organization of meaning two anticipatory interfaces simulation Organization of meaning one anticipatory interface and a historical retention mechanism simulation

11. Relation to the measurement ? • The three-dimensions of the measurement in a Triple Helix configuration: •  eight (= 23) discrete values

12. at http://www.leydesdorff.net/th local

13. Mutual Information:Tij = Hi + Hj - HijTij≥ 0; always positive Configurational Information: TUIG = HU + HI + HG – HUI – HIG – HUG + HUIG TUIG is potentiallynegative (cf. spurious correlation)

14. time time

16. Krippendorff, K. (2009). W. Ross Ashby’s information theory: a bit of history, some solutions to problems, and what we face today. International Journal of General Systems, 38(2), 189-212.

17. Statistics Sweden: N = 1,187,421; November 2011  48.5% of the regional synergy is provided by the three metropolitan areas of Stockholm, Gothenburg, and Malmö/Lund. (with Øivind Strand,) The Swedish System of Innovation: Regional Synergies in a Knowledge-Based Economy, Journal of the American Society for Information Science and Technology (in press).

18. Figure: The distribution of 339 second-level administrative units in the PRC compared in terms of their contribution to the synergy among technology, geography, and organization.

19. Count the overlaps twice (or more)  mutual redundancy 

20. Mutual Redundancy in Two Dimensions  R12 = – T12

21. Source: Brooks & Wiley (1986: 43).

22. Weaver (1949, p. 26): “Similarly one can imagine another box in the diagram which, inserted between the information source and the transmitter, would be labeled “semantic noise,” the box previously labeled as simply “noise” now being labeled “engineering noise.” Codes of communication Codes of communication SEMANTIC NOISE SEMANTIC NOISE

23. ;

24. Figure 3: Rotation of the two vectors P and Q for the first component (U = 1) and the consequent development of the contribution of this component to the redundancy R1 (= P12 – Q12).

25. Figure 6: Three components in the generation of redundancy with noise in the fuzzy interval of (0, 3π/2r) added to the third component Rf3: initial values as in Figure 3.

26. simulation • Figure 7: Summation of the three components R123 ( ) = -3.82 with and without noise in the fuzzy interval of (0, 3π/2r); the coupling coefficient g = 0.2; initial values as in Figure 3.

27. REFERENCES: • Ivanova, I. A., & Leydesdorff, L. (2014, in press). Redundancy Generation in University-Industry-Government Relations: The Triple Helix Modeled, Measured, and Simulated. Scientometrics. doi: 10.1007/s11192-014-1241-7; http://www.leydesdorff.net/redundancy/figures.xlsx • Leydesdorff, L., & Ivanova, I. A. (2014). Mutual Redundancies in Inter-human Communication Systems: Steps Towards a Calculus of Processing Meaning. Journal of the Association for Information Science and Technology, 65(2), 386-399. • Leydesdorff, L., Johnson, M., & Ivanova, I. A. (2014; in press). The Communication of Expectations and Individual Understanding: Redundancy as Reduction of Uncertainty, and the Processing of Meaning. Kybernetes. • Ivanova, I. A., & Leydesdorff, L. (2013, in press). Rotational symmetry and the transformation of innovation systems in a Triple Helix of university–industry–government relations. Technological Forecasting and Social Change. doi: 10.1016/j.techfore.2013.08.022.

28. Conclusions • The scientific model (or paradigm) operates as a system of rationalized (that is, codified) expectations; • Codified knowledge can be considered as “a meaning that makes a difference”; • The only system that can be reconstructed in terms of expectations (counter-factually) is the social system of communications; • This generates redundancies; other options; • The mechanism of generating redundancy is further codified in scientific communication.