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How to stimulate scientific creativity through funding Wolfgang Stroebe.

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Presentation on theme: "How to stimulate scientific creativity through funding Wolfgang Stroebe."— Presentation transcript:

1 How to stimulate scientific creativity through funding Wolfgang Stroebe

2 NWO NWO: Vernieuwing en kwaliteit. Dat zijn de speerpunten waarmee NWO werkt aan de toekomst van de wetenschap in Nederland Vernieuwingsimpuls: Veni, Vidi, Vici Aanvragers: Veni: pasgepromoveerd Vidi: maximaal 8 jaar geleden gepromoveerd Vici: maximaal 15 jaar geleden gepromoveerd, en/of maximaal 3 jaar geleden benoemd tot hoogleraar

3 Thus, if you are over 40, you have had it, since there is very little money in the open competition If you are very successful and get a chair early, you have had it even earlier So why not get money from your own university?

4 Utrecht University Requirements for high potential grants: You must not be a professor You must collaborate interdisciplinary

5 Factors likely to increase scientific creativity? Thus, the assumption guiding funding agencies seems to be that to be creative, you have to be young and you have to collaborate with colleagues from other disciplines. The question I want to address in my talk is whether funding nearly exclusively the young, and in addition forcing them into interdisciplinary collaboration really increases scientific creativity

6 How to measure scientific creativity Number of publication and number of citations Simonton (1997) “Quality is.. a probabilistic function of quantity” In Psychology the following holds (Simonton, e.g., Psych Rev. 1997): # Publications (r =.47} # Citations (r =.67} with Eminence as rated by experts Citations help to predict future Nobel price winners Eminence in 1903 correlated. 73 with posthumous citation in 1966-70

7 Who is creative? Price (1963) law: If k = number of people active in a field Square root of k = number of people who account for half of everything produced In any field, one tenth of the scientists produce roughly half of all the work

8 Productivity Distribution for Psychologists (Simonton, 2002, p. 41)

9 Citations 299 Australian academic psychologists studied in 1970-1975 (White & White, 1978) Top 10% in output 36% of all publications 60% of total citations 196 American academic psychologists (Helmreich et al., 1980) 11% no citations in 3 years 25% 2 or fewers in 3 years 10% more than 50 citations per year Thus, the eminent minority does not only publish a lot, they also account for most of the citations

10 Age and scientific producitivity in six fields (Cole, AJS, 1979)

11 Age and scientific productivity Relationship curvilinear Peak around age 40 However, age accounts for little variance in productivity (6-7%)

12 Age and resistance to new ideas Planck’s principle: “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.” Huxley: ”Men of science should be strangled on their 60th birthday, lest they retard scientific progress.” “No researcher to date has found substantial effects of age on acceptance of new ideas” (Levin et al., 1995, Social Studies of Science, p. 281)

13 Is past performance the best predictor? Lifetime-stability of scientific productivity

14 Correlation for number of publications published by cohort of mathematicians during different time periods (Cole, 1979) 1950-541955-591960-641965-691970-74 1950—54.68.62.61.63 1955-59.72.74.71 1960-64.74.73 1965-69.79 1970-74

15 Causes of stability Environmental: The cumulative advantage or Mathew effect (according to the Gospel of St. Mathew) : “For onto everyone that hath shall be given, and he shall have abundance: but from him that hath not shall be taken away even that which he hath”

16 The cause of stability: individual differences in creative potential Individuals begin their career with a certain amount of “initial creative potential”, which determines their later productivity (Simonton, 2002)

17 If the cumulative advantage model is correct, then individual differences in output should correlate far higher for two consecutive age period than for two nonconsecutive age periods. If variation in productivity is a function of some latent variable (i.e., creative potential), correlations should be of roughly equal magnitude, regardless of to distance between age periods. All evidence supports the individual difference assumption (e.g., the data of Cole, 1979)

18 Conclusions for funding The implications of the individual difference model are that only funding individuals with creative potential will result in creative research The best predictor of creative potential is track record Track record in later career phases is a better predictor of future output Obviously, one should give money to promising young scientists to get them started With only 6-8% of productivity predicted by age and the remainder by track record, you destroy a lot of creative potential by restricting funding to the young

19 Interdisciplinary collaboration Does inducing researchers to collaborate interdisciplinary increase scientific creativity? Why should it?

20 A three component theory of creativity (Amabile, 1996) Creativity is a function of Domain-relevant skills Creativity-relevant processes Motivation

21 Potential effects of interdisciplinary collaboration Discourse among researchers from different disciplines might help them to break the mold of their old disciplinary problems-solving strategies and motivat innovative new strategies Barriers: External pressure ruins intrinsic motivation Division of labor between disciplines reduces interactions

22 When is interdisciplinary research unlikely to stimulate creativity? Externally motivated Pressure to create output Utilitarian motives (e.g., to access techonology or patient samples) Great discrepancy in approaches

23 When is it likely to stimulate creativity Collaboration is intrinsically motivated No immediate pressure to create output Similar methodological approach Disciplines study the same concepts from different perspectives (e.g., economics and social psychology)

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