Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-27T01:19:45.508Z Has data issue: false hasContentIssue false

Tradition–invention dichotomy and optimization in the field of science

Published online by Cambridge University Press:  10 November 2022

Mukta Watve
Affiliation:
Independent Researchers, Pune 411052, India [email protected] [email protected]://milindwatve.in/
Milind Watve
Affiliation:
Independent Researchers, Pune 411052, India [email protected] [email protected]://milindwatve.in/

Abstract

The central idea of the bifocal stance theory (BST) by Jagiello et al. has substantial relevance to scientific research. Both tradition-following and exploration-innovation are important in science and researchers subconsciously try to optimize their strategies. We outline three important dimensions of this optimization and argue that attempts to understand this complex process can help us design better science education, research training, investigation, and science publication.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Beaty, R. E., Kenett, Y. N., Christensen, A. P., Rosenberg, M. D., Benedek, M., Chen, Q., … Silvia, P. J. (2018). Robust prediction of individual creative ability from brain functional connectivity. Proceedings of the National Academy of Sciences of the United States of America, 115(5), 10871092. https://doi.org/10.1073/pnas.1713532115CrossRefGoogle ScholarPubMed
Biro, D., Inoue-Nakamura, N., Tonooka, R., Yamakoshi, G., Sousa, C., & Matsuzawa, T. (2003). Cultural innovation and transmission of tool use in wild chimpanzees: Evidence from field experiments. Animal Cognition, 6(4), 213223. https://doi.org/10.1007/s10071-003-0183-xCrossRefGoogle ScholarPubMed
Boogert, N. J., Reader, S. M., & Laland, K. N. (2006). The relation between social rank, neophobia and individual learning in starlings. Animal Behaviour, 72(6), 12291239. https://doi.org/10.1016/j.anbehav.2006.02.021CrossRefGoogle Scholar
Chapman, C. A., Bicca-Marques, J. C., Calvignac-Spencer, S., Fan, P., Fashing, P. J., Gogarten, J., … Stenseth, N. C. (2019). Games academics play and their consequences: How authorship, h-index and journal impact factors are shaping the future of academia. Proceedings of the Royal Society B: Biological Sciences, 286(1916), 20192047. https://doi.org/10.1098/rspb.2019.2047CrossRefGoogle ScholarPubMed
Coussi-Korbel, S., & Fragaszy, D. M. (1995). On the relation between social dynamics and social learning. Animal Behaviour, 50(6), 14411453. https://doi.org/10.1016/0003-3472(95)80001-8CrossRefGoogle Scholar
Federspiel, I. G., Boeckle, M., von Bayern, A. M. P., & Emery, N. J. (2019). Exploring individual and social learning in jackdaws (Corvus monedula). Learning and Behavior, 47(3), 258270. https://doi.org/10.3758/s13420-019-00383-8CrossRefGoogle Scholar
Germar, M., Albrecht, T., Voss, A., & Mojzisch, A. (2016). Social conformity is due to biased stimulus processing: Electrophysiological and diffusion analyses. Social Cognitive and Affective Neuroscience, 11(9), 14491459.CrossRefGoogle ScholarPubMed
Jones, N. A. R., Spence-Jones, H. C., Webster, M., & Rendell, L. (2021). Individual behavioural traits not social context affects learning about novel objects in archerfish. Behavioral Ecology and Sociobiology, 75(3), 58. https://doi.org/10.1007/s00265-021-02996-4CrossRefGoogle Scholar
Kendal, R., Hopper, L. M., Whiten, A., Brosnan, S. F., Lambeth, S. P., Schapiro, S. J., & Hoppitt, W. (2015). Chimpanzees copy dominant and knowledgeable individuals: Implications for cultural diversity. Evolution and Human Behavior, 36(1), 6572. https://doi.org/10.1016/j.evolhumbehav.2014.09.002CrossRefGoogle ScholarPubMed
Kendal, R. L., Coolen, I., van Bergen, Y., & Laland, K. N. (2005). Trade-offs in the adaptive use of social and asocial learning. Advances in the Study of Behavior, 35(05), 333379. https://doi.org/10.1016/S0065-3454(05)35008-XCrossRefGoogle Scholar
Kuhn, T. (2020). The structure of scientific revolutions Vol I and II. University of Chicago Press (1962, 1970).Google Scholar
Laland, K. N. (2004). Social learning strategies. Learning and Behavior, 32(1), 414. https://doi.org/10.1109/COGINF.2005.1532634CrossRefGoogle ScholarPubMed
Morgan, T. J. H., Laland, K. N., Biele, G., Yoon, C., & Burke, C. J. (2012). The biological bases of conformity. Frontiers in Neuroscience, 6, 87. https://doi.org/10.3389/fnins.2012.00087CrossRefGoogle ScholarPubMed
Padalia, D. (2014). Conformity bias: A fact or an experimental artifact? Psychological Studies, 59(3), 223230. https://doi.org/10.1007/s12646-014-0272-8CrossRefGoogle Scholar
Sasaki, T., & Okada, I. (2015). Cheating is evolutionarily assimilated with cooperation in the continuous snowdrift game. BioSystems, 131, 5159. https://doi.org/10.1016/j.biosystems.2015.04.002CrossRefGoogle ScholarPubMed
Tröhler, U. (2005). Lind and scurvy: 1747 to 1795. Journal of the Royal Society of Medicine, 98(11), 519522. https://doi.org/10.1258/jrsm.98.11.519CrossRefGoogle ScholarPubMed
Watve, M. (2017). Social behavioural epistemology and the scientific community. Journal of Genetics, 96(3), 525533. https://doi.org/10.1007/s12041-017-0790-yCrossRefGoogle ScholarPubMed
Watve, M. (2019). The evolutionary psychology of scientific publishing: Cost–benefit optimization of players in the game. https://doi.org/10.32942/osf.io/nvpe2.CrossRefGoogle Scholar
Weatherall, J. O., & O'Connor, C. (2021). Conformity in scientific networks. Synthese, 198, 72577278. https://doi.org/10.1007/s11229-019-02520-2CrossRefGoogle Scholar