Abstract
Some scientists write literary fiction books in their spare time. If these books contain scientific knowledge, literary fiction becomes a mechanism of knowledge transfer. In this case, we could conceptualize literary fiction as non-formal knowledge transfer. We model knowledge transfer via literary fiction as a function of the type of scientist (academic or non-academic) and his/her scientific field. Academic scientists are those employed in academia and public research organizations whereas non-academic scientists are those with a scientific background employed in other sectors. We also distinguish between direct knowledge transfer (the book includes the scientist’s research topics), indirect knowledge transfer (scientific authors talk about their research with cultural agents) and reverse knowledge transfer (cultural agents give scientists ideas for future research). Through mixed-methods research and a sample from Spain, we find that scientific authorship accounts for a considerable percentage of all literary fiction authorship. Academic scientists do not transfer knowledge directly so often as non-academic scientists, but the former engage into indirect and reverse transfer knowledge more often than the latter. Scientists from History stand out in direct knowledge transfer. We draw propositions about the role of the academic logic and scientific field on knowledge transfer via literary fiction. We advance some tentative conclusions regarding the consideration of scientific authorship of literary fiction as a valuable knowledge transfer mechanism.
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Source: Own elaboration based on the Spanish version of Bureau Van Dick’s Orbis, i.e. the Iberian Balance Analysis System (SABI)
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Notes
Notice the use of the word ‘scientists’ instead or ‘researchers’ or other related terms along the paper. In several academic and non-academic fora, we checked that the definition of both terms overlaps. Some experts consider that researchers can be scientists (scientific researchers) or not (researchers that do not follow the scientific method). Some others consider that scientists can be researchers (professional scientists) or not (anyone who follows a systematic way to increase understanding). Dictionaries are not much helpful, either. For instance, according to the Cambridge Dictionary, a researcher is someone engaged into the ‘study of a subject in order to discover new information’; a scientist is ‘someone who studies science or works in science’, being science ‘knowledge gained by observation and experiment’. We do not appreciate strong differences between the two terms, but we prefer ‘scientist’ because of its connotations (‘passionate with what he/she does’, ‘motivated for the sake of knowledge’), which are slightly more positive than those of ‘researcher’. Despite claims that Arts and Humanities are not science, we include scholars in these disciplines among scientists (we also considered the term ‘scholar’, but its definition according to the Cambridge Dictionary is ‘a person of great knowledge and learning’, which does not provide clearer cut points either).
We consider literary fiction as the narrative forms of literature, i.e. novels, short stories, plays; thus leaving aside poetry or literary essay.
In the field of Educational Sciences, the distinction between formal, informal and non-formal learning or education is common (Colardyn and Bjornavold 2004). It has been our source of inspiration to propose the term and definition of ‘non-formal knowledge transfer’.
We have also generated a variable on contextual knowledge transfer, i.e. whether in fiction works the action occurs in a scientific setting, prominent characters are scientists, etc., but we left it out of the analyses for simplification.
We made this distinction within Humanities because of the large number of authors that belonged to Linguistics and Literature, and for the unusual patterns of knowledge transfer in Linguistics and Literature coming out of the interviews (see Sect. 4.2.2).
As deducible from historical examples in Sect. 3, we have included deceased writers in the sample. This was important conceptually to show the prevalence of the phenomenon of scientific writers. However, there are not many deceased writers (9%) and their inclusion does not condition the results. When we include a dummy for deceased authors or remove them from the sample, the sign and significance of all coefficients hold.
Actually, let us recall, as in a previous footnote, that Academic Scientist 10 joined academia after having written the novel.
https://biblioteca.ucm.es/escritores/ [last access 20/10/2016].
References
Ayoub, M. R., Gottschalk, S., & Müller, B. (2016). Impact of public seed-funding on academic spin-offs. The Journal of Technology Transfer, online first.
Azagra-Caro, J. M., Aznar-Marquez, J., & Blanco, J. M. (2008). Interactive vs. non-interactive knowledge production by faculty members. Applied Economics,40(10), 1289–1297.
Baccini, A., Barabesi, L., Cioni, M., & Pisani, C. (2014). Crossing the hurdle: the determinants of individual scientific performance. Scientometrics,101(3), 2035–2062.
Banou, C. (2013). The organization of book-publishing houses in a changing era. Logos,24(1), 30–40.
Barbieri, E., Rubini, L., Pollio, C., & Micozzi, A. (2016). What are the trade-offs of academic entrepreneurship? An investigation on the Italian case. The Journal of Technology Transfer, online first.
Benneworth, P. (2014). Tracing how the arts and humanities research translates, circulates and consolidates in society. How have scholars been reacting to diverse impact and public value agendas? Arts and Humanities Higher Education,14(1), 45–60.
Benneworth, P., Charles, D., & Madanipour, A. (2010). Building localized interactions between universities and cities through university spatial development. European Planning Studies,18(10), 1611–1629.
Bercovitz, J., & Feldman, M. (2006). Entrepreneurial universities and technology transfer: A conceptual framework for understanding knowledge-based economic development. The Journal of Technology Transfer,31(1), 175–188.
Bradley, S. R., Hayter, C. S., & Link, A. (2013). Models and methods of university technology transfer. Foundations and Trends in Entrepreneurship,9(6), 571–650.
Breznitz, S. M., & Feldman, M. P. (2010). The engaged university. The Journal of Technology Transfer,37(2), 139–157.
Carayol, N., & Matt, M. (2006). Individual and collective determinants of academic scientists’ productivity. Information Economics and Policy,18(1), 55–72.
Cassity, E., & Ang, I. (2006). Humanities-industry partnerships and the ‘Knowledge Society’: The Australian experience. Minerva,44(1), 47–63.
Chang, Y. C., Yang, P. Y., Martin, B. R., Chi, H. R., & Tsai-Lin, T. F. (2016). Entrepreneurial universities and research ambidexterity: A multilevel analysis. Technovation,54, 7–21.
Colardyn, D., & Bjornavold, J. (2004). Validation of formal, non-formal and informal learning: Policy and practices in EU member states. European Journal of Education,39(1), 69–89.
Crozier, W. R. (1999). Age and individual differences in artistic productivity: Trends within a sample of British novelists. Creativity Research Journal,12(3), 197–204.
D’Este, P., & Patel, P. (2007). University–industry linkages in the UK: What are the factors underlying the variety of interactions with industry? Research Policy,36(9), 1295–1313.
Deb, S. (2017). Trump proposes eliminating the Arts and Humanities endowments. The New York Times, Retrieved from: https://www.nytimes.com/2017/03/15/arts/nea-neh-endowments-trump.html
Ehlenz, M. M. (2015). Neighborhood Revitalization and the Anchor Institution Assessing the Impact of the University of Pennsylvania’s West Philadelphia Initiatives on University City. Urban Affairs Review, 1078087415601220.
Fähnrich, B. (2015). Science diplomacy: Investigating the perspective of scholars on politics–science collaboration in international affairs. Public Understanding of Science, 0963662515616552.
Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic creativity. Personality and social psychology review,2(4), 290–309.
Fier, H., & Pyka, A. (2014). Against the one-way-street: analyzing knowledge transfer from industry to science. The Journal of Technology Transfer,39(2), 219–246.
Florida, R. (2005). Cities and the creative class. London: Routledge.
Goddard, J. (2009). Re-inventing the civic university. London: NESTA.
Gorraiz, J., Purnell, P. J., & Glänzel, W. (2013). Opportunities for and limitations of the Book Citation Index. Journal of the American Society for Information Science and Technology,64(7), 1388–1398.
Lam, A. (2011). What motivates academic scientists to engage in research commercialization: ‘Gold’, ‘ribbon’ or ‘puzzle’? Research Policy,40(10), 1354–1368.
Landry, R., Amara, N., & Ouimet, M. (2006). Determinants of knowledge transfer: evidence from Canadian university researchers in Natural Sciences and engineering. The Journal of Technology Transfer,32(6), 561–592.
Link, A. N., Siegel, D. S., & Bozeman, B. (2007). An empirical analysis of the propensity of academics to engage in informal university technology transfer. Industrial and Corporate Change,16(4), 641–655.
Madjar, N. (2008). Emotional and informational support from different sources and employee creativity. Journal of Occupational and Organizational Psychology,81(1), 83–100.
MarketLine. (2016). MarketLine Industry Profile: Global Publishing. Rockville: MarketLine, www.marketline.com. Accessed May 28, 2017.
McCrae, R. R., & Sutin, A. R. (2009). Openness to experience. Handbook of Individual Differences in Social Behavior,15, 257–273.
Molas-Gallart, J., & Tang, P. (2011). Tracing ‘productive interactions’ to identify social impacts: An example from the Social Sciences. Research Evaluation,20(3), 219–226.
Nederhof, A. J. (2006). Bibliometric monitoring of research performance in the Social Sciences and the Humanities: A Review. Scientometrics,66(1), 81–100.
OECD. (2000). Knowledge management in the learning society. Paris: Organisation for Economic Co-Operation and Development.
OECD. (2007). Revised fields of science and technology. Paris: Organisation for Economic Co-operation and Development.
Olmos-Peñuela, J., Benneworth, P., & Castro-Martínez, E. (2015). What stimulates researchers to make their research usable? Towards an ‘openness’ approach. Minerva,53(4), 381–410.
Olmos-Peñuela, J., Castro-Martínez, E., & D’Este, P. (2014). Knowledge transfer activities in Social Sciences and humanities: Explaining the interactions of research groups with non-academic agents. Research Policy,43(4), 696–706.
Parker, I. (2015). Podemos as event or not: what it looks like from Manchester. Teknokultura,12(1), 153–160.
Perkmann, M., King, Z., & Pavelin, S. (2011). Engaging excellence? Effects of faculty quality on university engagement with industry. Research Policy,40(4), 539–552.
Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., et al. (2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research Policy,42(2), 423–442.
Shalley, C. E., Gilson, L. L., & Blum, T. C. (2009). Interactive effects of growth need strength, work context, and job complexity on self-reported creative performance. Academy of Management Journal,52(3), 489–505.
Shehu, E., Prostka, T., Schmidt-Stölting, C., Clement, M., & Blömeke, E. (2014). The influence of book advertising on sales in the German fiction book market. Journal of Cultural Economics,38(2), 109–130.
Smith, H. L., & Bagchi-Sen, S. (2012). The research university, entrepreneurship and regional development: Research propositions and current evidence. Entrepreneurship & Regional Development,24(5–6), 383–404.
Taylor, B. J., Cantwell, B., & Slaughter, S. (2013). Quasi markets in U.S. Higher Education: The humanities and institutional revenues. The Journal of Higher Educations,84(5), 675–707.
Thelwall, M. (2017). Book genre and author gender: Romance > Paranormal-Romance to Autobiography > Memoir. Journal of the Association for Information Science and Technology,68(5), 1212–1223.
Tijssen, R. J. W. (2006). Universities and industrially relevant science: Towards measurement models and indicators of entrepreneurial orientation. Research Policy,35(10), 1569–1585.
Acknowledgements
This research was funded by Project AICO/2016/A/107 of the Valencian Regional Government. Nicolás Robinson-Garcia was supported by a Juan de la Cierva-Formación Fellowship from the Spanish Ministry of Economy and Competitiveness. We are indebted to Pablo Marín Liébana (supported by CSIC’s Fellowship JAE-INT 16/00455) for his work in the database, conducting interviews and sharing ideas, and to the authors interviewed for their patience and generosity. Some of them informed about their consent to be mentioned by name: Sergio R. Alarte (‘Tormentas de verano’), María Ángeles Chavarría (‘Mi otro yo’), Juan Pablo Heras (‘De fábula’), Xavier Minguez (‘Flor de carxofa’), Lluís Miret (L’ombra del mal’), Javier Navarro (‘Tableaux vivants’) and Fedosy Santaella (‘El dedo de David Lynch’). David Barberá-Tomás, Alejandra Boni, Elena Castro-Martínez and Richard Woolley provided invaluable feedback through informal talks, and other INGENIO colleagues during a seminar presentation. Thanks as well to attendants to the presentations of the paper at the 2016 Science and Technology Indicators Conference, the 2016 Technology Transfer Conference, the 2017 Bologna Workshop ‘University-Industry Collaborations and Academic Entrepreneurship’ and the 2017 Druid Conference for their participation and constructive comments, especially to our discussants Dipesh Sigdell, Carmelo Cennamo and Juan Antonio Candiani.
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Azagra-Caro, J.M., Fernández-Mesa, A. & Robinson-García, N. ‘Getting out of the closet’: scientific authorship of literary fiction and knowledge transfer. J Technol Transf 45, 56–85 (2020). https://doi.org/10.1007/s10961-018-9672-6
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DOI: https://doi.org/10.1007/s10961-018-9672-6