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Modelling Scientific Communities

Published online by Cambridge University Press:  30 November 2023

Cailin O'Connor
Affiliation:
University of California, Irvine

Summary

This Element will overview research using models to understand scientific practice. Models are useful for reasoning about groups and processes that are complicated and distributed across time and space, i.e., those that are difficult to study using empirical methods alone. Science fits this picture. For this reason, it is no surprise that researchers have turned to models over the last few decades to study various features of science. The different sections of the element are mostly organized around different modeling approaches. The models described in this element sometimes yield take-aways that are straightforward, and at other times more nuanced. The Element ultimately argues that while these models are epistemically useful, the best way to employ most of them to understand and improve science is in combination with empirical methods and other sorts of theorizing.
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Online ISBN: 9781009359535
Publisher: Cambridge University Press
Print publication: 21 December 2023

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References

Akerlof, George A and Michaillat, Pascal (2018). “Persistence of false paradigms in low-power sciences.” Proceedings of the National Academy of Sciences, 115(52), 1322813233.CrossRefGoogle ScholarPubMed
Alexander, Diane, Gorelkina, Olga, and Hengel, Erin (2021). “ Gender and the time cost of peer review.” Working Paper.Google Scholar
Alexander, Jason McKenzie, Himmelreich, Johannes, and Thompson, Christopher (2015). “Epistemic landscapes, optimal search, and the division of cognitive labor.” Philosophy of Science, 82(3), 424453.CrossRefGoogle Scholar
Allen, Christopher and Mehler, David MA (2019). “Open science challenges, benefits and tips in early career and beyond.” Public Library of Science Biology, 17(5), e3000246.Google ScholarPubMed
Anderson, Katharine A (2016). “A model of collaboration network formation with heterogeneous skills.” Network Science, 4(2), 188215.CrossRefGoogle Scholar
Arvan, Marcus, Kofi Bright, Liam, and Heesen, Remco (2020). “Jury theorems for peer review.” The British Journal for the Philosophy of Science. https://doi.org/10.1086/719117.Google Scholar
Avin, Shahar (2015). “Funding science by lottery.” Recent Developments in the Philosophy of Science: EPSA13 Helsinki. Springer, 111126.CrossRefGoogle Scholar
Avin, Shahar (2019). “Centralized funding and epistemic exploration.” The British Journal for the Philosophy of Science, 70(3), 629656.CrossRefGoogle Scholar
Azar, Ofer H (2005). “The review process in economics: Is it too fast?Southern Economic Journal, 72(2), 482491.Google Scholar
Baker, Monya (2016). “1,500 scientists lift the lid on reproducibility.” Nature News, 533(7604), 452.CrossRefGoogle Scholar
Bala, Venkatesh and Goyal, Sanjeev (1998). “Learning from neighbours.” The Review of Economic Studies, 65(3), 595621.CrossRefGoogle Scholar
Balietti, Stefano, Mäs, Michael, and Helbing, Dirk (2015). “On disciplinary fragmentation and scientific progress.” Public Library of Science One, 10(3), e0118747.Google ScholarPubMed
Banerjee, Siddhartha, Goel, Ashish, and Kollagunta Krishnaswamy, Anilesh (2014). “Re-incentivizing discovery: Mechanisms for partial-progress sharing in research.” Proceedings of the Fifteenth ACM Conference on Economics and Computation, 149166.Google Scholar
Barabâsi, Albert-Laszlo, Jeong, Hawoong, Néda, Zoltan, et al. (2002). “Evolution of the social network of scientific collaborations.” Physica A: Statistical Mechanics and Its Applications, 311(3–4), 590614.CrossRefGoogle Scholar
Barkoczi, Daniel and Galesic, Mirta (2016). “Social learning strategies modify the effect of network structure on group performance.” Nature Communications, 7(1), 18.CrossRefGoogle ScholarPubMed
Bauchner, Howard, Fontanarosa, Phil B, Flanagin, Annette, and Thornton, Joe (2018). “Scientific misconduct and medical journals.” Jama, 320(19), 19851987.CrossRefGoogle ScholarPubMed
Bedessem, Baptiste (2019). “The division of cognitive labor: Two missing dimensions of the debate.” European Journal for Philosophy of Science, 9(1), 116.CrossRefGoogle Scholar
Begley, C Glenn and Ellis, Lee M (2012). “Raise standards for preclinical cancer research.” Nature, 483(7391), 531533.CrossRefGoogle ScholarPubMed
Bender, Max Ernst, Edwards, Suzanne, von Philipsborn, Peter, et al. (2015). “Using co-authorship networks to map and analyse global neglected tropical disease research with an affiliation to Germany.” Public Library of Science Neglected Tropical Diseases, 9(12), e0004182.CrossRefGoogle ScholarPubMed
Benjamin, Daniel J, Berger, James O, Johannesson, Magnus, et al. (2018). “Redefine statistical significance.” Nature Human Behaviour, 2(1), 610.CrossRefGoogle ScholarPubMed
Bergstrom, Carl T, Foster, Jacob G, and Song, Yangbo (2016). “ Why scientists chase big problems: Individual strategy and social optimality.” ArXiv Preprint ArXiv:1605.05822.Google Scholar
Bird, Alexander (2021). “Understanding the replication crisis as a base rate fallacy.” The British Journal for the Philosophy of Science, 72(4), 965993.CrossRefGoogle Scholar
Boroomand, Amin and Smaldino, Paul E (2021). “Hard work, risk-taking, and diversity in a model of collective problem solving.” Journal of Artificial Societies and Social Simulation, 24(4) 10.CrossRefGoogle Scholar
Boschini, Anne and Sjögren, Anna (2007). “Is team formation gender neutral? Evidence from coauthorship patterns.” Journal of Labor Economics, 25(2), 325365.CrossRefGoogle Scholar
Botts, Tina Fernandes, Kofi Bright, Liam, Cherry, Myisha, Mallarangeng, Guntur, and Spencer, Quayshawn (2014). “What is the state of blacks in philosophy?Critical Philosophy of Race, 2(2), 224242.CrossRefGoogle Scholar
Bourne, Philip E, Polka, Jessica K, Vale, Ronald D, and Kiley, Robert (2017). “Ten simple rules to consider regarding preprint submission.” Public Library of Science Computational Biology, 13, e1005473.Google ScholarPubMed
Boyer, Thomas (2014). “Is a bird in the hand worth two in the bush? Or, whether scientists should publish intermediate results.” Synthese, 191(1), 1735.CrossRefGoogle Scholar
Boyer-Kassem, Thomas and Imbert, Cyrille (2015). “Scientific collaboration: Do two heads need to be more than twice better than one?Philosophy of Science, 82(4), 667688.CrossRefGoogle Scholar
Bright, Liam K (2017a). “Decision theoretic model of the productivity gap.” Erkenntnis, 82(2), 421442.CrossRefGoogle Scholar
Bright, Liam K (2017b). “On fraud.” Philosophical Studies, 174(2), 291310.CrossRefGoogle Scholar
Bright, Liam K (2021). “Why do scientists lie?Royal Institute of Philosophy Supplements, 89, 117129.CrossRefGoogle Scholar
Bright, Liam K, Dang, Haixin, and Heesen, Remco (2018). “A role for judgment aggregation in coauthoring scientific papers.” Erkenntnis, 83(2), 231252.CrossRefGoogle Scholar
Bruner, Justin and O’Connor, Cailin (2017). “Power, bargaining, and collaboration.” In Boyer-Kassem, T., Mayo-Wilson, C., and Weisberg, M. (eds.), Scientific Collaboration and Collective Knowledge. Oxford University Press, 135160.Google Scholar
Bruner, Justin P (2013). “Policing epistemic communities.” Episteme, 10(4), 403416.CrossRefGoogle Scholar
Bruner, Justin P (2019). “Minority (dis) advantage in population games.” Synthese, 196(1), 413427.CrossRefGoogle Scholar
Bruner, Justin P and Holman, Bennett (2019). “Self-correction in science: Meta-analysis, bias and social structure.” Studies in History and Philosophy of Science Part A, 78, 9397.CrossRefGoogle ScholarPubMed
Camerer, Colin F, Dreber, Anna, Holzmeister, Felix, et al. (2018). “Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015.” Nature Human Behaviour, 2(9), 637644.CrossRefGoogle Scholar
Campbell, Donald T (1965). “Variation and selective retention in socio-cultural evolution.” Social Change in Developing Area.Google Scholar
Casadevall, Arturo and Fang, Ferric C (2012). “Reforming science: Methodological and cultural reforms.” Infection and Immunity, 80, 891896.CrossRefGoogle ScholarPubMed
Chambers, Christopher D (2013). “Registered reports: A new publishing initiative at Cortex.” Cortex, 49(3), 609610.CrossRefGoogle ScholarPubMed
Collins, Harry M (1974). “The TEA set: Tacit knowledge and scientific networks.” Science Studies, 4(2), 165185.CrossRefGoogle Scholar
Cotton, Christopher (2013). “Submission fees and response times in academic publishing.” American Economic Review, 103(1), 501509.CrossRefGoogle Scholar
Currie, Adrian (2019). “Existential risk, creativity & well-adapted science.” Studies in History and Philosophy of Science Part A, 76, 3948.CrossRefGoogle ScholarPubMed
Dahlberg, Brett (2018). “Cornell food researcher’s downfall raises larger questions for science.” NPR.Google Scholar
Dasgupta, Partha and David, Paul A (1994). “Toward a new economics of science.” Research Policy, 23(5), 487521.Google Scholar
Dasgupta, Partha and Maskin, Eric (1987). “The simple economics of research portfolios.” The Economic Journal, 97(387), 581595.CrossRefGoogle Scholar
Langhe, De, Rogier, (2014). “A unified model of the division of cognitive labor.” Philosophy of Science, 81(3), 444459.CrossRefGoogle Scholar
de Melo-Martín, , Inmaculadade, and Intemann, Kristen (2018). The fight against doubt: How to bridge the gap between scientists and the public. Oxford University Press.CrossRefGoogle Scholar
Carmen, Del, Alejandro, and Bing, Robert L (2000). “Academic productivity of African Americans in criminology and criminal justice.” Journal of Criminal Justice Education, 11(2), 237249.CrossRefGoogle Scholar
Derex, Maxime, Perreault, Charles, and Boyd, Robert (2018). “Divide and conquer: Intermediate levels of population fragmentation maximize cultural accumulation.” Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1743), 20170062.CrossRefGoogle ScholarPubMed
Devezer, Berna, Nardin, Luis G, Baumgaertner, Bert, and Ozge Buzbas, Erkan (2019). “Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity.” Public Library of Science One, 14(5), e0216125.Google Scholar
Devezer, Berna, Navarro, Danielle J, Vandekerckhove, Joachim, and Ozge Buzbas, Erkan (2021). “The case for formal methodology in scientific reform.” Royal Society Open Science, 8(3), 200805.CrossRefGoogle ScholarPubMed
Dion, Michelle L, Lawrence Sumner, Jane, and McLaughlin Mitchell, Sara (2018). “Gendered citation patterns across political science and social science methodology fields.” Political Analysis, 26(3), 312327.CrossRefGoogle Scholar
Dotson, Kristie (2011). “Tracking epistemic violence, tracking practices of silencing.” Hypatia, 26(2), 236257.CrossRefGoogle Scholar
Douglas, Heather, Elliott, Kevin, Maynard, Andrew, Thompson, Paul, and Whyte, Kyle (2014). “Guidance on Funding from Industry.” SRPoiSE.org. http://srpoise.org/wp-content/uploads/2014/06/Guidance-on-Funding-from-Industry-Final.pdf.Google Scholar
Du Bois, WEB (1898). “The study of the Negro problems.” The Annals of the American Academy of Political and Social Science, 11(1), 123.Google Scholar
Eklund, Anders, Nichols, Thomas E, and Knutsson, Hans (2016). “Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates.” Proceedings of the National Academy of Sciences, 113(28), 79007905.CrossRefGoogle ScholarPubMed
Etzkowitz, Henry, Fuchs, Stephan, Gupta, Namrata, Kemelgor, Carol, and Ranga, Marina (2008). “The coming gender revolution in science.” In Hackett, Edward J., Amsterdamska, Olga, Lynch, Michael, and Wajcman, Judy (eds.), The Handbook of Science and Technology Studies. Cambridge: MIT Press, 403428.Google Scholar
Fanelli, Daniele (2009). “How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data.” Public Library of Science One, 4(5), e5738.Google ScholarPubMed
Fanelli, Daniele (2012). “Negative results are disappearing from most disciplines and countries.” Scientometrics, 90(3), 891904.CrossRefGoogle Scholar
Fang, Christina, Lee, Jeho, and Schilling, Melissa A (2010). “Balancing exploration and exploitation through structural design: The isolation of subgroups and organizational learning.” Organization Science, 21(3), 625642.CrossRefGoogle Scholar
Fazelpour, Sina and Rubin, Hannah (2022). “Diversity and homophily in social networks.” Proceedings of the Annual Meeting of the Cognitive Science Society.Google Scholar
Fazelpour, Sina and Steel, Daniel (2022). “Diversity, trust and conformity: A simulation study.” Philosophy of Science, 89(2), 209231.CrossRefGoogle Scholar
Feldon, David F, Peugh, James, Maher, Michelle A, Roksa, Josipa, and Tofel-Grehl, Colby (2017). “Time-to-credit gender inequities of first-year PhD students in the biological sciences.” CBE Life Sciences Education, 16(1), 19.CrossRefGoogle ScholarPubMed
Ferber, Marianne A and Brün, Michael (2011). “The gender gap in citations: Does it persist?Feminist Economics, 17(1), 151158.CrossRefGoogle Scholar
Ferber, Marianne A and Teiman, Michelle (1980). “Are women economists at a disadvantage in publishing journal articles?Eastern Economic Journal, 6(3/4), 189193.Google Scholar
Frey, Daniel and Šešelja, Dunja (2018). “What is the epistemic function of highly idealized agent-based models of scientific inquiry?Philosophy of the Social Sciences, 48(4), 407433.CrossRefGoogle Scholar
Frey, Daniel and Šešelja, Dunja (2020). “Robustness and idealizations in agent-based models of scientific interaction.” The British Journal for the Philosophy of Science, 71(4), 1411-1437.CrossRefGoogle Scholar
Fricker, Miranda (2007). Epistemic Injustice: Power and the Ethics of Knowing. Oxford University Press.CrossRefGoogle Scholar
Gabriel, Nathan and O’Connor, Cailin (2023). “Can confirmation bias improve group learning? Working Paper.Google Scholar
Gadbury, Gary L and Allison, David B (2012). “Inappropriate fiddling with statistical analyses to obtain a desirable p-value: Tests to detect its presence in published literature.” Plos One, 7(1), e46363.CrossRefGoogle ScholarPubMed
Gelman, Andrew and Loken, Eric (2013). “The garden of forking paths: Why multiple comparisons can be a problem, even when there is no ‘expedition’ or ‘-hacking’ and the research hypothesis was posited ahead of time.Department of Statistics, Columbia University, 348, 117.Google Scholar
Glänzel, Wolfgang and Schubert, András (2004). “Analysing scientific networks through co-authorship.” In Moed, H., Glanzel, W., Smoch, U. (eds.), Handbook of Quantitative Science and Technology Research. Springer, 257276.Google Scholar
Goldman, Alvin I (1999). Knowledge in a Social World. Oxford University Press.CrossRefGoogle Scholar
Goldman, Alvin I and Shaked, Moshe (1991). “An economic model of scientific activity and truth acquisition.” Philosophical Studies: An International Journal for Philosophy in the Analytic Tradition, 63(1), 3155.CrossRefGoogle Scholar
Golub, Benjamin and Jackson, Matthew O (2010). “Naive learning in social networks and the wisdom of crowds.” American Economic Journal: Microeconomics, 2(1), 112149.Google Scholar
Golub, Benjamin and Jackson, Matthew O (2012). “How homophily affects the speed of learning and best-response dynamics.” The Quarterly Journal of Economics, 127(3), 12871338.CrossRefGoogle Scholar
Goodman, Steven and Greenland, Sander (2007). “Why most published research findings are false: Problems in the analysis.” Public Library of Science Medicine, 4(4), e168.Google ScholarPubMed
Gopalakrishna, Gowri, Ter Riet, Gerben, Vink, Gerko, et al. (2022). “Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in the Netherlands.” Public Library of Science One, 17(2), e0263023.Google ScholarPubMed
Gorman, Dennis M, Elkins, Amber D, and Lawley, Mark (2019). “A systems approach to understanding and improving research integrity.” Science and Engineering Ethics, 25(1), 211229.CrossRefGoogle ScholarPubMed
Grim, Patrick, Singer, Daniel J, Bramson, Aaron, et al. (2019). “Diversity, ability, and expertise in epistemic communities.” Philosophy of Science, 86(1), 98123.CrossRefGoogle Scholar
Grim, Patrick, Singer, Daniel J, Fisher, Steven, et al. (2013). “Scientific networks on data landscapes: Question difficulty, epistemic success, and convergence.” Episteme, 10(4), 441464.CrossRefGoogle ScholarPubMed
Grim, Patrick, Singer, Daniel J, Reade, Christopher, and Fisher, Steven (2015). “Germs, genes, and memes: Function and fitness dynamics on information networks.” Philosophy of Science, 82(2), 219243.CrossRefGoogle Scholar
Gross, Kevin and Bergstrom, Carl T (2019). “Contest models highlight inherent inefficiencies of scientific funding competitions.” Public Library of Science Biology, 17(1), e3000065.Google ScholarPubMed
Gross, Kevin and Bergstrom, Carl T (2021). “Why ex post peer review encourages high-risk research while ex ante review discourages it.” Proceedings of the National Academy of Sciences, 118(51), e2111615118.CrossRefGoogle Scholar
Harnagel, Audrey (2019). “A mid-level approach to modeling scientific communities.” Studies in History and Philosophy of Science Part A, 76, 4959.CrossRefGoogle ScholarPubMed
Head, Megan L, Holman, Luke, Lanfear, Rob, Kahn, Andrew T, and Jennions, Michael D (2015). “The extent and consequences of p-hacking in science.” Public Library of Science Biology, 13(3), e1002106.Google ScholarPubMed
Heesen, Remco (2017a). “Academic superstars: Competent or lucky?Synthese, 194(11), 44994518.CrossRefGoogle Scholar
Heesen, Remco (2017b). “Communism and the incentive to share in science.” Philosophy of Science, 84(4), 698716.CrossRefGoogle Scholar
Heesen, Remco (2018). “Why the reward structure of science makes reproducibility problems inevitable.” The Journal of Philosophy, 115(12), 661674.CrossRefGoogle Scholar
Heesen, Remco (2021). “Cumulative advantage and the incentive to commit fraud in science.” Studies in History and Philosophy of Science Part A. https://doi.org/10.1086/716235.Google Scholar
Heesen, Remco and Kofi Bright, Liam (2020). “Is peer review a good idea?The British Journal for the Philosophy of Science, 72(3), 635663.CrossRefGoogle Scholar
Heesen, Remco, Kofi Bright, Liam, and Zucker, Andrew (2019). “Vindicating methodological triangulation.” Synthese, 196(8), 30673081.CrossRefGoogle Scholar
Heesen, Remco and Romeijn, Jan-Willem (2019). “Epistemic diversity and editor decisions: A statistical Matthew effect.” Philosophers’ Imprint, 19(39), 120.Google Scholar
Hegselmann, Rainer, Krause, Ulrich (2002). “Opinion dynamics and bounded confidence models, analysis, and simulation.” Journal of Artificial Societies and Social Simulation, 5(3) 133.Google Scholar
Hengel, Erin (2022). “Publishing while female: Are women held to higher standards? Evidence from peer review.” The Economic Journal, 132(648), 29512991. https://doi.org/10.1093/ej/ueac032/6586337.CrossRefGoogle Scholar
Higginson, Andrew D and Munafò, Marcus R (2016). “Current incentives for scientists lead to underpowered studies with erroneous conclusions.” Public Library of Science Biology, 14(11), e2000995.Google ScholarPubMed
Hightower, Jane Marie (2011). Diagnosis: Mercury: Money, Politics, and Poison. Island Press.Google Scholar
Hitzig, Zoe and Stegenga, Jacob (2020). “The problem of new evidence: P-hacking and pre-analysis plans.” Diametros, 17(66), 124.CrossRefGoogle Scholar
Hollenbeck, John R and Wright, Patrick M (2017). “Harking, sharking, and tharking: Making the case for post hoc analysis of scientific data.” Journal of Management, 43, 518.CrossRefGoogle Scholar
Holman, Bennett and Bruner, Justin (2017). “Experimentation by industrial selection.” Philosophy of Science, 84(5), 10081019.CrossRefGoogle Scholar
Holman, Bennett and Bruner, Justin P (2015). “The problem of intransigently biased agents.” Philosophy of Science, 82(5), 956968.CrossRefGoogle Scholar
Hong, Lu and Page, Scott E (2004). “Groups of diverse problem solvers can outperform groups of high-ability problem solvers.” Proceedings of the National Academy of Sciences, 101(46), 1638516389.CrossRefGoogle ScholarPubMed
Huebner, Bryce and Kofi Bright, Liam (2020). “Collective responsibility and fraud in scientific communities.” In Bazargan-Forward, S. and Tollefsen, D. P. (eds.), The Routledge Handbook of Collective Responsibility, 358372.CrossRefGoogle Scholar
Hull, David L (1988). Science as a Process: An Evolutionary Account of the Social and Conceptual Development of Science. University of Chicago Press.CrossRefGoogle Scholar
Ioannidis, John PA (2005). “Why most published research findings are false.” Public Library of Science Medicine, 2(8), e124.Google ScholarPubMed
Ioannidis, John PA (2008). “Why most discovered true associations are inflated.” Epidemiology, 19(5), 640648.CrossRefGoogle ScholarPubMed
Jackson, Matthew O and Wolinsky, Asher (2003). A Strategic Model of Social and Economic Networks. Springer.CrossRefGoogle Scholar
John, Leslie K, Loewenstein, George, and Prelec, Drazen (2012). “Measuring the prevalence of questionable research practices with incentives for truth telling.” Psychological Science, 23(5), 524532.CrossRefGoogle ScholarPubMed
Jönsson, Martin L, Hahn, Ulrike, and Erik, J Olsson, (2015). “The kind of group you want to belong to: Effects of group structure on group accuracy.” Cognition, 142, 191204.CrossRefGoogle ScholarPubMed
Kaplan, Robert M and Irvin, Veronica L (2015). “Likelihood of null effects of large NHLBI clinical trials has increased over time.” Public Library of Science One, 10(8), e0132382.Google ScholarPubMed
Kauffman, Stuart and Levin, Simon (1987). “Towards a general theory of adaptive walks on rugged landscapes.” Journal of Theoretical Biology, 128(1), 1145.CrossRefGoogle ScholarPubMed
Kauffman, Stuart A and Weinberger, Edward D (1989). “The NK model of rugged fitness landscapes and its application to maturation of the immune response.” Journal of Theoretical Biology, 141(2), 211245.CrossRefGoogle ScholarPubMed
Kerr, Norbert L (1998). “HARKing: Hypothesizing after the results are known.” Personality and Social Psychology Review, 2(3), 196217.CrossRefGoogle ScholarPubMed
Kitcher, Philip (1990). “The division of cognitive labor.” The Journal of Philosophy, 87(1), 522.CrossRefGoogle Scholar
Klein, Richard A, Ratliff, Kate A, Vianello, Michelangelo, et al. (2014). “Investigating variation in replicability: A ‘many labs’ replication project.” Social Psychology, 45(3), 142152.CrossRefGoogle Scholar
Klein, Richard A, Vianello, Michelangelo, Hasselman, Fred, et al. (2018). “Many labs 2: Investigating variation in replicability across samples and settings.” Advances in Methods and Practices in Psychological Science, 1(4), 443490.CrossRefGoogle Scholar
Kleinberg, Jon and Oren, Sigal (2011). “Mechanisms for (mis) allocating scientific credit.” Proceedings of the Forty-Third Annual ACM Symposium on Theory of Computing. 529538.CrossRefGoogle Scholar
Korf, Rebecca (2023). Taking the Social Structure of Science Seriously When Debating Values in Science. Working Paper.Google Scholar
Kuhn, Thomas (1962). The Structure of Scientific Revolutions. Princeton University Press.Google Scholar
Kummerfeld, Erich and Zollman, Kevin JS (2020). “Conservatism and the scientific state of nature.” The British Journal for the Philosophy of Science, 67(4) 10571076.CrossRefGoogle Scholar
Kyburg Jr, Henry E and Man Teng, Choh (2013). “Choosing among interpretations of probability.” ArXiv Preprint ArXiv:1301.6713.Google Scholar
LaCroix, Travis, Geil, Anders, and O’Connor, Cailin (2021). “The dynamics of retraction in epistemic networks.” Philosophy of Science, 88(3), 415438.CrossRefGoogle Scholar
Lakens, Daniel (2019). “The value of preregistration for psychological science: A conceptual analysis.” Japanese Psychological Review, 62(3), 221230.Google Scholar
Landemore, Hélène (2012). Democratic Reason. Princeton University Press.Google Scholar
Larivière, Vincent, Chaoqun, Ni, Gingras, Yves, Cronin, Blaise, and Sugimoto, Cassidy R (2013). “Bibliometrics: Global gender disparities in science.” Nature, 504(7479), 211213.CrossRefGoogle ScholarPubMed
Latham, Gary P, Erez, Miriam, and Locke, Edwin A (1988). “Resolving scientific disputes by the joint design of crucial experiments by the antagonists: Application to the Erez–Latham dispute regarding participation in goal setting.” Journal of Applied Psychology, 73(4), 753772.CrossRefGoogle Scholar
Lazer, David and Friedman, Allan (2007). “The network structure of exploration and exploitation.” Administrative Science Quarterly, 52(4), 667694.CrossRefGoogle Scholar
Lee, Carole J (2016). “eds Michael Brownstein, and Saul.”, Jennifer Implicit Bias and Philosophy, Volume 1: Metaphysics and Epistemology, 265282.CrossRefGoogle Scholar
Leonard, Thomas C (2002). “Reflection on rules in science: An invisible-hand perspective.” Journal of Economic Methodology, 9(2), 141168.CrossRefGoogle Scholar
Leslie, Derek (2005). “Are delays in academic publishing necessary?American Economic Review, 95(1), 407413.CrossRefGoogle Scholar
Lewandowsky, Stephan and Oberauer, Klaus (2020). “Low replicability can support robust and efficient science.” Nature Communications, 11(1), 112.Google ScholarPubMed
Lewandowsky, Stephan, Pilditch, Toby D, Madsen, Jens K, Oreskes, Naomi, and Risbey, James S (2019). “Influence and seepage: An evidence-resistant minority can affect public opinion and scientific belief formation.” Cognition, 188, 124139.CrossRefGoogle ScholarPubMed
Link, Albert N, Swann, Christopher A, and Bozeman, Barry (2008). “A time allocation study of university faculty.” Economics of Education Review, 27(4), 363374.CrossRefGoogle Scholar
Luukkonen, Terttu (2012). “Conservatism and risk-taking in peer review: Emerging ERC practices.” Research Evaluation, 21(1), 4860.CrossRefGoogle Scholar
Magnus, PD (2013). “What scientists know is not a function of what scientists know.” Philosophy of Science, 80(5), 840849.CrossRefGoogle Scholar
March, James G (1991). “Exploration and exploitation in organizational learning.” Organization Science, 2(1), 7187.CrossRefGoogle Scholar
Mason, Winter A, Jones, Andy, and Goldstone, Robert L (2008). “Propagation of innovations in networked groups.” Journal of Experimental Psychology: General, 137(3), 422433.CrossRefGoogle ScholarPubMed
Mayo, Deborah G (1996). Error and the Growth of Experimental Knowledge. University of Chicago Press.CrossRefGoogle Scholar
Mayo, Deborah G (2018). “Statistical inference as severe testing.” Cambridge, UK: Cambridge Univ. Press Access provided by Katholieke Universiteit Leuven-KU Leuven on,.Google Scholar
Conor, Mayo-Wilson, Zollman, Kevin JS, and Danks, David (2011). “The independence thesis: When individual and social epistemology diverge.” Philosophy of Science, 78(4), 653677.Google Scholar
McDowell, John M and Kiholm Smith, Janet (1992). “The effect of gender-sorting on propensity to coauthor: Implications for academic promotion.” Economic Inquiry, 30(1), 6882.CrossRefGoogle Scholar
McElreath, Richard and Smaldino, Paul E (2015). “Replication, communication, and the population dynamics of scientific discovery.” Public Library of Science One, 10(8), e0136088.Google ScholarPubMed
McShane, Blakeley B, Gal, David, Gelman, Andrew, Robert, Christian, and Tackett, Jennifer L (2019). “Abandon statistical significance.” The American Statistician, 73(sup1), 235245.CrossRefGoogle Scholar
Merton, Robert K (1942). “A note on science and democracy.” Journal of Legal and Political Sociology, 1, 115126.Google Scholar
Merton, Robert K (1957). “Priorities in scientific discovery: A chapter in the sociology of science.” American Sociological Review, 22(6), 635659.CrossRefGoogle Scholar
Merton, Robert K (1968). “The Matthew effect in science: The reward and communication systems of science are considered.” Science, 159(3810), 5663.CrossRefGoogle Scholar
Merton, Robert K (1973). The Sociology of Science: Theoretical and Empirical Investigations. University of Chicago press.Google Scholar
Mohseni, Aydin (2023a). “ HARKing: From misdiagnosis to mispescription.” Working Paper.Google Scholar
Mohseni, Aydin (2023b). “ Intervention and backfire in the replication crisis.” Working Paper.Google Scholar
Mohseni, Aydin and Randall Williams, Cole (2021). “Truth and conformity on networks.” Erkenntnis, 86, 15091530.CrossRefGoogle Scholar
Ramal, Moonesinghe, Khoury, Muin J, and Cecile JW Janssens, A (2007). “Most published research findings are false: But a little replication goes a long way.” Public Library of Science Medicine, 4(2), e28. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0040028.Google Scholar
Muldoon, Ryan and Weisberg, Michael (2011). “Robustness and idealization in models of cognitive labor.” Synthese, 183(2), 161174.CrossRefGoogle Scholar
Munafò, Marcus R, Nosek, Brian A, Bishop, Dorothy VM, et al. (2017). “A manifesto for reproducible science.” Nature Human Behaviour, 1(1), 19.CrossRefGoogle ScholarPubMed
Murphy, Kevin R and Aguinis, Herman (2019). “HARKing: How badly can cherry-picking and question trolling produce bias in published results?Journal of Business and Psychology, 34(1), 117.CrossRefGoogle Scholar
Newman, Mark EJ (2001). “Scientific collaboration networks: I. Network construction and fundamental results.” Physical Review E, 64(1), 016131.CrossRefGoogle ScholarPubMed
Newman, Mark EJ (2004). “Coauthorship networks and patterns of scientific collaboration.” Proceedings of the National Academy of Sciences, 101(suppl 1), 52005205.CrossRefGoogle ScholarPubMed
Nissen, Silas Boye, Magidson, Tali, Gross, Kevin, and Bergstrom, Carl T (2016). “Publication bias and the canonization of false facts.” Elife, 5, e21451.CrossRefGoogle ScholarPubMed
Nosek, Brian A and Bar-Anan, Yoav (2012). “Scientific utopia: I. Opening scientific communication.” Psychological Inquiry, 23(3), 217243.CrossRefGoogle Scholar
Nosek, Brian A, Ebersole, Charles R, DeHaven, Alexander C, and Mellor, David T (2018). “The preregistration revolution.” Proceedings of the National Academy of Sciences, 115(11), 26002606.CrossRefGoogle ScholarPubMed
Nosek, Brian A and Lakens, Daniël (2014). “Registered reports: A method to increase the credibility of published results.” Social Psychology, 45(3), 137141.CrossRefGoogle Scholar
Nosek, Brian A, Spies, Jeffrey R, and Motyl, Matt (2012). “Scientific utopia: II. Restructuring incentives and practices to promote truth over publishability.” Perspectives on Psychological Science, 7(6), 615631.CrossRefGoogle ScholarPubMed
Nuzzo, Regina (2015). “Fooling ourselves.” Nature, 526(7572), 182185.CrossRefGoogle Scholar
O’Connor, Cailin (2017). “The cultural red king effect.” The Journal of Mathematical Sociology, 41(3), 155171.CrossRefGoogle Scholar
O’Connor, Cailin (2019a). “The natural selection of conservative science.” Studies in History and Philosophy of Science Part A, 76, 2429.CrossRefGoogle ScholarPubMed
O’Connor, Cailin (2019b). The Origins of Unfairness: Social Categories and Cultural Evolution. Oxford University Press, USA.CrossRefGoogle Scholar
O’Connor, Cailin and Bruner, Justin (2019). “Dynamics and diversity in epistemic communities.” Erkenntnis, 84(1), 101119.CrossRefGoogle Scholar
O’Connor, Cailin and Owen Weatherall, James (2018). “Scientific polarization.” European Journal for Philosophy of Science, 8(3), 855875.CrossRefGoogle Scholar
O’Connor, Cailin and Owen Weatherall, James (2019). The Misinformation Age. Yale University Press.Google Scholar
Okasha, Samir (2006). Evolution and the Levels of Selection. Oxford University Press.CrossRefGoogle Scholar
Olsson, E.J. (2013). A Bayesian Simulation Model of Group Deliberation and Polarization. In: Zenker, F. (eds.), Bayesian Argumentation. Synthese Library, vol 362. Springer: Dordrecht, 113133. https://doi.org/10.1007/978-94-007-5357-0_6.CrossRefGoogle Scholar
Open Science Collaboration, et al. (2015). “Estimating the reproducibility of psychological science.” Science, 349(6251).Google Scholar
Oreskes, Naomi and Conway, Erik M (2011). Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming. Bloomsbury Publishing, USA.Google Scholar
Oster, Sharon (1980). “The optimal order for submitting manuscripts.” The American Economic Review, 70(3), 444448.Google Scholar
Peirce, Charles S (1967). “Note on the theory of the economy of research.” Operations Research, 15(4), 643648.CrossRefGoogle Scholar
Pinto, Manuela Fernández and Fernández Pinto, Daniel (2018). “Epistemic landscapes reloaded: An examination of agent-based models in social epistemology.” Historical Social Research/Historische Sozialforschung, 43(1 (163)), 4871.Google Scholar
Polanyi, Michael, Ziman, John, and Fuller, Steve (2000). “The republic of science: Its political and economic theory Minerva, I (1)(1962), 54–73.” Minerva, 38(1), 132.CrossRefGoogle Scholar
Popper, Karl R (1972). Objective Knowledge. Volume 360. Oxford University Press, Oxford.Google Scholar
Pöyhönen, Samuli (2017). “Value of cognitive diversity in science.” Synthese, 194(11), 45194540.CrossRefGoogle Scholar
Protzko, John, Krosnick, Jon, Nelson, Leif D, et al. (2023). “ High replicability of newly-discovered social-behavioral findings is achievable.” Working Paper.Google Scholar
Radzvilas, Mantas, Peden, William, and De Pretis, Francesco (2021). “A battle in the statistics wars: A simulation-based comparison of Bayesian, Frequentist and Williamsonian methodologies.” Synthese, 199(5), 1368913748.CrossRefGoogle Scholar
Reijula, Samuli and Kuorikoski, Jaakko (2019). “Modeling epistemic communities.” In Miranda, Fricker, Graham, Peter J., Henderson, David, and Pedersen, Nikolaj JLL, (eds.), The Routledge Handbook of Social Epistemology. Routledge, 240249.CrossRefGoogle Scholar
Reijula, Samuli and Kuorikoski, Jaakko (2021). “The diversity-ability trade-off in scientific problem solving.” Philosophy of Science, 88(5), 894905.CrossRefGoogle Scholar
Rogers, Everett M (2010). Diffusion of Innovations. Simon and Schuster.Google Scholar
Romero, Felipe (2016). “Can the behavioral sciences self-correct? A social epistemic study.” Studies in History and Philosophy of Science Part A, 60, 5569.CrossRefGoogle ScholarPubMed
Romero, Felipe (2017). “Novelty versus replicability: Virtues and vices in the reward system of science.” Philosophy of Science, 84(5), 10311043.CrossRefGoogle Scholar
Romero, Felipe (2018). “Who should do replication labor?Advances in Methods and Practices in Psychological Science, 1(4), 516537.CrossRefGoogle Scholar
Romero, Felipe (2020). “The Division of Replication Labor.” Philosophy of Science, 87(5), 10141025.CrossRefGoogle Scholar
Romero, Felipe and Sprenger, Jan (2021). “Scientific self-correction: The Bayesian way.” Synthese, 198(23), 58035823.CrossRefGoogle Scholar
Rosenstock, Sarita, Bruner, Justin, and O’Connor, Cailin (2017). “In epistemic networks, is less really more?Philosophy of Science, 84(2), 234252.CrossRefGoogle Scholar
Rosenthal, Robert (1979). “The file drawer problem and tolerance for null results.” Psychological Bulletin, 86(3), 638641.CrossRefGoogle Scholar
Rossiter, Margaret W (1993). “The Matthew Matilda effect in science.” Social Studies of Science, 23(2), 325341.CrossRefGoogle Scholar
Rubin, Hannah (2022). “Structural causes of citation gaps.” Philosophical Studies, 179, 23232345.CrossRefGoogle Scholar
Rubin, Hannah and O’Connor, Cailin (2018). “Discrimination and collaboration in science.” Philosophy of Science, 85(3), 380402.CrossRefGoogle Scholar
Rubin, Hannah and Schneider, Mike D (2021). “Priority and privilege in scientific discovery.” Studies in History and Philosophy of Science Part A, 89, 202211.CrossRefGoogle ScholarPubMed
Rubin, Mark (2017). “When does HARKing hurt? Identifying when different types of undisclosed post hoc hypothesizing harm scientific progress.” Review of General Psychology, 21(4), 308320.CrossRefGoogle Scholar
Rubin, Mark (2020). “Does preregistration improve the credibility of research findings?” ArXiv Preprint ArXiv:2010.10513.Google Scholar
Sampaio, Ricardo Barros, Marcus Vinicius, de Araújo Fonseca, Zicker, Fabio, et al. (2016). “Co-authorship network analysis in health research: Method and potential use.” Health Research Policy and Systems, 14(1), 110.Google Scholar
Santana, Carlos (2021). “Let’s not agree to disagree: The role of strategic disagreement in science.” Synthese, 198(25), 61596177.CrossRefGoogle Scholar
Sarsons, Heather (2017). “Recognition for group work: Gender differences in academia.” American Economic Review, 107(5), 141145.CrossRefGoogle Scholar
Schneider, Mike D (2021). “Creativity in the social epistemology of science.” Philosophy of Science, 88(5), 882893.CrossRefGoogle Scholar
Schneider, Mike D, Rubin, Hannah, and O’Connor, Cailin (2022). “Promoting diverse collaborations.” In Ramsey, G. and de Block, A. (eds.), The Dynamics of Science: Computational Frontiers in History and Philosophy of Science. University of Pittsburgh Press.Google Scholar
Schofield, Paul N, Bubela, Tania, Weaver, Thomas, et al. (2009). “Post-publication sharing of data and tools.” Nature, 461(7261), 171173.CrossRefGoogle ScholarPubMed
Selvin, Hanan C and Stuart, Alan (1966). “Data-dredging procedures in survey analysis.” The American Statistician, 20(3), 2023.Google Scholar
Simmons, Joseph P, Nelson, Leif D, and Simonsohn, Uri (2016). “False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 13591366CrossRefGoogle Scholar
Singer, Daniel J (2019). “Diversity, not randomness, trumps ability.” Philosophy of Science, 86(1), 178191.CrossRefGoogle ScholarPubMed
Smaldino, Paul (2019a). “Better methods can’t make up for mediocre theory.” Nature, 575(7783), 910.CrossRefGoogle ScholarPubMed
Smaldino, Paul E (2019b). “ Five models of science, illustrating how selection shapes methods.” Working paper.CrossRefGoogle Scholar
Smaldino, Paul and O’Connor, Cailin (2022). “Interdisciplinarity can aid the spread of better methods between scientific communities.” Collective Intelligence, 1(2), 26339137221131816.CrossRefGoogle Scholar
Smaldino, Paul E (2019b). “ Five models of science, illustrating how selection shapes methods.” Working Paper.CrossRefGoogle Scholar
Smaldino, Paul E and McElreath, Richard (2016). “The natural selection of bad science.” Royal Society Open Science, 3(9), 160384.CrossRefGoogle ScholarPubMed
Smaldino, Paul E, Turner, Matthew A, and Contreras Kallens, Pablo A (2019). “Open science and modified funding lotteries can impede the natural selection of bad science.” Royal Society Open Science, 6(7), 190194.CrossRefGoogle ScholarPubMed
Smith, Adam (1759). The Theory of Moral Sentiments. for A. Millar, Printed and Kincaid, A. and , J. Bell.CrossRefGoogle Scholar
Smith, George Davey and Ebrahim, Shah. “Data dredging, bias, or confounding: They can all get you into the BMJ and the Friday papers.” British Medical Journal 325, 14371438.CrossRefGoogle Scholar
Soderberg, Courtney K, Errington, Timothy M, Schiavone, Sarah R, et al. (2021). “Initial evidence of research quality of registered reports compared with the standard publishing model.” Nature Human Behaviour, 5(8), 990997.CrossRefGoogle ScholarPubMed
Solomon, Miriam (2006). “Groupthink versus the wisdom of crowds: The social epistemology of deliberation and dissent.” The Southern Journal of Philosophy, 44(S1), 2842.CrossRefGoogle Scholar
Sommers, Samuel R (2006). “On racial diversity and group decision making: Identifying multiple effects of racial composition on jury deliberations.” Journal of Personality and Social Psychology, 90(4), 597612.CrossRefGoogle ScholarPubMed
Sonnert, Gerhard and Holton, Gerald (1996). “Career patterns of women and men in the sciences.” American Scientist, 84(1), 6371.Google Scholar
Stanford, P Kyle (2019). “Unconceived alternatives and conservatism in science: The impact of professionalization, peer-review, and Big Science.” Synthese, 196(10), 39153932.CrossRefGoogle Scholar
Stephan, Paula (1996). How Economics Shapes Science. Harvard University Press.Google Scholar
Stewart, Alexander J and Plotkin, Joshua B (2021). “The natural selection of good science.” Nature Human Behaviour, 5, 15101518.CrossRefGoogle ScholarPubMed
Strevens, Michael (2003). “The role of the priority rule in science.” The Journal of Philosophy, 100(2), 5579.CrossRefGoogle Scholar
Strevens, Michael (2006). “The role of the Matthew effect in science.” Studies in History and Philosophy of Science Part A, 37(2), 159170.CrossRefGoogle Scholar
Strevens, Michael (2011). “Economic approaches to understanding scientific norms.” Episteme, 8(2), 184200.CrossRefGoogle Scholar
Strevens, Michael (2013). “Herding and the quest for credit.” Journal of Economic Methodology, 20(1), 1934.CrossRefGoogle Scholar
Strevens, Michael (2017). “Scientific sharing: Communism and the social contract.” In Boyer-Kassem, T., Mayo-Wilson, C., and Weisberg, M. (eds.), Scientific Collaboration and Collective Knowledge, 333.Google Scholar
Szollosi, Aba, Kellen, David, Navarro, Danielle, et al. (2020). “Is preregistration worthwhile? Trends in Cognitive Sciences, 24(2), 9495.CrossRefGoogle ScholarPubMed
Tendeiro, Jorge N and Kiers, Henk AL (2019). “A review of issues about null hypothesis Bayesian testing.” Psychological Methods, 24(6), 774795.CrossRefGoogle ScholarPubMed
Thagard, Paul (2006). “How to collaborate: Procedural knowledge in the cooperative development of science.” The Southern Journal of Philosophy, 44(S1), 177196.CrossRefGoogle Scholar
Thoma, Johanna (2015). “The epistemic division of labor revisited.” Philosophy of Science, 82(3), 454472.CrossRefGoogle Scholar
Thompson, Abigail (2014). “Does diversity trump ability?Notices of the AMS, 61(9), 10241030.Google Scholar
Tiokhin, Leo, Lakens, Daniel, Smaldino, Paul E, and Panchanathan, Karthik (2021). “Shifting the level of selection in science.” Perspectives on Psychological Science, 17456916231182568.Google Scholar
Tiokhin, Leonid and Derex, Maxime (2019). “Competition for novelty reduces information sampling in a research game-a registered report.” Royal Society Open Science, 6(5), 180934.CrossRefGoogle Scholar
Tiokhin, Leonid, Panchanathan, Karthik, Lakens, Daniel, et al. (2021). “Honest signaling in academic publishing.” Public Library of Science One, 16(2), e0246675.Google ScholarPubMed
Leonid, Tiokhin, Yan, Minhua, and Morgan, Thomas JH (2021). “Competition for priority harms the reliability of science, but reforms can help.” Nature Human Behaviour, 5(7), 857867.Google Scholar
Viola, Marco (2015). “Some remarks on the division of cognitive labor.” RT. A Journal on Research Policy and Evaluation, 3.Google Scholar
Wagner, Elliott and Herington, Jonathan (2021). “Agent-based models of dual-use research restrictions.” The British Journal for the Philosophy of Science, 72(2), 377399.CrossRefGoogle Scholar
Watts, Christopher and Gilbert, Nigel (2011). “Does cumulative advantage affect collective learning in science? An agent-based simulation.” Scientometrics, 89(1), 437463.CrossRefGoogle Scholar
Weatherall, James Owen and O’Connor, Cailin (2021a). “Conformity in scientific networks.” Synthese, 198(8), 72577278.CrossRefGoogle Scholar
Weatherall, James Owen and O’Connor, Cailin (2021b). “Endogenous epistemic factionalization.” Synthese, 198(25), 61796200.CrossRefGoogle Scholar
Weatherall, James Owen, O’Connor, Cailin, and Bruner, Justin P (2020). “How to beat science and influence people: Policymakers and propaganda in epistemic networks.” The British Journal for the Philosophy of Science, 71(4), 11571186.CrossRefGoogle Scholar
Weisberg, Michael and Muldoon, Ryan (2009). “Epistemic landscapes and the division of cognitive labor.” Philosophy of Science, 76(2), 225252.CrossRefGoogle Scholar
West, Jevin D, Jacquet, Jennifer, King, Molly M, Correll, Shelley J, and Bergstrom, Carl T (2013). “The role of gender in scholarly authorship.” Public Library of Science One, 8(7), e66212.Google ScholarPubMed
Wright, Sewall (1932). “The roles of mutation, inbreeding, crossbreeding, and selection in evolution.” Proceedings of the Sixth International Congress on Genetics, 356366.Google Scholar
Jingyi, Wu (forthcoming). Better than Best. Philosophy of Science.Google Scholar
Jingyi, Wu (2023a). “ The communist norm and industrial science.” Withholding Knowledge. Working Paper.Google Scholar
Jingyi, Wu (2023b). “Epistemic advantage on the margin: A network standpoint epistemology.” Philosophy and Phenomenological Research, 106(3), 755777.Google Scholar
Jingyi, Wu and O’Connor, Cailin (2023). “How should we promote transient diversity in science? Synthese, 201(2), 37.Google Scholar
Jingyi, Wu, O’Connor, Cailin, and Smaldino, Paul E (forthcoming). “The cultural evolution of science.” In Tehrani, J., Kendal, R. and Kendal, J. (eds.), The Oxford Handbook of Cultural Evolution. Oxford University Press.Google Scholar
Xie, Yu, Wang, Kai, and Kong, Yan (2021). “Prevalence of research misconduct and questionable research practices: A systematic review and meta-analysis.” Science and Engineering Ethics, 27(4), 128.CrossRefGoogle ScholarPubMed
Yahosseini, Kyanoush Seyed and Moussaïd, Mehdi (2020). “Comparing groups of independent solvers and transmission chains as methods for collective problem-solving.” Scientific Reports, 10(1), 19.CrossRefGoogle ScholarPubMed
Zollman, Kevin (2023). “ The scientific ponzi scheme.” Working Paper.Google Scholar
Zollman, Kevin JS (2007). “The communication structure of epistemic communities.” Philosophy of Science, 74(5), 574587.CrossRefGoogle Scholar
Zollman, Kevin JS (2009). “Optimal publishing strategies.” Episteme, 6(2), 185199.CrossRefGoogle Scholar
Zollman, Kevin JS (2010). “The epistemic benefit of transient diversity.” Erkenntnis, 72(1), 1735.CrossRefGoogle Scholar
Zollman, Kevin JS (2018). “The credit economy and the economic rationality of science.” The Journal of Philosophy, 115(1), 533.CrossRefGoogle Scholar

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Modelling Scientific Communities
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Modelling Scientific Communities
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