Исследовательское поведение: ограниченно рациональное производство рационального научного знания

1. Newton-Smith, W. H. (1981). The Rationality of Science. London: Routledge.

2. Merton, R. K. (1942). Science and technology in a democratic order. Journal of Legal and Political Sociology. Vol. 1. P. 115–126.

3. Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics. Vol. 69, no. 1. P. 99–118.

4. Sent, E.-M. (2018). Rationality and bounded rationality: you can’t have one without the other. European Journal of the History of Economic Thought. Vol. 25, is. 6. P. 1370–1386.

5. Bazerman, M. H. and Messick, D. M. (1998). On the power of a clear definition of rationality. Business Ethics Quarterly, Vol. 8, is. 3. P. 477–480.

6. Simon, H. A. (1956). A Comparison of Game Theory and Learning Theory. Psychometrika. Vol. 21, is. 3. P. 267–272.

7. Boudon, R. (1989). Subjective Rationality and the Explanation of Social Behavior. Rationality and Society. Vol. 1, is 2. P. 173–196.

8. Ryall, M. D. (2003). Subjective Rationality, Self-Confirming Equilibrium, and Corporate Strategy. Management Science. Vol. 49, no. 7. P. 936–949.

9. Gilboa, I., Maccheroni, F., Marinacci, M. and Schmeidler, D. (2010). Objective and subjective rationality in a multiple prior model. Econometrica. Vol. 78, no. 2. P. 755–770.

10. Loewenstein, G. (1996). Out of Control: Visceral Influences on Behavior. Organizational Behavior and Human Decision Processes. Vol. 65, no. 3. P. 272–292.

11. Kahneman, D. and Tversky, A. (1984). Choices, values, and frames. American Psychologist. Vol. 39, no. 4. P. 341–350.

12. Thaler, R. H. (1991). Quasi Rational Economics. New York: Russell Sage Found.

13. Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review. Vol. 93, is. 5. P. 1449–1475.

14. Jones, B. D. (1999). Bounded rationality. Annual Review of Political Science. Vol. 2, is. 1. P. 297–321.

15. Coase, R. (1992). The Institutional Structure of Production. American Economic Review. Vol. 82, is. 4. P. 713–719.

16. Polya, G. (1954). Mathematics and Plausible Reasoning. Vol. I&II. Princeton, NJ: Princeton University Press.

17. Hertwig, R. and Pachur, T. (2015). Heuristics, History of. In: Wright J. (Ed.) International Encyclopedia of the Social & Behavioral Sciences, 2nd ed., Vol. 10. P. 879–835. Oxford: Elsevier.

18. Reber, A. S. (1992). The cognitive unconscious: An evolutionary perspective. Consciousness and Cognition. Vol. 1, is. 2. P. 93–133.

19. Greenwald, A. G. and Ganaji, M. R. (1995). Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes. Psychological Review. Vol. 102, is. 1. P. 4–27.

20. Casarett, D. (2016). The Science of Choosing Wisely – Overcoming the Therapeutic Illusion. New England Journal of Medicine. Vol. 374, no. 13. P. 1203–1205.

21. Lieder, F. and Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences. Vol. 43, article e1; DOI 10.1017/S0140525X1900061X.

22. Hahna, M., Futrell, R., Levy, R. and Gibson, E. (2022). A resource-rational model of human processing of recursive linguistic structure. PNAS: Psychological and Cognitive Sciences. Vol. 119, no. 43, article e2122602119.

23. Tversky, A. and Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science. New Series. Vol. 185, no. 4157. P. 1124–1131.

24. Taylor, R. N. (1975). Psychological determinants of bounded rationality: Implications for decision-making strategies. Decision Sciences. Vol. 6, is. 3. P. 409–429.

25. Caverni, J.-P., Fabre, J.-M. and Gonzalez, M. (1990). Cognitive Biases: Their Contribution for Understanding Human Cognitive Processes. Advances in Psychology. Vol. 68. P. 7–12.

26. Byyny, R. L. (2017). Cognitive bias: Recognizing and managing our unconscious biases. The Pharos. No. Winter. P. 2–6.

27. Johnson, D. and Levin, S. (2009). The tragedy of cognition: psychological biases and environmental inaction. Current Science. Vol. 97, no. 11. P. 1593–1603.

28. Van Vugt, M., Griskevicius, V. and Schultz, P. W. (2014). Naturally Green: Harnessing Stone Age Psychological Biases to Foster Environmental Behavior. Social Issues and Policy Review. Vol. 8, is. 1. P. 1–32.

29. Haselton, M. G., Bryant, G. A., Wilke, A., Frederick, D. A., Galperin, A., Frankenhuis, W. E. and Moore, T. (2009). Adaptive rationality: An evolutionary perspective on cognitive bias. Socia1 Cognition. Vol. 27, no. 5. P. 733–763.

30. Jussim, L. (2012). Social perception and social reality: Why accuracy dominates bias and self-fulfilling prophecy. New York: Oxford University Press.

31. Jussim, L. (2017). Précis of Social Perception and Social Reality: Why accuracy dominates bias and self-fulfilling prophecy. Behavioral and Brain Sciences. Vol. 40, article e1 DOI:10.1017/S0140525X1500062X.

32. Kahneman, D. and Tversky, A. (1996). On the Reality of Cognitive Illusions. Psychological Review. Vol. 103, no. 3. P. 582–591.

33. Samuelson, W., Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty. Vol. 1, is.1. P. 7–59.

34. Barberis, N., Shleifer, A. and Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics. Vol. 49, is. 3. P. 307–343.

35. Gifford, R. (2011). The dragons of inaction: Psychological barriers that limit climate change mitigation and adaptation. American Psychologist. Vol. 66, no. 4. P. 290–302.

36. Chu, J. S. G. and Evans, J. A. (2021). Slowed canonical progress in large fields of science. Proceedings of the National Academy of Sciences (PNAS). Vol. 118, no. 41, article e2021636118.

37. Gigerenzer, G. (1991). How to make cognitive illusions disappear: Beyond “heuristics and biases”. In: Stroebe W. & Hewstone M. (Eds.). European Review of Social Psychology. (Vol. 2. P. 83–115). Chichester, UK: Wiley.

38. Gigerenzer, G and Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science. Vol. 1, is. 1. P. 107–143.

39. Grandori, A. and Cholakova, M. (2013). Unbounding bounded rationality: Heuristics as the logic of economic discovery. International Journal of Organization Theory & Behavior. Vol. 16, no. 3. P. 368–392.

40. Gigerenzer, G. (2008). Why heuristics work. Perspectives on Psychological Science. Vol. 3, is.1. P. 20–29.

41. Gigerenzer, G. and Gaissmaier, W. (2011). Heuristic Decision Making. Annual Review of Psychology, Vol. 62. P. 451–82.

42. Goldman, A. (1986). Epistemology and Cognition. Cambridge, MA: Harvard University Press.

43. Wible, J. R. (1997). Towards an evolutionary conception of rationality in science and economics. In: Wible, J. R. The Economics of Science: Methodology and Epistemology as if Economics Really Mattered. London: Routledge. P. 190–202.

44. Liebenberg, L. (2021). The Origin of Science: The Evolutionary Roots of Scientific Reasoning and its Implications for Tracking Science. 2nd ed. Cape Town: CyberTracker.

45. Feyerabend, P. (1975). Against Method: Outline of an Anarchistic Theory of Knowledge. London: Verso.

46. Bergström, L. (1980). Some Remarks Concerning Rationality in Science. In: Hilpinen R. (Ed.) Rationality in Science Dordrecht: Springer. P. 1–11.

47. Szollosi, A. and Newell, B. R. (2020). People as intuitive scientists: Reconsidering statistical explanations of decision making. Trends in Cognitive Sciences. Vol. 24, is. 12. P. 1008–1018.

48. Viktoruk, E. N. and Chernyeva, A. S. (2010). Understanding Horizons in Methodology of Socially-Humanitarian Cognition. Journal of Siberian Federal University: Humanities & Social Sciences. Vol. 5, no. 3. P. 776–784.

49. Turk-Browne, N. B., Junge, J. A. and Scholl, B. J. (2005). The Automaticity of Visual Statistical Learning. Journal of Experimental Psychology: General. Vol. 134, no. 4. P. 552–564.

50. Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.

51. Becker, G. S. (1976). The economic approach to human behavior. In: Becker, G. S. The Economic Approach to Human Behavior Chicago: University of Chicago Press. P. 3–14.

52. Merton, R. K. (1942). A note on science and democracy. Journal of Legal and Political Sociology. Vol. 1. P. 115–126.

53. Ioannidis, J. P. A. (2012). Why Science Is Not Necessarily Self-Correcting. Perspectives on Psychological Science. Vol. 7, is. 6. P. 645–654.

54. Stroebe, W., Postmes, T. and Spears, R. (2012). Scientific Misconduct and the Myth of Self-Correction in Science. Perspectives on Psychological Science. Vol. 7, no. 6. P. 670–688.

55. Allchin, D. (2015). Correcting the “self-correcting” mythos of science. Filosofia e História da Biologia. Vol. 10, is. 1. P. 19–35.

56. Romero, F. (2016). Can the Behavioral Sciences Self-Correct? A Social Epistemic Study. Studies In History and Philosophy of Science Part A. Vol. 60, is.1. P. 55–69.

57. De Vries, R., Anderson, M. S. and Martinson, B. C. (2006). Normal Misbehavior: Scientists Talk about the Ethics of Research. Journal of Empirical Research on Human Research Ethics. Vol. 1, is.1. P. 43–50.

58. Necker, S. (2014). Scientific misbehavior in economics. Research Policy. Vol. 43, is. 10. P. 1747–1759.

59. Hesselmann, F., Graf, V., Schmidt, M. and Reinhart, M. (2017). The visibility of scientific misconduct: A review of the literature on retracted journal articles. Current Sociology Review. Vol. 65, no. 6. P. 814–845.

60. Bruner, J. P. and Holman, B. (2019). Self-correction in science: Meta-analysis, bias and social structure. Studies in History and Philosophy of Science. Part A. Vol. 78. P. 93–97.

61. Tourish, D., Craig, R. (2020). Research Misconduct in Business and Management Studies: Causes, Consequences and Possible Remedies. Journal of Management Inquiry. Vol. 29, is. 2. P. 174–187.

62. Chubin, D. E. (1985). Misconduct in Research: An Issue of Science Policy and Practice. Minerva. Vol. 23, no. 2. P. 175–202.

63. Biagioli, M., Kenney, M., Martin, B. and Walsh, J. P. (2019). Academic misconduct, misrepresentation and gaming: A reassessment. Research Policy. Vol. 48, is. 2. P. 401–413.

64. Ioannidis, J. P. (2005). Why most published research findings are false. PLoS Medicine. Vol. 2, is. 8, article e124; DOI: 10.1371/journal.pmed.0020124.

65. Wilholt, T. (2009). Bias and values in scientific research. Studies in History and Philosophy of Science. Vol. 40, is.1. P. 92–101.

66. Ditto, P. H. (2009). Passion, reason, and necessity: A quantity-of-processing view of motivated reasoning. In: Bayne, T. & Fernández, J. (Eds.). Delusion and Self-Deception: Affective and Motivational Influences on Belief Formation New York: Psychology Press. P. 23–53.

67. Berggren, N., Jordahl, H. and Stern, C. (2009). The political opinions of Swedish social scientists. Finnish Economical Papers. Vol. 22, no. 2. P. 75–88.

68. Charlton, B. G. (2009). Clever sillies: Why high IQ people tend to be deficient in common sense. Medical Hypotheses. Vol. 73, no. 6. P. 867–70.

69. Woodley, M. A. (2010). Are high-IQ individuals deficient in common sense? A critical examination of the ‘clever sillies’ hypothesis. Intelligence. Vol. 38. P. 471–80.

70. Franco, A., Malhotra, N. and Simonovits, G. (2014). Publication bias in the social sciences: Unlocking the file drawer. Science. Vol. 345, no. 6203. P. 1502–1505.

71. Fanelli, D., Costas, R. and Ioannidis, J. P. A. (2017). Meta-assessment of bias in science. Proceedings of the National Academy of Sciences. Vol. 114, no. 14. P. 3714–3719.

72. Peterson, E. L. (2019). Can scientific knowledge sift the wheat from the tares? A brief history of bias (and fears about bias) in science. In: McCain, K. & Kampourakis, K. (Eds.). What is Scientific Knowledge? An Introduction to Contemporary Epistemology of Science London: Routledge. P. 195–211.

73. May, J. (2021). Bias in Science: Natural and Social. Synthese. Vol. 199, is. 1–2. P. 3345–3366.

74. Nickerson, R. S. (1998). Confirmation Bias: A Ubiquitous Phenomenon in Many Guises. Review of General Psychology. Vol. 2, no. 2. P. 175–220.

75. Kappes, A., Harvey, A. H., Lohrenz, T., Montague, P. R. and Sharot, T. (2020). Confirmation bias in the utilization of others' opinion strength. Nature Neuroscience. Vol. 23, is. 1. P. 130–137.

76. Schumm, W. R. (2021). Confirmation bias and methodology in social science: An editorial. Marriage & Family Review. Vol. 57, is. 4. P. 285–293.

77. McSweeney, B. (2021). Fooling ourselves and others: confirmation bias and the trustworthiness of qualitative research – Part 1 (the threats). Journal of Organizational Change Management. Vol. 34, no. 5. P. 1063–1075.

78. Fine, M. A. (2022). Distinctions between Scientific Misconduct and Bias in Social Science: Avoidable versus Unavoidable Deviations from Best Practices in Research. Marriage & Family Review. Vol. 58, is. 1. P. 89–100.

79. Moser, S. (2013). Confirmation Bias: The Pitfall of Forensic Science. Themis: Research Journal of Justice Studies and Forensic Science. Vol. 1, is. 1. P. 71–80.

80. Jenkins, H. M. and Ward, W. C. (1965). Judgment of contingency between responses and outcomes. Psychological Monographs. Vol. 79, is. 1. P. 1–17.

81. Shanks, D. R. and Dickinson, A. (1987). Associative accounts of causality judgment. In: Bower, G. H. (Ed.). The Psychology of Learning and Motivation San Diego, CA: Academic Press. P. 229–261.

82. Matute, H., Blanco, F., Yarritu, I., Díaz-Lago, M., Vadillo, M. A. and Barberia, I. (2015). Illusions of causality: How they bias our everyday thinking and how they could be reduced. Frontiers in Psychology. Vol. 6. article 888. DOI: 10.3389/fpsyg.2015.00888.

83. Moshman, D. (1990). Rationality as a Goal of Education. Educational Psychology Review. Vol. 2, no. 4. P. 335–364.

84. Park, P. S. (2022). The evolution of cognitive biases in human learning. Journal of Theoretical Biology. Vol. 541, article 111031.

85. Merton, R. K. (1968). The Matthew Effect in Science. Science. Vol. 159, no. 3810. P. 56–63.

86. Matute, H., Yarritu, I. and Vadillo, M. A. (2011). Illusions of causality at the heart of pseudoscience. British Journal of Psychology. Vol. 102, no. 3. P. 392–405.

87. Torres, M. N., Barberia, I. and Rodríguez-Ferreiro, J. (2020). Causal illusion as a cognitive basis of pseudoscientific beliefs. British Journal of Psychology. Vol. 111, no. 4. P. 840–852.

88. Seglen, P. O. (1992). The skewness of science. Journal of the American Society for Information Science. Vol. 43, is. 9. P. 628–638.

89. Hamilton, D. P. (1990). Publishing by – and for? – the Numbers. Science. Vol. 250, no. 4986. P. 1331–1332.

90. Hamilton, D. P. (1991). Research Papers: Who’s Uncited Now. Science. Vol. 251, no. 4989. P. 25.

91. Schwartz, C. A. (1997). The rise and fall of uncitedness. College & Research Libraries. Vol. 58, no. 1. P. 19–29.

92. Van Noorden, R. (2017). The science that’s never been cited. Nature. Vol. 552, no. 7684. P. 162–164.

93. Camacho-Minano, M. and Nunez-Nickel, M. (2009). The multilayered nature of reference selection. Journal of the American Society for Information Science and Technology. Vol. 60, is. 4. P. 754–777.

94. MacRoberts, M. H. and MacRoberts, B. R. (2010). Problems of citation analysis: A study of uncited and seldom‐cited influences. Journal of the American Society for Information Science and Technology. Vol. 61, is. 1. P. 1–12.