Nullius in Verba

In this final episode of the three-part series on the Philosophical Psychology lectures by Paul Meehl, we discuss lectures 6-8, which cover the ten obfuscating factors in "soft areas" of psychology and a host of advice Meehl provides for researchers, reviewers, editors, and educators on how to improve practice. 

Shownotes

• Krefeld-Schwalb, A., Sugerman, E. R., & Johnson, E. J. (2024). Exposing omitted moderators: Explaining why effect sizes differ in the social sciences. Proceedings of the National Academy of Sciences, 121(12), e2306281121. https://doi.org/10.1073/pnas.2306281121
• Lakens, D., & Etz, A. J. (2017). Too True to be Bad: When Sets of Studies With Significant and Nonsignificant Findings Are Probably True. Social Psychological and Personality Science, 8(8), 875–881. https://doi.org/10.1177/1948550617693058

In this episode, we continue the discussion of Meehl's Philosophy of Psychology course, focusing on lectures 3, 4, and 5. 

Shownotes

• The quote "Don't make a mockery of honest ad-hockery" is probably from Clark Glymour: https://en.wikipedia.org/wiki/Clark_Glymour
• Good, I. J. (1965). The Estimation of Probabilities: An Essay on Modern Bayesian Methods. M.I.T. Press.
• Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science, 237(4820), 1317–1323.

Video lectures: https://meehl.umn.edu/video 

Faust, D., & Meehl, P. E. (1992). Using scientific methods to resolve questions in the history and philosophy of science: Some illustrations. Behavior Therapy, 23(2), 195–211. https://doi.org/10.1016/S0005-7894(05)80381-8

Serlin, R. C., & Lapsley, D. K. (1985). Rationality in psychological research: The good-enough principle. American Psychologist, 40(1), 73–83. https://doi.org/10.1037/0003-066X.40.1.73

Meehl, P. E. (1990). Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant it. Psychological Inquiry, 1(2), 108–141. https://doi.org/10.1207/s15327965pli0102_1

Meehl, P. E. (1992). Cliometric metatheory: The actuarial approach to empirical, history-based philosophy of science. Psychological Reports, 71, 339–467.

In advance of the next three episodes discussing the Philosophical Psychology lectures by Paul E. Meehl, we present a brief reading from his autobiography in A history of psychology in autobiography.

• Meehl, P. E. (1989). Paul E. Meehl. In G. Lindzey (Ed.), A history of psychology in autobiography (Vol. 8, pp. 337–389). Stanford, CA: Stanford University Press.

In this episode, we discuss objectivity and disinterestedness in science. We talk about norms, values, interests, and objectivity in research practice, peer review, and hiring decisions. Is it possible to be completely objective? Is objectivity a feature of epistemic products or epistemic processes? And most importantly, how would you objectively rate this podcast?

Shownotes

• Armstrong, J. S. (1979). Advocacy and objectivity in science. Management Science, 25(5), 423–428.
• Declaration of Interest by Stephen Senn: http://senns.uk/Declaration_Interest.htm
• Djørup, S., & Kappel, K. (2013). The norm of disinterestedness in science; a restorative analysis. SATS, 14(2). https://doi.org/10.1515/sats-2013-0009
• Elliott, K. C. (2017). A Tapestry of Values: An Introduction to Values in Science. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780190260804.001.0001
• Feyerabend, Paul. "How to defend society against science." Philosophy: Basic Readings (1975): 261-271.
• Jamieson, K. H., McNutt, M., Kiermer, V., & Sever, R. (2019). Signaling the trustworthiness of science. Proceedings of the National Academy of Sciences, 116(39), 19231–19236. https://doi.org/10.1073/pnas.1913039116
• Janack, M. (2002). Dilemmas of objectivity. Social Epistemology, 16(3), 267-281.
• John, S. (2021). Objectivity in science. Cambridge University Press.
• Merton, R. K. (1973). The sociology of science: Theoretical and empirical investigations. University of Chicago Press.
• Mitroff, I. I. (1974). Norms and Counter-Norms in a Select Group of the Apollo Moon Scientists: A Case Study of the Ambivalence of Scientists. American Sociological Review, 39(4), 579–595. https://doi.org/10.2307/2094423
• Mitroff, I. I. (1974). The subjective side of science: A philosophical inquiry into the psychology of the Apollo moon scientists (First Edition). Elsevier.
• A Russian polar researcher has been charged trying to stab a colleague to death at a remote Antarctic base https://www.businessinsider.com/sergey-savitsky-alleged-attempted-murder-at-antarctic-bellingshausen-2018-10 
• Stamenkovic, P. (2023). Facts and objectivity in science. Interdisciplinary Science Reviews, 1–22. https://doi.org/10.1080/03080188.2022.2150807

In this episode, we discuss the role of criticism in science. When is criticism constructive as opposed to obsessive? What are the features of fair and useful scientific criticism? And should we explicitly teach junior researchers to both give and accept criticism?

Shownotes:

• Babbage, C. (1830). Reflections on the Decline of Science in England: And on Some of Its Causes.
• Prasad, Vinay, and John PA Ioannidis. "Constructive and obsessive criticism in science." European journal of clinical investigation 52.11 (2022): e13839.
• Lakatos, I. (1968, January). Criticism and the methodology of scientific research programmes. In Proceedings of the Aristotelian society (Vol. 69, pp. 149-186). Aristotelian Society, Wiley.
• LOWI: https://lowi.nl/en/home/ As an independent advisory body it plays a role in the complaints procedure about alleged violations of principles of research integrity.
• Holcombe, A. O. (2022). Ad hominem rhetoric in scientific psychology. British Journal of Psychology, 113(2), 434–454. https://doi.org/10.1111/bjop.12541
• Daniel C. Dennett: I've Been Thinking https://wwnorton.com/books/9780393868050 
• Phillip Stark textbook chapter on logical fallacies: https://www.stat.berkeley.edu/~stark/SticiGui/Text/reasoning.htm 
• Gelman, A., & Tuerlinckx, F. (2000). Type S error rates for classical and Bayesian single and multiple comparison procedures. Computational Statistics, 15(3), 373–390. https://doi.org/10.1007/s001800000040
• Popper, K. R. (1959). The logic of scientific discovery. Routledge.
• PubPeer: https://pubpeer.com

In this episode, we continue discussing Dubin’s 8-step method for theory building. We discuss the measurement of theoretical constructs, using logical propositions to make falsifiable predictions from theories, and the importance of specifying boundary conditions. 

Shownotes

• Jaccard, J., & Jacoby, J. (2010). Theory Construction and Model-building Skills: A Practical Guide for Social Scientists. Guilford Press.
• McGuire, W. J. (1973). The yin and yang of progress in social psychology: Seven koan. Journal of Personality and Social Psychology, 26(3), 446–456. https://doi.org/10.1037/h0034345
• Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on Generality (COG): A Proposed Addition to All Empirical Papers. Perspectives on Psychological Science, 12(6), 1123–1128. https://doi.org/10.1177/1745691617708630
• Norm Macdonald: The Professor of Logic
• Raven Paradox: https://platonicrealms.com/encyclopedia/Hempels-Ravens-Paradox 
• Pavlov, I. (1936). Bequest of Pavlov to the Academic Youth of His Country. Science, 83(2155), 369–370. https://doi.org/10.1126/science.83.2155.369

In this episode we discussed the 8-step method of theory building proposed by Robin Dubin in his classic 1969 book Theory Building.

Shownotes

• Dubin, R. (1969). Theory building. Free Press. http://catalog.hathitrust.org/api/volumes/oclc/160506.html
• Lynham, S. A. (2002). Quantitative Research and Theory Building: Dubin’s Method. Advances in Developing Human Resources, 4(3), 242–276. https://doi.org/10.1177/15222302004003003
• Elms, A. C. (1975). The crisis of confidence in social psychology. American Psychologist, 30(10), 967.
• Meehl, P. E. (1978). Theoretical Risks and Tabular Asterisks: Sir Karl, Sir Ronald, and the Slow Progress of Soft Psychology. Journal of Consulting and Clinical Psychology, 46(4), 806–834. https://doi.org/10.1037/0022-006X.46.4.806
• Swedberg, R. (2014). The art of social theory. Princeton University Press.
• Ben Wright: https://en.wikipedia.org/wiki/Benjamin_Drake_Wright
• Yarkoni, T., & Westfall, J. (2017). Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning. Perspectives on Psychological Science, 12(6), 1100–1122. https://doi.org/10.1177/1745691617693393
• Isaac, M. G., Koch, S., & Nefdt, R. (2022). Conceptual engineering: A road map to practice. Philosophy Compass, 17(10), e12879. https://doi.org/10.1111/phc3.12879

In this episode, we discuss the barriers to cumulative science, including inconsistent measurement tools, overreliance on single studies, and the large volume of research publications. Can replications, interdisciplinary collaborations, and prospective meta-analyses help us solve this issue? Can AI solve all our problems?  And do most scientists treat their theories like toothbrushes?

Shownotes

• Opening quote by George Sarton
  • Sarton, G. (1927). Introduction to the History of Science (Vol. 376). 
• Is Science Cumulative? a Physicist Viewpoint: https://link.springer.com/chapter/10.1007/978-1-4020-6279-7_10
• Psychological Methods. (2009). Special Issue: Multi-Study Methods for Building a Cumulative Psychological Science.

• Walter Mischel, Becoming a Cumulative Science 

• Dorothy Bishop - Why we need cumulative science (AIMOS)
• Watkins, J. W. (1984). Science and Skepticism. Princeton University Press.

In today’s episode, we continue our conversation about preregistration. How flexible can we be when we preregister, without increasing flexibility in our analysis? How well do people preregister, and what does a good preregistration look like? And how do we deal with deviations from preregistrations?

Shownotes

• Dubin, R. (1969). Theory building. Free Press. His full quote is: "There is no more devastating commendation that the self-designated theorist makes of the researcher than to label his work purely descriptive". 
• Claesen, A., Gomes, S., Tuerlinckx, F., & Vanpaemel, W. (2021). Comparing dream to reality: An assessment of adherence of the first generation of preregistered studies. Royal Society Open Science, 8(10), 211037. https://doi.org/10.1098/rsos.211037
• Akker, O. van den, Bakker, M., Assen, M. A. L. M. van, Pennington, C. R., Verweij, L., Elsherif, M., Claesen, A., Gaillard, S. D. M., Yeung, S. K., Frankenberger, J.-L., Krautter, K., Cockcroft, J. P., Kreuer, K. S., Evans, T. R., Heppel, F., Schoch, S. F., Korbmacher, M., Yamada, Y., Albayrak-Aydemir, N., … Wicherts, J. (2023). The effectiveness of preregistration in psychology: Assessing preregistration strictness and preregistration-study consistency. MetaArXiv. https://doi.org/10.31222/osf.io/h8xjw
• Sequential analysis and alpha spending functions https://lakens.github.io/statistical_inferences/10-sequential.html 
• Bishop, D. V. M. (2018). Fallibility in Science: Responding to Errors in the Work of Oneself and Others. Advances in Methods and Practices in Psychological Science, 2515245918776632. https://doi.org/10.1177/2515245918776632
• FDAAA Trial Tracker https://fdaaa.trialstracker.net 
• Ensinck, E., & Lakens, D. (2023). An Inception Cohort Study Quantifying How Many Registered Studies are Published. PsyArXiv. https://doi.org/10.31234/osf.io/5hkjz
• Quantitude episode on preregistration https://quantitudepod.org/s3e07-in-defense-of-researcher-degrees-of-freedom/ 
• Lakens, D. (2023). When and How to Deviate from a Preregistration. PsyArXiv. https://doi.org/10.31234/osf.io/ha29k 

In this two part episode we discuss the fine art of preregistration. We go back into the history of preregistration, its evolution, and current use. Do we preregister to control the Type 1 error rate, or to show that we derived our prediction from theory a priori? Can and should we preregister exploratory or secondary data analysis? And how severe is the issue of severe testing?

Shownotes

• ClinicalTrials.gov
• You can preregister on AsPredicted and the OSF
• Johnson, M. (1975). Models of Control and Control of Bias. European Journal of Parapsychology, 36–44.
• SPIRIT Checklist
• Bishop, D. V. M. (2018). Fallibility in Science: Responding to Errors in the Work of Oneself and Others. Advances in Methods and Practices in Psychological Science, 1(3), 432–438. https://doi.org/10.1177/2515245918776632
• FDA trials tracker: https://fdaaa.trialstracker.net 
• Ensinck, E., & Lakens, D. (2023). An Inception Cohort Study Quantifying How Many Registered Studies are Published. PsyArXiv. https://doi.org/10.31234/osf.io/5hkjz
• van den Akker, O. R., van Assen, M. A. L. M., Enting, M., de Jonge, M., Ong, H. H., Rüffer, F., Schoenmakers, M., Stoevenbelt, A. H., Wicherts, J. M., & Bakker, M. (2023). Selective Hypothesis Reporting in Psychology: Comparing Preregistrations and Corresponding Publications. Advances in Methods and Practices in Psychological Science, 6(3), 25152459231187988. https://doi.org/10.1177/25152459231187988
• Claesen, A., Gomes, S., Tuerlinckx, F., & Vanpaemel, W. (2021). Comparing dream to reality: An assessment of adherence of the first generation of preregistered studies. Royal Society Open Science, 8(10), 211037. https://doi.org/10.1098/rsos.211037
• Bakan, D. (1966). The test of significance in psychological research. Psychological Bulletin, 66(6), 423–437. https://doi.org/10.1037/h0020412
• Rosenthal, R. (1966). Experimenter effects in behavioral research. Appleton-Century-Crofts.
• Johnson, M. (1975). Models of Control and Control of Bias. European Journal of Parapsychology, 36–44.
• de Groot, A. D. (1969). Methodology. Mouton & Co.
• Claesen, A., Lakens, D., Vanpaemel, W., & Dongen, N. van. (2022). Severity and Crises in Science: Are We Getting It Right When We’re Right and Wrong When We’re Wrong? PsyArXiv. https://doi.org/10.31234/osf.io/ekhc8

In the first episode of 2024, we discuss the double-edged sword: reverence to authority. Should scientists respect others on whose shoulders they stand? Or should they be wary of appeal to authority? How should scientists deal with other sources of authority in science, like for example, the government or academic societies? And how can we differentiate true expertise from mere authority?  Enjoy. 

Shownotes

• Frank, P. (1956). The role of authority in the interpretation of science. Synthese, 10, 335–338.
• Barber, B. (1952). Science and the social order. Glencoe, Ill. : Free Press. http://archive.org/details/sciencesocialord0000barb
• Barber, B. (1961). Resistance by Scientists to Scientific Discovery. Science, 134(3479), 596–602.
• Kitcher, P. (1992). Authority, deference, and the role of individual reasoning in science. In E. Mcmullin (Ed.), The social dimensions of science. Notre Dame: The University of Notre Dame Press
• Polanyi, M. (1962). The republic of science. Minerva, 1(1), 54–73
• The practice of two-spaces after the end of a sentence comes from when type-writers used monospaced typefaces: https://slate.com/technology/2011/01/two-spaces-after-a-period-why-you-should-never-ever-do-it.html 

The Fixation of Belief. Charles S. Peirce. Popular Science Monthly 12 (November 1877), 1-15.

• http://peirce.org/writings/p107.html 

In this second installment of The Anticreativity Letters, we continue discussing the Tempter's tactics for stifling creativity and how to overcome them. 

In the first of a two-part episode, we discuss The Anticreativity Letters by Richard Nisbett, in which a senior "tempter" advises a junior tempter on ways to prevent a young psychologist from being a productive and creative scientist.

• Nisbett, R. E. (1990). The anticreativity letters: Advice from a senior tempter to a junior tempter. American Psychologist, 45(9), 1078–1082.

• BMJ Christmas issue: https://www.bmj.com/about-bmj/resources-authors/article-types/christmas-issue
  
• Quote by Ira Glass: https://www.goodreads.com/quotes/309485-nobody-tells-this-to-people-who-are-beginners-i-wish

A reading of:

Nisbett, R. E. (1990). The anticreativity letters: Advice from a senior tempter to a junior tempter. American Psychologist, 45(9), 1078–1082. https://doi.org/10.1037/0003-066X.45.9.1078

In today’s episode, we discuss the role of mentorship in academia. What are the characteristics of a good mentor-mentee relationship? What are the qualities of good mentors and good mentees? Does mentorship play a role in the development of scientific knowledge? And could mentors and mentees benefit from couples therapy?

Note: D.I.H.C is pronounced 'dick' but this is meant to be a family-friendly podcast :)

Shownotes

• https://www.psychologytoday.com/us/blog/emotional-fitness/201303/10-things-your-relationship-needs-thrive

• Roberts, L. R., Tinari, C. M., & Bandlow, R. (2019). An effective doctoral student mentor wears many hats and asks many questions. International Journal of Doctoral Studies, 14, 133.

• Sarabipour, S., Niemi, N. M., Burgess, S. J., Smith, C. T., Filho, A. W. B., Ibrahim, A., & Clark, K. (2023). Insights from a survey of mentorship experiences by graduate and postdoctoral researchers (p. 2023.05.05.539640). bioRxiv. https://doi.org/10.1101/2023.05.05.539640

In this episode, we discuss the role of trust in science. Why should we verify but trust other scientists? What are the prerequisites for building trust within the scientific community? Who is ultimately responsible for verifying our claims and practices that bolster those claims? And should we give personality tests to everyone who enters academia?

Shownotes

• Hardwig, J. (1991). The role of trust in knowledge. The Journal of Philosophy, 88(12), 693–708.

• Hendriks, F., Kienhues, D., Bromme, R. (2016). Trust in Science and the Science of Trust. In: Blöbaum, B. (eds) Trust and Communication in a Digitized World. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-28059-2_8 

• Strand, J. F. (2023). Error tight: Exercises for lab groups to prevent research mistakes. Psychological Methods, No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/met0000547

• Duygu Uygun-Tunç: Trust and criticism in science, Part I: Critical rationalism instead of organized skepticism: https://uyguntunc.wordpress.com/2020/10/30/trust-and-criticism-in-science-part-i-critical-rationalism-instead-of-organized-skepticism/

• Vazire, S. (2017). Quality Uncertainty Erodes Trust in Science. Collabra: Psychology, 3(1), 1. https://doi.org/10.1525/collabra.74

• Wicherts, J. M. (2011). Psychology must learn a lesson from fraud case. Nature, 480(7375), Article 7375. https://doi.org/10.1038/480007a

• Fricker, E. (2002). Trusting others in the sciences: A priori or empirical warrant? Studies in History and Philosophy of Science Part A, 33(2), 373–383. https://doi.org/10.1016/S0039-3681(02)00006-7

In advance of our episode Verify but Trust, a reading of John Hardwig's paper The Role of Trust in Science. 

• Hardwig, J. (1991). The role of trust in knowledge. The Journal of Philosophy, 88(12), 693–708.

In today’s episode, we discuss the peer review process---its history, its present, and its future. How does peer review work? How long has it existed in its current form? Should reviews be open and signed? Should reviewers be paid for their hard labor? Should we just abandon the peer review process, or does it have a positive role to play? 

Shownotes

• Peer Community in Registered Reports: https://rr.peercommunityin.org/

• Suggestion to Darwin to publish a book about pigeons instead of The Origins of Species: https://www.darwinproject.ac.uk/letter/DCP-LETT-2457A.xml

• Baldwin, M. (2018). Scientific Autonomy, Public Accountability, and the Rise of “Peer Review” in the Cold War United States. Isis, 109(3), 538–558. https://doi.org/10.1086/700070

• Burnham, J. C. (1990). The evolution of editorial peer review. JAMA, 263(10), 1323–1329.

In this episode, we discuss Quantifauxcation, described by statistician Philip Stark as “situations in which a number is, in effect, made up, and then is given credence merely because it is quantitative.” We give examples of quantifauxcation in psychology, including errors of the third kind. We spend the second half of the podcast discussing how to develop quantitative measures that are meaningful and bridge the divide between qualitative and quantitative observations.

Shownotes

• Statistics textbook by Philip Stark.

• Stark, P. B. (2022). Pay No attention to the model behind the curtain. Pure and Applied Geophysics, 179(11), 4121–4145. https://doi.org/10.1007/s00024-022-03137-2 

• Burgess, E. W. (1927). Statistics and case studies as methods of sociological research, Vol 12(3), 103-120. (Thanks to Andy Grieve!)

• Nick Brown's role in pointing out flaws in the positivity ratio.

• Retraction notice of the positivity ratio paper.

• Blog by Tania Lombrozo on nonsensical formulas in abstracts.

• Kimball, A. W. (1957). Errors of the third kind in statistical consulting. Journal of the American Statistical Association, 52(278), 133–142. https://doi.org/10.1080/01621459.1957.10501374

• Type III errors: Philip Stark’s post of Deborah Mayo’s blog

• Brower, D. (1949). The problem of quantification in psychological science. Psychological Review, 56(6), 325–333. https://doi.org/10.1037/h0061802

• Guttman scales

• Wilson, M. (2023). Constructing measures: An item response modeling approach. Taylor & Francis.

• Wilson, M., Bathia, S., Morell, L., Gochyyev, P., Koo, B. W., & Smith, R. (2022). Seeking a better balance between efficiency and interpretability: Comparing the likert response format with the Guttman response format. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000462

• Bhatti, H.A., Mehta, S., McNeil, R., Wilson, M. (2023). A scientific approach to assessment: Rasch measurement and the four building blocks. In X. Liu & W. Boone (Eds.), Advances in Applications of Rash Measurement in Science Education. Springer Nature. 

In preparation for a discussion on Quantifauxcation, a reading of 'Problem-Centering vs. Means-Centering in Science' by Abraham H. Maslow (1946). 

• Maslow, A. H. (1946). Problem-Centering vs. Means-Centering in Science. Philosophy of Science, 13(4), 326–331. https://doi.org/10.1086/286907

In today’s episode, we discuss intellectual vices. How can we tell the difference between justified confidence and unjustified arrogance? How do we deal with feelings of envy or negative comparison with other scientists? What is the difference between building one’s career and careerism? And what do we do about scientists who do not care about the truth? 

Shownotes

• Azrin, N. H., Holz, W., Ulrich, R., & Goldiamond, I. (1961). The control of the content of conversation through reinforcement. Journal of the Experimental Analysis of Behavior, 4, 25–30. https://doi.org/10.1901/jeab.1961.4-25 

• Meehl, P. E. (1967). Theory-testing in psychology and physics: A methodological paradox. Philosophy of Science, 103–115. https://doi.org/10.1086/288135  

• Mitroff, I. I. (1974). Norms and Counter-Norms in a Select Group of the Apollo Moon Scientists: A Case Study of the Ambivalence of Scientists. American Sociological Review, 39(4), 579–595. https://doi.org/10.2307/2094423

• Susan Blackmore: https://en.wikipedia.org/wiki/Susan_Blackmore 

In this episode, we discuss scientific snobbery and the ways in which it affects our interactions with and perceptions of other scientists. What are the reasons for hierarchies among different disciplines, institutions, and approaches to science? What are some ways in which snobbery manifests in science? And is it snobby to not want to present scientific posters? Enjoy. 

Shownotes: 

• Ego and Math (3Blue1Brown)

• M. V. Berry; Regular and irregular motion. AIP Conf. Proc. 15 September 1978; 46 (1): 16–120. https://doi.org/10.1063/1.31417

In this episode, we continue our conversation on the replication crisis⏤Which methodological, theoretical, and practical concerns did psychologists raise half a century ago? What has changed, and what remains the same, during the current crisis? 

Shownotes

• Orne, M. T. (1962). On the social psychology of the psychological experiment: With particular reference to demand characteristics and their implications. American Psychologist, 17(11), 776–783. https://doi.org/10.1037/h0043424

• Rosenthal, R. (1966). Experimenter effects in behavioral research. Appleton-Century-Crofts.

• Gergen, K. J. (1973). Social psychology as history. Journal of Personality and Social Psychology, 26, 309–320. https://doi.org/10.1037/h0034436

• Koole, S. L., & Lakens, D. (2012). Rewarding replications: A sure and simple way to improve psychological science. Perspectives on Psychological Science, 7(6), 608–614. https://doi.org/10.1177/1745691612462586

• Greenwald, A. G. (Ed.). (1976). An editorial. Journal of Personality and Social Psychology, 33(1), 1–7. https://doi.org/10.1037/h0078635

• Ring, K. (1967). Experimental social psychology: Some sober questions about some frivolous values. Journal of Experimental Social Psychology.

• Ledgerwood, A., & Sherman, J. W. (2012). Short, sweet, and problematic? The rise of the short report in psychological science. Perspectives on Psychological Science, 7(1), 60–66.

• Barber, T. X. (1976). Pitfalls in Human Research: Ten Pivotal Points. Pergamon Press.

• Dunnette, M. D. (1966). Fads, fashions, and folderol in psychology. American Psychologist, 21(4), 343–352. https://doi.org/10.1037/h0023535

• Babbage, C. (1830). Reflections on the Decline of Science in England: And on Some of Its Causes. B. Fellowes.

Reading of the chapter "Investigator Data Analysis Effect" from the book:

In this episode, we discuss the replication crisis in psychology which has been an important topic of discussion for the last decade. We revisit some key events from the start of the replication crisis, such as the publication of Daryl Bem's studies on precognition, the paper False Positive Psychology, and the Reproducibility Project and share personal anecdotes about how it was to live through the replication crisis.

Shownotes: 

• Bem, D. J. (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. Journal of Personality and Social Psychology, 100(3), 407–425. https://doi.org/10.1037/a0021524

• Ritchie, S. J., Wiseman, R., & French, C. C. (2012). Failing the Future: Three Unsuccessful Attempts to Replicate Bem’s ‘Retroactive Facilitation of Recall’ Effect. PLOS ONE, 7(3), Article e33423. https://doi.org/10.1371/journal.pone.0033423

• Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science, 22(11), 1359–1366. https://doi.org/10.1177/0956797611417632

• John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science, 23(5), 524–532. https://doi.org/10.1177/0956797611430953

• Fiedler, K., & Schwarz, N. (2016). Questionable Research Practices Revisited. Social Psychological and Personality Science, 7(1), 45–52. https://doi.org/10.1177/1948550615612150
  • NOTE: Daniel says in the podcast the paper below is by Fiedler and Strack - but it is by Fiedler and Schwarz.

• Ebersole, C. R., Mathur, M. B., Baranski, E., Bart-Plange, D.-J., Buttrick, N. R., Chartier, C. R., Corker, K. S., Corley, M., Hartshorne, J. K., IJzerman, H., Lazarević, L. B., Rabagliati, H., Ropovik, I., Aczel, B., Aeschbach, L. F., Andrighetto, L., Arnal, J. D., Arrow, H., Babincak, P., …

• Nosek, B. A. (2020). Many Labs 5: Testing Pre-Data-Collection Peer Review as an Intervention to Increase Replicability. Advances in Methods and Practices in Psychological Science. https://doi.org/10.1177/2515245920958687

• Luttrell, A., Petty, R. E., & Xu, M. (2017). Replicating and fixing failed replications: The case of need for cognition and argument quality. Journal of Experimental Social Psychology, 69, 178–183. https://doi.org/10.1016/j.jesp.2016.09.006

• Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on Generality (COG): A Proposed Addition to All Empirical Papers. Perspectives on Psychological Science, 12(6), 1123–1128. https://doi.org/10.1177/1745691617708630

• Simonsohn, U. (2015). Small Telescopes Detectability and the Evaluation of Replication Results. Psychological Science, 26(5), 559–569. https://doi.org/10.1177/0956797614567341

In this episode we reflect on the role of intelligence in scientist. How much does intelligence matter in science, and which other characteristics might play a role in doing good science? Do scientist need to be extremely intelligent or can anyone do science? And what is the role of stupidity in science? 

Capax Mentis roughly translates to "capacity of mind."

Smriti stupidly messed up her audio so the quality isn't great. Apologies! 

Shownotes

• Schwartz, M. A. (2008). The importance of stupidity in scientific research. Journal of Cell Science, 121(11), 1771. https://doi.org/10.1242/jcs.033340
• Bernal, J. D. (1939). The Social Function Of Science. Routledge.
• Paul Medawar: Advice to a Young Scientist 
• Feynman talking about the uncomfortable feeling of confusion  
• A good scientist always keeps learning – Nobel Laureate Peter Doherty 
• Flatland (1884) by Edwin Abbott Abbott 
• A zero-order correlation simply refers to the correlation between two variables (i.e., the independent and dependent variable) without controlling for the influence of any other variables. Essentially, this means that a zero-order correlation is the same thing as a Pearson correlation.

As prologue to the next episode on how smart one needs to be to be a scientist, we present a reading of chapter 2 "How can I tell if I am cut out to be a scientific research worker?" by Peter B. Medawar from his 1979 book 'Advice to a young scientist'. Our next episode was inspired by the section "Am I brainy enough to be a scientist?"

https://www.google.nl/books/edition/Advice_To_A_Young_Scientist/3fg3DgAAQBAJ

In this episode we discuss Daniel Dennett's distinction between chess, or research worth doing, and 'chmess,'  research not worth doing. We discuss ways to determine whether our research is chess or chmess, and how to avoid being sucked into lines of research we don't particularly care about. 

Shownotes

• Dennett, D. C. (2006). Higher-order truths about chmess. Topoi, 25, 39–41.
• Dunnette, M. D. (1966). Fads, fashions, and folderol in psychology. American Psychologist, 21(4), 343.
  • Folderol means 'a useless ornament or accessory', and is used to indicate something is 'nonsense'. 
• Dweck, C. S. (2022). Mindsets: From bathtubs to hot beliefs to social change. In Kassin, S. (Ed.) Pillars of Social Psychology: Stories and Retrospectives, 213–219. Cambridge University Press. 
• The Kardashian Index

As prologue to the next episode on Chmess, we present a reading of a paper by Daniel C. Dennett: 

• Dennett, D. C. (2006). Higher-order truths about chmess. Topoi, 25, 39–41.

In today's episode, we discuss vocational virtues⸺scientific principles that should guide the behavior of scientists. We discuss whether we agree with values put forth by numerous scientists, including Ivan Pavlov, Peter Medawar, Santiago Ramón y Cajal, Barry Schwartz, among others, and share our own. 

Correction: At 56:24, Smriti mentions the book This is Biology, which is written by Ernst Mayr, not E.O. Wilson. 

Shownotes

• Pavlov, I. (1936). Bequest of Pavlov to the Academic Youth of His Country. Science, 83(2155), 369–370. https://doi.org/10.1126/science.83.2155.369
• Schwartz, B. (2022). Science, scholarship, and intellectual virtues: A guide to what higher education should be like. Journal of Moral Education, 51(1), 61-72.
• Robert T. Pennock: An Instinct for Truth: Curiosity and the Moral Character of Science
• Merton, R. K. (1942). A Note on Science and Democracy. Journal of Legal and Political Sociology, 1, 115–126.
• Schwartz, B. (1990). The creation and destruction of value. American Psychologist, 45(1), 7.
• Paul Medawar: Advice to a Young Scientist 
• Ernst Mayr. This is Biology
• Santiago Ramón y Cajal: Advice for a Young Investigator
• Bernal, J. D. (1939). The Social Function Of Science. Routledge. 
• Weber, M. (1917/1958). Science as a Vocation. Daedalus, 87(1), 111–134.
• E.O. Wilson: Letters to a Young Scientist

As prologue to the next episode on vocational virtues, we present a reading of a paper by Barry Schwartz: 

Schwartz, B. (2022). Science, scholarship, and intellectual virtues: A guide to what higher education should be like. Journal of Moral Education, 51(1), 61-72.  https://doi.org/10.1080/03057240.2020.1772211  (Published online: 19 Jun 2020)

You can read the paper here. 

An episode from Smriti's previous podcast with Paul Connor where they discussed the paper with Barry can be found here.  

In this episode, we discuss the topic of research waste. We discuss what it is it that is being wasted and whether we waste fewer scientific resources and talent through coordination, team science, and better planning. 

Shownotes

• Bacon, New Atlantis, 1626: https://www.gutenberg.org/files/2434/2434-h/2434-h.htm 
• Dennett, D. C. (2006). Higher-order truths about chmess. Topoi, 25(1–2), 39–41. https://doi.org/10.1007/s11245-006-0005-2
• Chalmers, I., & Glasziou, P. (2009). Avoidable waste in the production and reporting of research evidence. The Lancet, 374(9683), 86–89.
• Mao's Hundred Flowers Campaign: https://en.wikipedia.org/wiki/Hundred_Flowers_Campaign 
• Glasziou, P., & Chalmers, I. (2018). Research waste is still a scandal—An essay by Paul Glasziou and Iain Chalmers. BMJ, 363, k4645. https://doi.org/10.1136/bmj.k4645
• AltmanDG. The scandal of poor medical research. BMJ 1994;308:283-4. 10.1136/bmj.308.6924.283 8124111
• Bernal, J. D. (1939). The Social Function Of Science. Routledge. http://archive.org/details/in.ernet.dli.2015.188098
• Duckworth, A. L., & Milkman, K. L. (2022). A guide to megastudies. PNAS Nexus, 1(5), pgac214. https://doi.org/10.1093/pnasnexus/pgac214
• Almaatouq, A., Griffiths, T. L., Suchow, J., Whiting, M. E., Evans, J., & Watts, D. J. (2022). Beyond Playing 20 Questions with Nature: Integrative Experiment Design in the Social and Behavioral Sciences. PsyArXiv. https://doi.org/10.31234/osf.io/anjkm

In this bonus episode, Daniël reads Chapter 5 of John Desmond Bernal’s book The Social Function of Science, entitled The Efficiency of Scientific Research in preparation of our upcoming podcast episode on research waste.

• You can read The Social Function of Science by Bernal at the Internet Archive: https://archive.org/details/in.ernet.dli.2015.188098

Shownotes

• Wilson, E. B. (1923). The Statistical Significance of Experimental Data. Science, 58(1493), 93–100. https://doi.org/10.1126/science.58.1493.93

• van Dongen, N. N. N., & van Grootel, L. (2021). Overview on the Null Hypothesis Significance Test. https://doi.org/10.31234/osf.io/hwk4n

• Stark, P. B., & Saltelli, A. (2018). Cargo‐cult statistics and scientific crisis. Significance, 15(4), 40-43.

• Uygun Tunç, D., Tunç, M. N., & Lakens, D. (2023). The epistemic and pragmatic function of dichotomous claims based on statistical hypothesis tests. Theory & Psychology, 09593543231160112. https://doi.org/10.1177/09593543231160112

• Bakan, D. (1966). The test of significance in psychological research. Psychological Bulletin, 66(6), 423–437. https://doi.org/10.1037/h0020412

• Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45(12), 1304–1312. https://doi.org/10.1037/0003-066X.45.12.1304

• Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49(12), 997–1003. https://doi.org/10.1037/0003-066X.49.12.997

• Cohen, J. (1995). The earth is round ( p 

In this episode, we discuss the issue of publication bias. We discuss issues like: Do we learn anything from null results, given the current state of research practices? Is poorly done research still worth sharing with the scientific community? And how can we move toward a system where null results are informative and worth publishing?

Shownotes

• Bones, A. K. (2012). We Knew the Future All Along Scientific Hypothesizing is Much More Accurate Than Other Forms of Precognition—A Satire in One Part. Perspectives on Psychological Science, 7(3), 307–309. https://doi.org/10.1177/1745691612441216

• Carter, E. C., & McCullough, M. E. (2014). Publication bias and the limited strength model of self-control: Has the evidence for ego depletion been overestimated? Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00823

• Greenwald, A. G. (1975). Consequences of prejudice against the null hypothesis. Psychological Bulletin, 82(1), 1–20. https://doi.org/10.1037/h0076157

• Fidler, F., Singleton Thorn, F., Barnett, A., Kambouris, S., & Kruger, A. (2018). The epistemic importance of establishing the absence of an effect. Advances in Methods and Practices in Psychological Science, 1(2), 237-244.

• Pickett, J. T., & Roche, S. P. (2017). Questionable, Objectionable or Criminal? Public Opinion on Data Fraud and Selective Reporting in Science. Science and Engineering Ethics, 1–21. https://doi.org/10.1007/s11948-017-9886-2

• Scheel, A. M., Schijen, M. R. M. J., & Lakens, D. (2021). An Excess of Positive Results: Comparing the Standard Psychology Literature With Registered Reports. Advances in Methods and Practices in Psychological Science, 4(2), 25152459211007468. https://doi.org/10.1177/25152459211007467

• Sterling, T. D. (1959). Publication Decisions and Their Possible Effects on Inferences Drawn from Tests of Significance—Or Vice Versa. Journal of the American Statistical Association, 54(285), 30–34. JSTOR. https://doi.org/10.2307/2282137

• The FDA Trial tracker to see which trials have not shared their results: https://fdaaa.trialstracker.net/ 

In this episode, we discuss physicist Richard Feynman’s famous speech ‘Cargo Cult Science,’ which refers to work that has all the affectations of science without the actual application of the scientific method. We also discuss topics like: What is pathological science? How might cargo cult science and pathological be different from pseudo-science? How do we know whether or not we’re in a cargo cult, and what can we do to make sure we're not fooling ourselves?

Shownotes

• Cargo Cult Science (Feynman, 1974)

• Gergen, K. J. (1973). Social psychology as history. Journal of personality and social psychology, 26(2), 309–320.

• Langmuir, I. (1989). Pathological science. Research-Technology Management, 32(5), 11-17.

• Sabine Hossenfelder. No one in physics dare say so, but the race to invent new particles is pointless. The Guardian.

• Young, P. T. (1932). Relative food preferences of the white rat. Journal of Comparative Psychology, 14(3), 297.

• Young, P. T. (1941). The experimental analysis of appetite. Psychological Bulletin, 38(3), 129.

In this bonus episode, we present a reading of the famous speech by physicist Richard Feynman on "science that isn't science," Cargo Cult Science, which will be the topic of the next episode. Enjoy. 

In this episode we discuss regulatory bodies their influence on the generation and dissemination of knowledge. Should regulatory bodies have the authority to affect the topics and methods of science? Is more highly regulated research actually better? And should we just give up on our own lines of research and become potato researchers? 

Shownotes

• Kitcher, P. (2001). Science, truth, and democracy. Oxford University Press.

• Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute (CPRI)

• Emergence of the NIH 

• DARPA SCORE

• Lakens, D. (2023). Is my study useless? Why researchers need methodological review boards. Nature, 613(7942), 9-9.

• PSA: Legate, N., Ngyuen, T. V., Weinstein, N., Moller, A., Legault, L., Vally, Z., ... & Ogbonnaya, C. E. (2022). A global experiment on motivating social distancing during the COVID-19 pandemic. Proceedings of the National Academy of Sciences, 119(22).

In this episode, we discuss the importance of consensus in science, both as means of establishing true knowledge and for determining which research questions might be worth pursuing. We also discuss barriers to reaching consensus and the different frameworks that are currently employed for trying to reach consensus among important stakeholders. 

Shownotes

• The Popper quote is from: Popper, K. R. (1959). The logic of scientific discovery. Routledge.

• The Polanyi quote is from: Polanyi, M. (1950). Freedom in Science. Bulletin of the Atomic Scientists, 6(7), 195–198. https://doi.org/10.1080/00963402.1950.11461263

• 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.

• The Many Smiles collaboration: Coles, N. A., et al., (2020). The Many Smiles collaboration: A multi-Lab foundational test of the facial feedback hypothesis. Nature Human Behaviour. https://doi.org/10.31234/osf.io/cvpuw

• Paul Meehl's 50 year rule: Meehl, P. E. (1992). Cliometric metatheory: The actuarial approach to empirical, history-based philosophy of science. Psychological Reports, 71, 339–339.

• Mulkay, M. (1978). Consensus in science. Social Science Information, 17(1), 107-122.

• Deliberative Polling

• Laudan, L. (1986). Science and values: The aims of science and their role in scientific debate. Univ of California Press.

In this episode, we discuss the insatiable itch to publish, starting with a quote from 1927 by sociologist Clarence Case on the dictum “Publish or perish.” We discuss ways in which individual goals to publish conflict with the broader scientific goal of producing useful knowledge. We also question the assumptions behind the notion that publishing less would be beneficial for science.

Shownotes

• Case, C. M. (1927). Scholarship in sociology. Sociology and Social Research, 12, 323-340 (Publish or perish)
  
  
• Phaf, R. H. (2020). Publish less, read more. Theory & Psychology, 30(2), 263–285. https://doi.org/10.1177/0959354319898250

• The term "insanabile scribendi cacoethes" comes from: Merton, R. K. (1968). The Matthew effect in science: The reward and communication systems of science are considered. Science, 159(3810), 56-63.

In this episode, we discuss the role of eminence in science. What ask questions like: What makes scientists eminent? What role does eminence play in science? Can eminence be spread across scientific teams instead of individuals? And how can we recognize and applaud scientists for their contributions, while avoiding conferring too many benefits on scientists who do become eminent?

Shownotes

• Eminent psychologists of the 20th century

• Intel - Our rock stars aren't like your rock stars

In our third episode, we discuss confirmation bias, which affects not only how scientists generate and test their own hypotheses, but also how they evaluate the scientific evidence presented by others. We discuss guardrails against confirmation bias that are already in place, and others that could potentially improve scientific practice if adopted. 

Shownotes

• Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12(3), 129-140.
  
  
• Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220.
  
  
• Mellers, B., Hertwig, R., & Kahneman, D. (2001). Do frequency representations eliminate conjunction effects? An exercise in adversarial collaboration. Psychological Science, 12(4), 269-275.
  
  
• Coles, N. A., March, D. S., Marmolejo-Ramos, F., Larsen, J. T., Arinze, N. C., Ndukaihe, I. L., ... & Liuzza, M. T. (2022). A multi-lab test of the facial feedback hypothesis by the many smiles collaboration. Nature Human Behaviour, 1-12.
  
  
• Dutilh, G., Sarafoglou, A., & Wagenmakers, E. J. (2021). Flexible yet fair: Blinding analyses in experimental psychology. Synthese, 198(23), 5745-5772.

• Sarafoglou, A., Hoogeveen, S., & Wagenmakers, E. J. (2023). Comparing analysis blinding with preregistration in the many-analysts religion project. Advances in Methods and Practices in Psychological Science, 6(1), 25152459221128319. 
• Faster-than-light neutrino anomaly

In our second episode, we discuss the role of skepticism in science, a topic that relates closely to the title of our podcast. Given that the scientific enterprise is essentially an exercise in organized skepticism, how can we maintain a healthy amount of skepticism while also ensuring that scientists don't slip into cynicism or nihilism? 

Shownotes

• Opening quote by Imre Lakatos from Science and Pseudoscience. Hear it from the man himself. 
  
  
• Ego depletion
  
  
• Ioannidis, J. P. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124. https://doi.org/10.1371/journal.pmed.0020124
  
  
• Wacholder, S., Chanock, S., Garcia-Closas, M., El Ghormli, L., & Rothman, N. (2004). Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. Journal of the National Cancer Institute, 96(6), 434-442. DOI: 10.1093/jnci/djh075

• Quote by Debra Mayo. Original reference: Mayo, D. G. (2018). Statistical inference as severe testing: How to get beyond the statistics wars. Cambridge University Press.

In our first episode, we discuss a quote from the preface to The Instauratio Magna (of which Novum Organum is a part), in which Bacon claims that scientists should be motivated to do science for the betterment of mankind, and not for personal motives like fame, fortune, or even fun. 

Here is the tweet (by Heidi Seibold) on academia not being aligned with good scientific practices.

An unedited transcript of the episode can be found here. 

In this introductory episode, Daniël and Smriti share which podcasts they like, why they are starting their own, and how their connection to each other is also tied to podcasting. They also talk about the theme of the podcast, which is inspired by Francis Bacon’s delineation of the scientific method 400 years ago.