Nullius in Verba

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

Philosopher John Hardwig discusses the role of trust in knowledge acquisition, the rise of collaborative research, detecting fraudulent research in science, and the challenges of detecting and punishing fraudulent researchers in the scientific field.

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  

Discussions on the replication crisis in social psychology, historical crises, concerns about negative consequences, publishing replications, the impact of statistical advances and computer technology on data manipulation, the importance of taking action and better science, relevance and real-world consequences

Reading of the chapter "Investigator Data Analysis Effect" from the book: Barber, T. X. (1976). Pitfalls in Human Research: Ten Pivotal Points. Pergamon Press.