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.

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