A Guide to Open Science for People Who Are Already Too Busy
No extra reading required
Trying to figure out what’s happening in the open science movement can be overwhelming. The conversation on Twitter can be enlightening, but there’s also rude dudes and near nihilism. On and offline, people can speak as if everyone already knows a dizzying array of acronyms from QRPs to TAIs¹.
Especially if you’re new to the field in general, this “open science” stuff can understandably seem like something to save for later. You’re just trying to learn the basics, and even if the ideas sound interesting they might seem too unapproachable or advanced.
I don’t blame anyone for feeling this way, but as a nearly outgoing PhD student I wish I’d started learning open science principles on Day 1. The learning curve might be a little steeper at the beginning, but I think I would have chosen projects more wisely, prioritized learning different material, and been less hard on myself².
Still, your adviser or department might not know much about open science ideas or prioritize them in training. Worse, your adviser or department might be actively hostile to these reforms ³. Or what if you’re a non-PhD student ECR or later career academic who wants the option of a less time-intensive intro to open science?
There are some awesome open science syllabi available, but they’re mostly designed for full courses taught by a professor. They can be great resources, but what about if you’re already overwhelmed with required reading or other responsibilities?
I’ve put together a tiered syllabus for learning about the replicability crisis, open science principles, and ways to make your own science more open. The first tier is literally “I Only Have Time to Listen to Podcasts While I’m Doing Other Things.”
I’ve also included short(ish)-form versions of suggested readings and a free online course. I highly recommend the other, previously linked syllabi if you have more time, but I understand academics are often time⁴ poor. I’ve also broken the syllabi up into 3 somewhat sequential sections. Hopefully you’ll find this resource useful!
Tier 1: I Only Have Time to Listen to Podcasts While I’m Doing Other Things
- Do We Even Need Open Science?
b. 2 Psychologists, 4 Beers — The Replication Crisis Gets Personal
c. The Black Goat — It’s So Complicated
- How Are We Not Completely Screwed?
a. Everything Hertz — Positive Developments in Biomedical Science
b. Rationally Speaking — Simine Vazire
- What Can I Do?
a. Everything Hertz — Misunderstanding p values/Interpreting effect size
b. The Black Goat — A Blooming, Buzzing Confusion
c. Everything Hertz — Work/Life Balance Parts 1 and 2
Tier 2: Fine, I’ll Read Some Things, But Don’t Make Them Too Long!
- Do We Even Need Open Science?
a. Tal Yarkoni Response to Bem ESP Paper
b. False Positive Psychology Paper
d. Reproducibility Project Paper
- How Are We Not Completely Screwed?
a. Psychology’s Renaissance by Authors of False Positive Psychology
b. Paper Introducing the Psychological Science Accelerator
c. Adoption of Open Access is Increasing
- What Can I Do?
a. Access to Large, Open Datasets — ICPSR
b. Resources for Rigorous Pre-Registration
c. Resource to Create Synthetic Data (If making your raw data open isn’t feasible)
Tier 3: Holy $*%& This Seems Important. Is There a Free, Self-Paced Class I Can Take on Better Understanding How to Interpret Scientific Findings?⁵
Improving Your Statistical Inferences Coursera Course by Daniel Lakens
1 ^ I made “TAIs” up, but even people who are super familiar with open science had a moment of curiosity/panic
2 ^ I bet I’d feel a little this way no matter when I learned open science principles and practices, but I’d still prefer to have learned them earlier
3 ^ Also, these list-serv posts are an excellent disconfirmatory tool if anyone ever says “I can’t imagine there are people who are actively hostile to open science”
4 ^ And money
5 ^ Oh, and as a bonus will it help me learn the programming language R?