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Skip to 0 minutes and 2 secondsA couple of other points, that I think are useful as we think about the spread of these ideas, or making them more attractive or encouraging people to use new tools. Convincing people that the tools are useful to them seems to be a really important incentive. And again, there are different ways to frame, say, writing up a pre-analysis plan. One way to frame it is, “God, it’s this really awful thing you have to do before you write a paper,” and it’s this burden. The other way is, “Hey, it makes your research better.” To think through the design before you actually launch the study.

Skip to 0 minutes and 32 secondsYou're going to find mistakes, you’re gonna improve what you’re doing and you’re going to be more likely to get published. So, to the extent that researchers understand, if it’s true, understand that you can do better research with these methods, that’s going to be a very powerful incentive to adopt them And again, the other thing that’s going to encourage the spread of new tools, is gonna be training the next generation. Really, you know, having these tools disseminate widely. Encourage people to think about them and use them.

Skip to 1 minute and 3 secondsIf you don’t have as much at stake, if you don’t have a whole lifetime worth of research that was carried out with methods that may not be as credible, you know why not use the most credible approaches. I think it’s going to be insiders who have built up a lot of work in an area that are going to resist change the most. That’s what Kuhn would say, that’s totally logical. There’s sort of a clean slate with new scholars. You know, these transparency methods, registration, pre-analysis plans, data sharing, all these things could become adopted very quickly. You know in labor economics and development economics, in 5 or 10 years, there was a huge shift in the nature of research.

Skip to 1 minute and 39 secondsSo the same thing could happen. It could be that in a relatively short amount of time these approaches are widely used, but again, there could be divergence. And I think, I had to put money on what’s going to happen, it may look something like this. There may be subgroups of scholars and political science psychology and economics. Subfields where the methods take off and others where they don’t for a while. Maybe, eventually, they’ll spread everywhere.

How to spread transparency

In our final video, I discuss what we can do as scientists, publishers, and policymakers to encourage the spread of research transparency principles. Researchers must be convinced that the tools available to them, such as Pre-Analysis Plans and data repositories, are useful, rather than a burden. Here I discuss what I believe to be the research community’s likely trajectory.

We hope you’ve gained a good understanding of the importance of research transparency, as well as knowledge of some tools you can use to improve your own research and workflow. But our work isn’t done yet. If you’ve enjoyed this course, join the research transparency movement! At the bottom of this page, you can find a downloadable Research Transparency Action Plan. In it, you’ll find actionable steps you can take to make your research more transparent and reproducible right now!

Alos, check out the BITSS website. In addition to a Manual of Best Practices, you’ll also find a wealth of other publicly available research transparency resources, information about grant competitions, and research transparency workshops we coordinate at BITSS, as well as our blog, which features posts from leaders in the open science movement. You can also follow us on Twitter @UCBITSS.

Finally, please take a 10-minute post-course survey so that we, and our partners at FutureLearn can continue to improve our course and the platform. The survey can be accessed at https://goo.gl/4ZaM8X.

Thank you for participating in this course. We hope this isn’t the last we see of you! Onward and open!

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This video is from the free online course:

Transparent and Open Social Science Research

University of California, Berkeley

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