Currently, during research programs such as MATS, many impactful AI Safety projects are being worked on

I think you could get to the problem faster than this. As I understand it, you're trying to motivate the shared repo by thinking about all of the duplicated work happening across the community & how valuable it would be for people trying to learn this style of research for the first time to work from a shared foundation. 

I think this is a pretty complex problem and needs to be called out more explicitly. Something like:

[For many early-career researchers, there's an unnecessarily steep learning curve for even figuring out what good norms for their research code should look like in the first place. We're all for people learning and trying things for themselves, but they should do that on top of a solid, trusted, well documented foundation. That's why things like e.g. the ARENA curriculum are so valuable.

But there aren't standardised templates/repos for doing most of the work in empirical alignment research, and we think this probably slows down new researchers a lot, and requires them to unnecessarily duplicate work and make mistakes that they might not notice are slowing them down. ML research in general involves so much tinkering and figuring things out, that building from a strong template can be a meaningful speedup and provide a helpful initial learning experience. 

For the MATS 7 scholars mentored by Ethan, Jan, Fabien, Mrinank, and others from the Anthropic Alignment Science team, we have created....