(I'm also wondering whether I am being overly concerned with theoretically justifying things!)
I think I would agree with this. It seems like you're trying to demonstrate your knowledge of a particular framework or set of frameworks through this exercise and you're letting that constrain your choices a lot. Maybe that will be a good choice if you're definitely going into academia as a political scientist after this, but otherwise, I would structure the approach around how research happens most naturally in the real world, which is that you have a research question that would have concrete practical value if it were answered, and then you set out to answer it using whatever combination of theories and methods makes sense for the question.
Suggestion: use an expert lens, but make the division you're looking at [experts connected to/with influence in the Biden administration] vs. ["outside" experts].
Rationale: The Biden administration thinks of and presents itself to the public as technocratic and guided by science, but as with any administration politics and access play a role as well. As you noted, the Biden administration did a clear about-face on this despite a lack of a clear consensus from experts in the public sphere. So why did that happen, and what role did expert influence play in driving it? Put another way, which experts was the administration listening to, and what does that suggest for how experts might be able to make change during the Biden administration's tenure?
These both seem like great options! Of the two, I think the first has more to play with as there is a pretty clear delineation between the epistemic vs. moral elements of the second, whereas I think debates about the first have those all jumbled up and it's thus more interesting/valuable to untangle them. I don't totally understand your hesitation so I'm afraid I can't offer much insight there, but with respect to long-term policymaking/shared beliefs, it does seem like the fault lines mapped onto fairly clear pro-free-market vs. pro-redistributive ideologies that drew the types of advocates one would have predicted given that divide.
FYI, there is an existing discussion of this question on the forum here.
Great piece! FYI, I wrote an essay with a similar focus and some of the same arguments about five years ago called All Causes are EA Causes. This article adds some helpful arguments, though, in particular the point about the risk of being over-identified with particular cause areas undermining the principle of cause neutrality itself. I continue to be an advocate for applying EA-style critical thinking within cause areas, not just across them!
Aside from that, neither Open Phil nor Good Ventures are structured as private foundations (Open Phil is an LLC), so Moskowitz & Tuna aren't subject to the 5% payout rule anyway.
This comment made me laugh out loud, all the more so because I couldn't tell whether you were joking.
Perhaps a small number of people who have thought about IIDM carefully and systematically could share their object-level arguments on which approaches seem the most promising to them.
Hi Jonas, I can share some personal reflections on this. Please note that the following are better described as hunches and impressions based on my experiences rather than strongly held opinions -- I'm hopeful that some of the analysis and knowledge synthesis EIP is doing this year will help us and me take more confident positions in the future.
If anyone's thinking seriously about doing as Linch suggests and would like to talk about the nuts and bolts of consulting, feel free to get in touch. I've been consulting independently for four years and am happy to share what I know/discuss potential collaborations.
This is a really great post, and I particularly appreciated the visual diagrams laying out the "problem tree." A number of aspects of what you're writing about (particularly choice of research questions, the lack of connection with the end user in designing research questions, challenges around research/evidence use in the real world, and incentives created by funders and organizational culture) strongly resonated with me. You might find it interesting to read a couple of articles I've written along these lines:
Finally, I just wanted to note a number of overlaps between this post (as well as the meta-science conversation more generally) and issues we're exploring in the improving institutional decision-making community. If you haven't already, I'd like to invite you to join our discussion spaces on Facebook and Slack, and it may be worth a conversation down the line to explore how we can support each other's efforts.