This is great stuff. I often find it hard to remember a lot of initiatives have happened (despite having read 80% of this list already) so this timeline is a good reference

As an aside, I think others may benefit from reading about diversity initiatives outside EA to remember this is hard problem. It's totally consistent for EA to be above-the-curve on this and still not move the needle much (directionally I think those two things are true but not confident on magnitudes), so linking some stuff I've been reading lately:

• DEI Deconstructed: Your No-Nonsense Guide to Doing the Work and Doing It Right has two neat chapters at the beginning: one on corporate initiatives over the past 10 years and another on US initiatives since World War II. The tidbits on US military diversity initiatives (and their mixed results) were new to me and sadly not something I see talked about much elsewhere. The rest of the book seemed to be a corporate strategy workbook which I didn't find useful but others might.
• Affirmative Action and the Quality-Fit Trade-Off explores the stronger forms of affirmative action practiced at law school + elite undergraduate universities. It summarizes the economic theory and evidence on whether these stronger forms can "backfire" for minority students. Ultimately, it's hard to say but mild forms seem good. Plato Stanford Encylopedia of Philosophy takes a legal and philosophical look at how the justification and practice for affirmative action has shifted over time.

Echoing what Eva said, I think you should consider waiting a year then apply for IDE / applied econ masters. An IDE program is probably the right fit given your goals, but I don't know any beyond Yale's IDE which expects you to already have worked in development first.

For Applied Econ, I like University of Maryland's Applied Economics Master's program. The program only requires Calc I and is very transparent about what it can do. Dev / global health placements, content, and networking will take a huge hit compared to IDE programs though.

You can use the year in the workforce to save money and take online classes on the side. Believe me, you'll want the savings. Development and global health can be financially tough in early career.

In general, the econ and math background required isn't too high for these type of real-world Master's degrees. Working + getting good grades in first-semester calculus, first-semester probability and stats, intermediate micro, and intermediate macro may be enough for admission.

This is my favorite in the series so far. I really enjoy the tacit knowledge flavor of it and that some of these lessons generalize beyond the CBA domain.

Would also love this. I think a useful contrast will be A/B testing in big tech firms. My amateur understanding is big tech firms can and should run hundreds of “RCTs” because:

• No need to acquire subjects.
• Minimal disruption to business since you only need to siphon off a minuscule portion of your user base.
• Tech experiments can finish in days while field experiments need at least a few weeks and sometimes years.
• If we assume treatments are heavy tailed, then a big tech firm running hundreds of A/B tests is more likely to learn of a weird trick that grows the business when compared to a NGO who may only get one shot. 

Something I've noticed more in the EA Forum is the increase in drive-by professional posts. Organizations will promote a idea, a job posting, or something else. Then they'll engage as long as they're on the front page before bouncing.

That's fine in small amounts or if the author is a regular contributor. But if the author is just stopping by to do their public engagement, then it breaks the illusion of a community.

And for me, that is the aesthetic draw of the forum. It's a place where expects and amateurs alike coexist in the same space, say things that are too rough for professional publication, and then respond to each other in real time.

It's magical and unreal that I can develop these (admittedly shallow and sometimes parasocial) relationships with people. It's cool that I have some chance of getting a leading expert to respond to my quarter-baked comment. It's cool that people sometimes recognize me in real life from what I wrote online.

And that feeling has been decreasing over time, which has made me lean more towards Slack, Discord, or even Twitter for real-time engagement. Meanwhile, I treat the Forum more as a searchable repository for EA-style research

This is a class act in reasoning transparency. I love how easy it is to skim and drill down into things for more detail. Same goes for the pre-print and replication code.

Nits:

• I was confused what calibration meant since I think of this exercise as simulation. To me, calibration is taking some observed data and reverse engineering the elasticity. But this is starting with the elasticity values -- taken from the Bouyssou et al. (2024) meta-analysis -- and seeing how that goes forward in a pretend-tax situation.
• I would have loved to hear about how trustworthy you found the Bouyssou et al. (2024) study, since it's providing the elasticity values for your main analysis. That meta-analysis is really cool and probably the best we have. But it also feels like a bucket of numbers that doesn't think too critically about its inputs. And cross-price elasticity feels like a tricky thing to estimate, something Rethink Priorities wrote about here.

But it's still really cool. I like how simple this is conceptually and that (given some assumptions) carbon tax can be net-positive for all animals.

I love this tiny hearts on pink banner aesthetic. Especially in the middle of winter where I'm at. 

I'm on a pause with donations for some personal and financial reasons, but if I was on the fence or was procrastinating, this absolutely would have pushed me to do so.

Personal reasons why I wished I delayed donations: I started donating 10% of my income about 6 years back when I was making Software Engineer money. Then I delayed my donations when I moved into a direct work path, intending to make up the difference later in life. I don't have any regrets about 'donating right away' back then. But if I could do it all over again with the benefit of hindsight, I would have delayed most of my earlier donations too.

First, I've been surprised by 'necessary expenses'. Most of my health care needs have been in therapy and dental care, neither of which is covered much by insurance. On top of that, friend visits cost more over time as people scatter to different cities, meaning I'm paying a lot more for travel costs. And family obligations always manage to catch me off-caught.

Second, career transitions are expensive. I was counting on my programming skills and volunteer organizing to mean a lot more in public policy and research. But there are few substitutes for working inside your target field. And while everyone complains about Master's degrees, it's still heavily rewarded on the job market so I ultimately caved in and paid for one. 

Finally, I'm getting a lot more from 'money right away' these days. Thanks to some mental health improvements, fancy things are less stressful and more enjoyable than before. The extra vacation, concert, or restaurant is now worth it, and so my optimal spending level has increased. That's not just for enjoyment. My productivity also improves after that extra splurging, whereas before there wasn't much difference in the relaxation benefit I got from a concert and a series of YouTube comedy skits.

If I had to find a lesson here, it's that I thought too much about my altruistic desires changing and not enough on everything else changing. I opted to 'donate right away' to protect against future me rebelling against effective charity, worrying about value drift and stories of lost motivation. In practice, my preference for giving 10% has been incredibly robust. My other preferences have been a lot more dynamic. 

Hey John, this is very cool to read. I like the focus on what surprised you as a founder (and maybe newcomer?) in the mental health field.

I'm curious to hear more about the implementation details. Could you tell me more about the length, intensity, and duration of a typical treatment program? I saw 6 sessions in a graph which makes me think this is once-a-week program for 1-2 hour sessions over 1-2 months

Less sessions is a reliable way to reduce cost, but my understanding is there’s a U-shaped curve to cost-effectiveness here. 1 session doesn't have enough benefits but 100 sessions costs too much and doesn't add more benefit.

Also, are you targeting specific conditions? I see improvement in insomnia but that can arise from a sleep intervention or a general CBT course too

Quickly throwing in a related dynamic. I suspect animal welfare folks have more free time to post online.

Career advancement in animal welfare is much more generalist than global health & development. This means there's not as many career goals to 'grind' towards, leaving more free time for public engagement. Alternative proteins feel like a space where one can specialize, but that's all I can think of. I'd love to know of other examples.

In contrast, global health & development has many distinct specialities that you have to focus on if you want to grow your career. It's not uncommon for someone's career to be built on incredibly narrow topic like, say, the implications of decentralization for regulating groundwater pollution. There are even 'playbooks' for breaking into the space, and they rarely align with writing EA Forum posts, or really any public writing.