I’ve been going through the evaluation reports and it seems like GWWC might not be as confident in Longview’s Emerging Challenges Fund or the EA Long-Term Future Fund as they are in their choices for GHD and Animal Welfare. The reports for these funds often include some uncertainties, like:

There were several limitations to the evaluation, including various conflicts of interest, limited access to relevant information (in part because the LTFF was not set up to be evaluated in this way), our lack of direct expertise and only limited access to expert external input, and the general difficulty of evaluating funding opportunities in the global catastrophic risk cause area.

We don’t know of any clearly better alternative donation option in reducing GCRs

On the other hand, the Founders Pledge GHD fund wasn’t fully recommended due to more specific methodological issues:

Our belief that FP GHDF evaluations do not robustly demonstrate that the opportunities they fund exceed their stated bar of 10x GiveDirectly in expectation, due to the presence of errors and insufficiently justified subjective inputs we found in some of their BOTECs that could cause the estimated cost-effectiveness to fall below this threshold.

Until I read various posts around the forum and personally looked into what LTFF in particular was funding, I was under the impression—partly from GWWC’s messaging—that the LTFF was at least comparable to a GiveWell or even an ACE. This is partly because GWWC usually recommend their GCR funds at the same time as these other funds.

It might be on me for having the wrong assumptions, so I wrote out my chain of thinking, and I’m keen to find out where we disagree:

1. There might be different evaluation standards between cause areas
2. These varying standards could mean a higher risk of wastage or even fraud in more risky funding opportunities; see this analysis
3. GWWC’s messaging and presentation might not fully convey these differences (the paragraph for these two funds briefly mentions lower tractability and an increased need for specialised grantmaking)
4. It might be challenging for potential donors to grasp these differences without clear communication

(I originally posted this to the 2024 recommendations but thought it might be more constructive / less likely to cause any issues over in this thread)

Goes without saying, but thank you for continuing to promote & facilitate experiments in democratic giving!

That makes so much more sense, thank you!

I was interested in a different presentation of the income estimate data, so I plotted it against the approximate actual income brackets:

I would love to see a deeper version of this graph that includes more of the raw data & has better error bars. I feel like this presentation is much more insightful!

I am surprised that The Humane League is the most well-recognised EA organisation. Is it possible that some respondents felt as if they recognised it, because they were thinking of new wave band The Human League? I noticed that it wasn’t assessed in the same way as 80k.

The IHME have published a new global indicator for depression treatment gaps—the ‘minimally adequate treatment rate’.

It’s defined using country-level treatment gap data, and then extrapolated to missing countries using Bayesian meta-regression (combined with other GBD data; there’s already a critique paper on this methodology FWIW).

Do you have a sense of the acceptability rates (i.e. what proportions of the treatment population moderately decreased their meat consumption)? Additionally, how did you account for selection effects (i.e. if a study includes vegetarians, those participants presumably wouldn’t see behaviour change)?

My mental model right now is that some small proportion of Western populations are amenable to meat reductions, with a sharp fall-off after this. Using these techniques on less aware populations might work, but we could assume that most high-income Western populations have already been exposed to these techniques and made up their minds. Averaged over a study, seeing a handful of participants change their minds in moderate ways would show a small effect size, or none at all, depending on the recruited population.

But I know very little about this area, so I assume the above is wrong. I just wanted to know in what ways, and what’s borne out by the data you have.

2 weeks out from the new GiveWell/GiveDirectly analysis, I was wondering how GHD charities are evaluating the impact of these results.

For Kaya Guides, this has got us thinking much more explicitly about what we’re comparing to. GiveWell and GiveDirectly have a lot more resources, so they can do things like go out to communities and measure second order and spillover effects.

On the one hand, this has got us thinking about other impacts we can incorporate into our analyses. Like GiveDirectly, we probably also have community spillover effects, we probably also avert deaths, and we probably also increase our beneficiaries’ incomes by improving productivity. I suspect this is true for many GHD charities!

On the other, it doesn’t seem fair to compare our analysis on individual subjective wellbeing to GiveDirectly’s analysis that incorporates many more things. Unless we believed that GiveDirectly is likely to be systematically better, it’s not the case that many GHD charities got 3–4× less cost-effective relative to cash transfers overnight, they may just count 3–4× less things! So I wonder if the standard cash transfers benchmark might have to include more nuance in the near-term. Kaya Guides already only makes claims about cost-effectiveness ‘at improving subjective wellbeing’ to try and cover for this.

Are other GHD charities starting to think the same way? Do people have other angles on this?

I think this is good. I think it would be valuable for most people here to read a criticism from an uncommon angle, even if you disagree with the author’s argument. Thank you for sharing it here!