How do you square:
The order was: I learned about one situation from a third party, then learned the situation described in TIME, then learned of another situation because I asked the woman on a hunch, then learned the last case from Owen.
with
No other women raised complaints about him to me, but I learned (in some cases from him) of a couple of other situations where his interactions with women in EA were questionable.
Emphasis mine. (Highlighting your first statement implies he informed you of multiple cases and this statement implies he only informed you of one)
Thanks - I've already commented. I'm pretty disappointed that Owen resigned 3 days before my comment and I was filibustered. (I've already commented there about the timeline, very curious to know what can possibly have been going on during that period other than getting together a PR strategy).
Please would someone be able to put together a slightly more fleshed out timeline of who knew what and when. Best I can tell is:
I know I'm probably being dense here, but would it be possible for you to share what the other possibilities are?
Edit: I guess there's "The person doesn't have the role, but we are bound by some kind of confidentiality we agreed when removing them from post"
Just bumping this in case you've forgotten. At the moment there only seem to be two possibities: 1/ you forgot about this comment or 2/ the person does still have a role "picking out promising students" as Peter asked. I'm currently assuming it's 2, and I imagine other people are too.
iirc, there is access to the histogram, which tells you how many people predicted each %age. I then sampled k predictors from that distribution.
"k predictors" is the number of samples I was looking at
">N predictors" was the total number of people who predicted on a given question
what does SD stand for? Usually I would expect standard deviation?
Yes, that's exactly right. The HLI methodology consists of polling together a bunch of different studies effect-sizes (measured in standard deviations) and then converting those standard deviations into WELLBYs. (By mulitplying by a number ~2).
No bet from me on the Ozler tria
Fair enough - I'm open to betting on this with anyone* fwiw. * anyone who hasn't already seen results / involved in the trial ofc
Any intervention is extremely sensitive to implementation details, whether deworming or nets or psychotherapy.
Yes, I'm sorry if my comment appeared to dismiss this fact as I do strongly agree with this.
Maybe some interventions are easier to implement than others, and there might be more variance in the effectiveness of psychotherapy compared with net distribution (although I doubt that, I would guess less variance than nets) but all are very sensitive to implementation details.
This is pretty much my point
I'd be interested in you backing up this comment with a bit explanation if you have time (all good if not!). I know this isn't your job and you don't have the time that Joel has, but what is it that has led you to conclude that the numbers are "on the order (or lower) than cash transfers"? Is this comment based on intuition or have you done some maths?
I haven't done a bottom up analyses, more I have made my own adjustments to the HLI numbers which get me to about that level:
I think the fairest way to resolve this would be to bet on the effect-size of the Ozler trial. Where would you make me 50/50 odds in $5k?
My analysis of StrongMinds is based on a meta-analysis of 39 RCTS of group psychotherapy in low-income countries. I didn’t rely solely on StrongMinds’ own evidence alone, I incorporated the broader evidence base from other similar interventions too. This strikes me, in a Bayesian sense, as the sensible thing to do.
I agree, but as we have already discussed offline, I disagree with some of the steps in your meta-analyses, and think we should be using effect sizes smaller than the ones you have arrived at. I certainly didn't mean to claim in my post that StrongMinds has no effect, just that it has an effect which is small enough that we are looking at numbers on the order (or lower) than cash-transfers and therefore it doesn't meet the bar of "Top-Charity".
I think Simon would define “strong evidence” as recent, high-quality, and charity-specific. If that’s the case, I think that’s too stringent. That standard would imply that GiveWell should not recommend bednets, deworming, or vitamin-A supplementation.
I agree with this, although I think the difference here is I wouldn't expect those interventions to be as sensitive to the implementation details. (Mostly I think this is a reason to reduce the effect-size from the meta-analysis, whereas HLI thinks it's a reason to increase the effect size).
As a community, I think that we should put some weight on a recommendation if it fits the two standards I listed above, according to a plausible worldview (i.e., GiveWell’s moral weights or HLI’s subjective wellbeing approach). All that being said, we’re still developing our charity evaluation methodology, and I expect our views to evolve in the future.
I agree with almost all of this. I don't think we should use HLI's subjective wellbeing approach until it is better understood by the wider community. I doubt most donors appreciate some of the assumptions the well-being approach makes or the conclusions that it draws.
I summarised a little bit how various organisations in the EA space aggregate QALY's over time here.
I think this post by Open Phil is probably related to what you're asking for and I would also recommend the GiveWell post on the same topic
I think this is still generally seen as a bit of an open question in the space