Here's one kidney donation confirmed: https://sjer.red/blog/2024/kidney/

So someone should bet the "zero" outcome to zero. I started to do that before noticing I committed not to bet in this market. So I sold the shares and someone else should take the free money.

For reference, according to UNOS, it appears that yearly kidney donations by living people is somewhere between 5 and 6 thousand per year in the US for the last decade

Also this one:

For my own reference, I took some notes on how I should've/could've structured this market: https://manifold.markets/dreev/how-many-distinct-schemes-are-there

How many distinct schemes are there for predicting an open-ended number on Manifold?

Sometimes you want to predict a number but don't know ahead of time what buckets to use or what a reasonable upper bound might be. For example, yesterday I created a market to predict how many people will follow Scott Alexander's example and donate a kidney. I realized, after it was too late for that market, there are better ways to do it and started taking notes for future reference. Then I thought to dogfood it, which is what this market is doing. As I learn about new schemes, I'll add them to the following list. 1. Pre-decided partition By partitition I mean mutually exclusive and exhaustive buckets. This is what I did in the kidney market. There's technically an "Other" option but it's impossible to be chosen unless the answer is somehow a negative number or something. (It just now occurs to me that technically/theoretically that is perfectly possible!) 2. Overlapping thresholds Use thresholds for the answers and allow them to overlap ("any number of answers chosen"). Then you can start with a guess at the median and make two answers, e.g., "less than 10" vs "10 or more". For every answer that has enough probability mass to be interesting, refine it by adding a new answer. Maybe you end up with "less than 10", "10 or more", and "100 or more". If the final answer is, say, 200 then both "10 or more" and "100 or more" are chosen as correct. HT @JamesGrugett 3. Branch from "Other" That's what this market is doing! Stick to "only one answer can be chosen" but keep branching off from the "Other" option. So start with just "One" (or "Zero" if that's a possibility) and "Other" and see how the probability mass gets apportioned. Add new options as desired, always keeping them mutually exclusive and exhaustive. HT evanbd on the Manifold Discord. Resolution Criteria I plan to only add new schemes on the Pareto frontier. In other words, if there's no possible scenario where anyone could prefer a proposed scheme to the ones already on the list, then I won't add it. If a proposed scheme is a special case of an existing one then we'll argue about it in the comments. For example, scheme 1 above is in some sense a special case of scheme 3. But unless I hear a good counterargument in the comments, I'm deeming it to deserve a distinct place on the list as a baseline scheme that a normal person would think to use. This is based on my own judgment. Pointing to a real-world use of a scheme on Manifold will probably convince me. The goal is to make a useful list. Only things that actually work on Manifold by the close date count.

Very similar to your FAQ #3, how do you count people who cite multiple others, including Scott, as inspiration? I'd expect that to be much more common than people who go all the way from uninterested to donating based on Scott's article alone.

@BenjaminCosman Good question. I see two approaches:

1. Pr(pivotal). Taking FAQ3 literally, we estimate the probability Scott was pivotal. For example, if Kyle the kidney donor was inspired by 3 people including Scott but would've donated with or without Scott's inspiration in particular, then Kyle doesn't count. If we guess a 50% chance without Scott, then Kyle counts as 0.5 inspired donors.

2. Divvy the credit. In this case if Kyle was equally inspired by 3 people including Scott then Kyle counts as 0.33 inspired donors.

Any suggestions for which is better? Let's err towards what's easiest to find out, not just what version we'd ideally want.

@dreev Well if I were restarting this market from scratch, I'd just count the number of people who cite Scott at all, rather than trying to divvy up credit or compute probabilities. But I'm not sure you can do that here based on the existing criteria and FAQ. The easiest way that would still roughly capture what you're looking for might be "last straw" accounting - ask people who the most recent inspiration was, and count as 1 for Scott and 0 otherwise.

I predict that getting the data will be difficult enough that this poll will be meaningless. How are you going to collect it? Comments on that post?

Affirmative. I may do additional work to estimate it.

@dreev That's going to seriously underestimate it.

I don't think I can bet until the counting mechanism is settled, so I can discount properly.

@Calion Ideas solicited! Just asking Scott is one idea.

@dreev That's certainly the best idea I can think of. If he agrees to tell you, that’s at least some kind of metric.

Would I necessarily tell Scott? I don’t know him and have never commented on his blog.

@akshitapurna Super fair. Maybe Scott will end up with a sense of this. Like if he learns of a case like that via some coincidence then he can infer that there are other such cases. I'm open to interpreting this either as "confirmed cases" or "our/Scott's best estimate of total cases".