Preston McAfee @mcafee@qoto.org

@bricegreen@bayes.club
Thanks for the kudos! Here is a copy that doesn't require a subscription:
https://vita.mc4f.ee/PDF/VoyageofColumbus.pdf

@ct_bergstrom@fediscience.org
I had blocked content marked sensitive and apparently Snowy Plovers are sensitive. Sorry about that.

@ct_bergstrom
Not sure why, but your photos are invisible for me.

@r000t @QOTO @Gargron @arteteco @Sphinx @khird @freemo

There are use-cases where the inverse logic is appealing, e.g. wanting to participate but not show posts to an abusive ex. What seems to be the natural compromise is (1) Alice blocking Bob prevents Bob from sending messages or replies to Alice, and (2) if Alice is private (only approved logged-in users can see her posts), Bob is blocked from seeing her content. GNU rooot makes a good point that if the content is public, there is no point in blocking any logged in user from seeing it. Note that (2) doesn't require any additional action because (1) prevents Alice from even seeing Bob's request to see Alice's content.

There are important use cases for private groups beyond the abusive ex. In my area (economics), public discussion is immediately attacked by trolls and poorly educated partisans. Having a private, restricted conversation is often necessary for having a good conversation.

And perhaps needless to say, it should be possible for a Mastodon instance to prevent blocking mods. What is beautiful about Mastodon is that if I don't like an instance's policies, I can move to another instance or start my own. This structure allows absolute free speech while allowing individuals to avoid speech they want to avoid through instance policies. Blocking moderators prevents enforcement of instance policies, so undermines the value of Mastodon.

@madhu_shrieks@sciences.social
First, kudos to the author for an engaging presentation. Second, there are several elements that appear misleading.

Caveat: I don't have access to JStor and can't seem to find the original paper on the Am Scientist website.

In the two person interaction, I understand the wealth dynamics to work like this. Each person wagers a fraction f of their wealth w1, w2 and the actual wager is f*min{w1,w2}. WLOG we can set w1+w2=1, so person 1's wealth follows the process:

w1=w1+p*f*min{w1,1-w1}

where p takes on the values -1 and 1 with equal probability. The right hand side has a zero expected value so 1's expected wealth does not change over time. So the statement that "the rich wind up with all the wealth" in this game is inaccurate. What does happen is that *someone* winds up with almost the wealth with high probability; the probabilities are determined by the initial wealth ratio w1/(w1+w2) because we know expected wealth is constant over time.

Here I am commenting on the statistical process; as a model of economic activity, what it shows is that even gambling with a zero expected loss is a loser for a risk averse person, as should be obvious. A fair bet still represents a garbling (in the Blackwell sense) of wealth and hence reduces expected utility for concave utility functions.

This is why there is a risk premium: risk averse people should only gamble when there is a positive expected return.

@niallfarrell
You have not given the correct interpretation. Gift-giving is a money pump. The giver obtained *at least* the purchase price in value, while the recipient obtained 2/3rds of the purchase price, producing 1 2/3rds in value. That is a pretty good social return!

@mempko

Well, not the way economists use the term efficiency, but there are multiple ways one might use the term efficiency and economists don't own it.

We also apparently use the term fragile differently; I use it to mean "likely to break," so that planning for most outcomes (optimizing for probable ranges) reduces fragility. Making supply chains very long made them fragile, because dependencies were hidden. This is how we came to have a yeast shortage -- we had a shortage of packaging. Many of the shortages were of the "for the want of a nail, the kingdom was lost" sort. These sorts of fragility are readily planned for and inexpensively thwarted when interest rates are low.

I think the challenges in prediction -- which are as you suggest probably growing -- is a red herring on the efficiency of resilience. Resilience means engineering for eventualities, not over-engineering for eventualities. Hotels face random demand; appropriately sized they handle more than the average demand but less than the maximum demand. That is resilient. Investing in good forecasting aids resilience.

There is nice work by Miles Kimball

https://www.jstor.org/stable/2938334

on when the response to increased uncertainty is to invest more or less in resilience.

I encourage you to mull on the extra water in my hikes -- I cast this as a known risk to make it simple, but all risks look like this: sometimes water will be more valuable than others and I have to make preparations in advance of the realization of uncertainty. Extra spending in this regard, like me carrying more water than I typically need, is exactly what insurance looks like.

BTW, markets also usually help with increased forecast uncertainty, mainly because the person with better predictions can make a lot of money and their trades spread that information. I am not claiming that market forces incent efficient investment in prediction, however.

@mempko

To bring more than I will *ever* need is not efficient, yes, nor is it insurance; efficient insurance is generally between the maximum need and the minimum need. But that is precisely what builds resilience: preparation for eventualities. And that was my point: resilience is efficient and is indeed a property of competitive markets. Now I am not saying our actual markets produced resilience, for mostly they did not, but the cause was not market forces but something else, e.g. short-run performance focus or a failure to calculate the probabilities.