Danish math major
Oskar Mathiasen
Karma: 117
I think “book of X” can be usefully “translated” as beliefs about X.
The book of truth is not truth, just like the book of night is not night.I think “book of names” can be read as human categoristion of animals (giving them name). Although other readings do seem plausible.
You might be interested in John Harsanyi on the topic.
He argues that the conclusion achieved in the original position is (average) utilitarianism.I agree that behind the veil one shouldn’t know the time (and thus can’t care differently about current vs future humans). This actually causes further problems for Rawls conception when you project back in time, what if the worst life that will ever be lived has already been lived? Then the maximin principle gives no guidance at all, and in positions of uncertainty it recommends putting all effort in preventing a new minimum from being set.
The concept of Kolmogorov Sufficient Statistic might be the missing piece. (cf Elements of information theory section 14.12)
We want the shortest program that describes a sequence of bits. A particularly interpretable type of such programs is “the sequence is in the set X generated by program p, and among those it is the n’th element”
Example “the sequence is in the set of sequences of length 1000 with 104 ones, generated by (insert program here), of which it is the n~10^144′th element”.We therefore define f(String, n) to be the size of the smallest set containing String which is generated by a program of length n. (Or alternatively where a program of length n can test for membership of the set)
If you plot the logarithm of f(String,n) you will often see bands where the line has slope −1, corresponding to using the extra bit to hardcode one more bit of the index. In this case the longer programs aren’t describing any more structure than the program where the slope started being −1. We call such a program a Kolmogorov minimal statistic.
The relevance is that for a biased coin with each flip independent the Kolmogorov minimal statistic is the bias. And it is often more natural to think about the Kolmogorov minimal statistics.
Then you violate the accurate beliefs condition. (If the world is infact a random mixture in proportion which their beliefs track correctly, then fdt will do better when averaging over the mixture)
I don’t think the quoted problem has that structure.
And suppose that the existence of S tends to cause both (i) one-boxing tendencies and (ii) whether there’s money in the opaque box or not when decision-makers face Newcomb problems.
But now suppose that the pathway by which S causes there to be money in the opaque box or not is that another agent looks at S
So S causes one boxing tendencies, and the person putting money in the box looks only at S.
So it seems to be changing the problem to say that the predictor observes your brain/your decision procedure. When all they observe is S which, while causing “one boxing tendencies”, is not causally downstream of your decision theory.
Further if S where downstream of your decision procedure, then fdt one boxes whether or not the path from the decision procedure to the contents of the boxes routes through an agent. Undermining the criticism that fst has implausible discontinuities.
Cant you make the same argument you make in Schwarz procreation by using Parfits hitchhiker after you have reached the city? In which case i think its better to use that example, as it avoids the Heighns criticism.
In the case of implausible discontinuities i agree with Heighn that there is no subjunctive dependence.
Here is a quick diagram of the causation in the thought experiment as i understand it.
We have an outcome which is completely determined by your decision to one box/two box and the predictor decision of whether to but money in the one box.
The Predictor decides based on the presence of a lesion (or some other physical fact)
Your decision how many boxes to take is determined by your decision theory.
And your decision theory is partly determined by the Lesion and partly by other stuff.
Now (my understanding of) the claim is that there is no downstream path from your decision theory to the predictor. This means that applying the do operator on the decision theory node doesn’t change the distribution of the choices of the predictor.
Denmark culled all mink due to worries about a covid strain in mink. It has only recently (January 1 2023) become legal to farm mink in Denmark again.
logical inductors are actually defined by the logical induction criterion. The market bit is there to prove that it is possible to fulfill the criterion.
There is also the somewhat boring answer that probability can refer to anything which obeys the axioms of probability.
Note that coop is a consumer cooperative not an employee cooperative.
https://en.wikipedia.org/wiki/Consumers%27_co-operative
New report from Denmark called “Focusrapport about Covid-19 related hospitalizations during the Covid-19 pandemic”
https://www.ssi.dk/-/media/cdn/files/fokusrapport-om-covid-19-relaterede-hospitalsindlggelser-under-sars-cov-2-epidemien_06012022_1.pdf?la=daIt is sadly in danish, so i will give a translation of the main results section and some of the graphs.
Summary of main results:
Theme 1:
* The older a patient is, the greater the likelihood that he or she will have a covid-19- related hospitalization of 12 hours or more.
* The proportion of short hospital stays of less than 12 hours has been fairly stable in each age group in 2021 with a few fluctuations.
* The median duration of long hospital stays (≥12 hours) has decreased from 5.5 days in March 2020, to 4.4 days in February 2021 and 4.0 days in October 2021.
* (this one is added by me) The average duration of (long?) hospitalizations has decreased from 9.2 days in March 2020, to 7.8 days in February 2021 and 7.2 days in October 2021.Theme 2:
* Among covid-19-related admissions in the period 1 June 2020 − 18 December 2021, 82% were registered with a covid-19 diagnosis, 3% with a respiratory diagnosis or an observable covid-19 diagnosis and 15% with another diagnosis. In the month of December, December 1, 2021 to December 18, 2021, they were corresponding shares resp. 73%, 4% and 23%.
* For all age groups ≥40 years, at least 80% of the admissions were registered with a covid-19 diagnosis. For younger adults and children, the proportion was lower.
* For vaccinated, 75% of admissions were registered with a covid-19 diagnosis, while the proportion among the unvaccinated was 82% in 2021. The proportion of patients registered with a diagnosis incompatible with Covid among vaccinated and unvaccinated were respectively. 21% and 15%.
percent of covid hospitalizations which where longer then 12 hours (in red) vs shorter than 12 hours (in blue) by age group over time.
number of hospitalizations that are covid (top), airways or observation (middle), and other (bottom)
the above categories as a proportion of covid positive hospitalizations over time.And the above categories as percentage by age group (over june-december 2021)
By age and vaccination status (vaccinated is to the left) (there are no vaccinated at ages below 9 in the period)
A few thoughts:
It seems weird that the median time of a long stay is going down, but the percentage of short stays is stable
Updated numbers from today at: https://files.ssi.dk/covid19/omikron/statusrapport/rapport-omikronvarianten-10122021-ek56
Now with English translations.
Only significant change is that hospitalizations are up to 1.4% (18 cases).
There should be daily updates found her https://www.ssi.dk/aktuelt/nyheder/2021
click the newest one and click “læs rapporten her” (read the report here). Which takes you to a page where you can download the rapport for that day
Repost from wordpress blog
status rapport from Denmark
Key numbers: they give numbers of cases by day, and also give cases of omicron as a percentage of other cases.
Of 785 cases in Danish citizens, 76.31% of omicron cases where in double vaxed, 7.13% in triple vaxed, compared to 73.69% double (probably also including triple) vaxed for covid in general. 14.14% unvaxed for omicron 22.93% for general (over the last 7 days)
Rate of hospitalization is 1.15% for omicron (9 cases), and 1.85 in general.
Everything is probably confounded by age and region. (omicron is less prevalent in children and over 65)
sources: https://experience.arcgis.com/experience/aa41b29149f24e20a4007a0c4e13db1d/page/page_5/ https://files.ssi.dk/covid19/omikron/statusrapport/rapport-omikronvarianten-09122021-ke43
Todays cumulative omicron cases is 398
Repost from my wordpress comments:
Danish seroprevalance (from https://www.ssi.dk/aktuelt/nyheder/2021/markant-stigning-i-den-fjerde-nationale-praevalensundersoegelse) seems to have been about 50% above commulative cases (from https://www.worldometers.info/coronavirus/country/denmark/) by may 2020.
Commulative omicron cases in Denmark per SSI https://www.ssi.dk/aktuelt/nyheder/2021
dec 3: 18 omicron cases
dec 5: 183 cases
dec 6: 261 cases
Oddly this looks linear (80 cases per day), but that is almost certainly random.
The fact that the 2 numbers are equal is not always true, it is randomly true on this day.
Yes.
I agree that the original post keeps going after removing differences in values because they don’t remove differences in marginal value, which is what matters.
I am providing an example where properly removing the differences in marginal value results in no trade.
You are using a nonstandard definition of goods. Would you equally object to a market with only blueberries, apples and bananas on the basis that there is only one good available (fruits)?
The example world can be modified easily to use any utility function of the form a·red points + b·yellow points + c·blue points.
Yes.
The comment was meant as a proof by example that you can have no trade in a world with comparative advantages, if everyone has the same marginal value of all products the result is no trade.
Diminishing marginal returns are indeed enough to make marginal values different between people.
People could trade making each others numbers bigger, it’s just that it will never be beneficial for both.
Letting people increase others numbers by decreasing their own number doesn’t change the results
The assumptions made here are not time reversible as the macrostate at time t+1 being deterministic given the macrostate at time t, does not imply that the macrostate at time t is deterministic given the macrostate at time t+1.
So in this article the direction of time is given through the asymmetry of the evolution of macrostates.