skat20phys

This has really hit home for me. I'm pretty sick with a 102 fever, cough, and aches. My guess for various reasons is that it's influenza A, but there are reasons to think it's not crazy to think it's COVID19.

The issue is that there's this kind of positive feedback loop about getting tested. If you have symptoms consistent with COVID19, you're told it's probably the flu and no need to go in and get tested unless you're high-risk. People always say "have there been identified cases of COVID19 near you?" The answer is basically "not that I know of," but if everyone is staying home and not getting tested so as to not panic and overburden the system, you don't know. As a result, it will look like nothing's there until suddenly there's a de novo case that can't be traced to Asia, Europe, or anywhere else that's had large numbers of cases. Then it's too late and is everywhere.

I understand the base rates, and that I probably don't have COVID19, but I don't really have faith in assessments of where things are at if people are rarely getting tested anyway.

Negative probabilities interestingly are showing up in various other realms. There seems to be converging interest in the topic from a number of areas.

For example, in relating Bayesian inference to algorithmic complexity-based inference: https://arxiv.org/abs/1401.7116

I've also read some interpretations of negative probabilities in terms of erroneous values. For example, if you're sampling observations, and a machine error causes an anomalous value to appear in the data. This I don't know I completely intuit but there are interpretations of negative probabilities outside of QM.

My sense is that they will eventually be accepted akin to imaginary numbers or something but that's just a hunch and I could be wrong.

That's a good point regarding MAP estimates versus, e.g., EAP estimates, although it does lead to questions about whether one or the other is preferable, and I think good arguments can be made either way.

I haven't read the linked paper yet, but the blog post points a little to what's on my mind.

To borrow a bit from a different paper and anonymous reviewer on one of my papers, inference serves different aims or philosophies. Sometimes it serves more of an estimation function, to increase information about some quantity, or to improve the estimate of that quantity. But sometimes it serves an evaluative, competitive function, in the Popperian sense of affording risky tests of one or more theories or models.

In this latter Popperian aim of inference, priors are to be minimized, which is in many ways the opposite scenario that is assumed with standard subjective Bayesian methods. And even with the former "estimation" inferential aims, there may be situations where you truly have no information or don't feel comfortable assuming it.

What's nice about Bayesian statistics is it still provides a framework for this scenario, in the form of reference priors, in that if nothing else your design and model supporting the parameter(s) to be inferred about implies some kind of assumptions about what you're making inferences about. That in turn can be transformed into a "least informative" prior. So it allows an objective Bayesian framework.

However, in that framework, in many cases you're still often left with uniform priors, which then reduce to frequentist statistics. And in a broader sense, frequentist methods are even further removed from making assumptions in that they completely eliminate the prior from inferential consideration.

There's a tension then, in that in small samples your priors will bias your estimates. If you use least informative priors, you're often doing something akin to frequentist methods anyway. And in large samples the likelihood dominates the posterior so it matters still less.

From a certain perspective, ultimately with Bayesian methods you're making a bet that your priors are accurate enough that the increased bias in estimates will be small enough to be offset by decreased variance due to use of a prior. It's a gamble though, the risks of which will probably vary depending on the costs and benefits of different types of error.

It's nice to see a paper trying to be honest about the problems with Bayesian inference, as it's a bit overhyped at the moment imho.

I'm amazed at smartphones and videochatting to be honest, but at some level it's something that seems like a natural evolution of what was there before.

For example, in a lot of ways we live in a sci-fi future, if the number of classic films featuring videochats as a sign of the future is any indication. On the other hand, those films did basically get the idea right, that there would be some screen with some little speaker and microphone that you'd talk to someone through.

If you go back a bit further though, like to the 1910s, there wasn't any idea of that at all. It was off the collective radar completely.

So in some sense, we are living in some continuation of the early 1970s, in the sense it was part of a future we could accurately envision. But we're not living in a continuation of the same era as pre "golden quarter" in that we aren't really entirely part of the future they imagined (I think 1945 isn't quite right, I'd push it back to pre-WWI).

At least that's one argument. I wish we could go back and time and interview a bunch of people who lived like 1900-1960+ about this issue, and compare it to what people who were born in, say, 1950, might say about it now.

FWIW, my sense is that people in the mid-twentieth century underestimated change in communication technology and overestimated change in transportation tech.

My reaction to this is kind of similar to yours, and sort of in-between a lot of others'. A lot of posts here seem to be nay-saying the piece, but I'm not really sure that's right or wrong.

The problem as I see it is it's not really clear how progress should be defined to address the sort of questions being asked in the article. Maybe someone has convincingly, and the article doesn't convey this, but without a clearer definition things seem to be a non-starter.

I have some intuition that the question of the piece is not really nonsense, that there was something about the interwar and postwar period that was different. A lot of advances since then have been powerful incremental improvements on those postwar innovations, but incremental nonetheless. The one exception I personally maybe see is networked communications, which have really revolutionized a lot and are still disrupting things. But outside of that my sense is that life (in the US) hasn't changed in fundamental ways since, say, 1975. Things are really different in a lot of ways, but the basics are the same. Conversely, my sense is things are really different compared to 1915.

On the other hand, I'm not sure any of my subjective senses of things are really accurate. I wasn't alive in 1915. So without quantifying anything convincingly this is all some armchair discussion.

I do think these kinds of questions are important, and I suspect there's some way of getting at this, maybe with very high-level economic or public health data (I've read that the biggest increases in life expectancy in the last 200 years or so, for example, have not actually come from any medical procedure or tech advances, but rather public health advances). But I agree that the way we define things is critical, and it would be interesting to address the question of the article definitively positively or negatively.

The issue is that psychosis/schizophrenia isn't like testing for a bacterium or looking at an x-ray. It's really a label for a set of presenting behavioral patterns, and is heterogeneous (I don't mean this critically, just the way it is).

So let's say someone is blind, and they come in. They will almost certainly be more likely to receive attention than someone who is not. But how their presenting disorganized thoughts, etc. are described is likely to be different given their history of blindness, especially if they had a lifetime history of associated cognitive deficits or issues.

It's also the case that overlapping presence of two pathologies is not necessarily same as them disjointly. So blindness etiological factors + psychosis etiological factors may not equal schizophrenia with blindness, but rather a more severe cognitive and/or physical disorder that receives an entirely different diagnosis. This latter scenario isn't necessarily a measurement issue, but it could be construed that way.

This is a good point but similar kinds of phenomena could lead to something more benign but equally problematic.

For example, let's say someone inherits (genetically or environmentally) etiologic factors for psychosis and blindness. It's possible that whatever these factors are, they are severe enough to have widespread enough effects that the person no longer receives a psychosis diagnosis, but instead some other diagnostic label that's more comprehensive in nature.

Schizophrenia is really just a label for a semi-heterogeneous set of pathologies that might be labeled something else. I'm not saying that these problems don't exist, just that how they are perceived and described might vary a bit from scenario to scenario (this is one of the main impetuses for DSM-III and later actually). So someone with one pathology might receive a diagnosis of schizophrenia, someone else, bipolar disorder, and yet someone else developmental disorder NEC/NOS.

It's entirely possible that if there is a negative correlation, it's because one reflects some preventative factors for the other, or something like that, but it's also possible that whatever causes the conjoint presence of the etiologies is catastrophic, leading to death, like you suggest, or the need for some entirely different label.

I use kubuntu as my preferred system and love it.

I will say that in my experience initial releases are often kinda glitchy or something, and that it can take awhile for brand new hardware etc to be supported well. But it's usually solved by just waiting a bit for the second version.

Classic flamewar statement here, but I've had fewer headaches overall with kubuntu than gnome flavors of Ubuntu (which Ive had to use for work). Deb+kde is a great combination. Maybe there's a better way to get that but I've always gone back to kubuntu when I've tried something else.

Psychology is no more predicated on mind-brain duality than computer science is predicated on hardware-algorithm duality. It's a level of analysis issue. There's plenty of psychology close to the neuron, and there's plenty of psychology where invoking neural substrates is unnecessary or even impossible.

I think the tricky part is that at some level you want to be comparing counterfactuals. That is, accident rates of Teslas on autopilot with a driver of Tesla-driver abilities, in road conditions where the accidents occur, and so forth.

It kinda seems self evident that a car that drives you into a wall randomly is less safe than one that doesn't.

I grant that Teslas might be safer than eg a drunk driver, and so we might be better off replacing all cars with Teslas in some sense, but we'd also be better off if we replaced drunk drivers with sober ones. But would safe, competent drivers be safer, and would that be ethical? At that point are you penalizing safe competent drivers?

Drunk drivers in Teslas are actually interesting for me to think about, because I suspect they'd inappropriately disengage autopilot at nontrivial rates. I'm not sure what that says but it seems significant to me in thinking about issues. To me it maybe suggests autopilot should be used as a feature of last resort, like "turn this on if you're unable to drive safely and comply with driving laws." But then shouldn't you just not be behind the wheel, and find someone who can?

This "driver aid" model itself is starting to sound like a problem to me. You either have safe, autonomous driving or you don't.

A model where a driver is assumed to disengage attention, etc but then be expected to rengage in a fraction of a second to respond to an anomalous event is fundamentally at its core flawed I think. It's like asking a human to drive and not drive at the same time. Most driving laws assume a driver should be alert and at the wheel; this is what...? Assuming you're not alert and at the wheel?

As you're pointing out, this leads to a convenient out legally for the manufacturer, who can just say "you weren't using it correctly."

I fail to see the point of autopilot at all if you're supposed to be able to correct it at any instant in real-world driving conditions.

I knew there were things like what I was mentioning, but couldn't remember the names of them. Thanks.

I don't think any of these biases are necessarily consciously enacted, but I think they exist in some of the ways you mention. There's a sort of echo chamber effect or positive feedback loop with citations.

Somewhere I remember reading a bibliometric analysis of citation patterns in the nutritional sciences regarding the effects of salt. There were two huge clusters of papers, one basically "salt is basically fine" and the other is "salt should basically be avoided". The papers in a cluster cited each other a lot, and not so much papers in the other clusters.

I agree that quality reviews become more important over time, but there's the issue of "according to who?" I suppose this becomes an expert judgment call and is the nature of these things, as it always has been, but I feel like as things become more parochial and balkanized the meaning of a "good review" changes somewhat, or becomes harder to agree on.

I guess as I'm thinking about it and reading through the comments, I'm maybe ok with the reviews being available, although I still believe anonymity is important as an option (although I'm not sure true anonymity can exist with publicly available text, so I go back and forth about that).

I'm not convinced review quality will improve with completely open reviews, because there's too many opportunities for retribution. Sure reviews that kill papers through a thousand tiny irrelevant cuts would probably go to the wayside more often, but my guess so to would very trenchant, highly critical reviews that make important but controversial points.

I'm actually very opposed to visible branding on a lot of things, especially clothing. At first I felt like I was being a little obsessive-compulsive but then eventually realized it's an ethical issue for me. Every time someone puts on a garment with a logo, they're being used to serve the interests of the corporation and not their own interests in a tiny way. The fact that this seems so natural says a lot about the state of our society in this regard.

As for your argument, I think it's reasonable but I would turn it on its head: to me every bit of money that's going into visible branding in some way is a signal that the company is putting effort into advertising itself on the outside of the clothing rather than improving quality. I can think of a couple of companies I buy from whose quality has declined in the last couple of decades overall in certain regards, and it's been directly associated with an increase in visible branding on their goods. Basically they started cashing in on their reputation, focusing on their brand identity rather than the quality of their items. Judging from comments in various places I'm not alone in the sense their quality has declined.

My impression is actually that it is not difficult to find minimally branded high-quality goods in many areas. In fact, the highest quality goods in a some areas are those with minimal or no branding.

I admit there are also many areas, like athletic wear, where this isn't usually the case. On the other hand, I've often noticed that if you actually compare some types of very high end activewear to less expensive variants, the difference is often just the logos. You're in effect paying more to have the logos off rather than less.

I personally feel that companies should be shamed out of including visible logos on their clothing.

Maybe we're talking about different things though. I do think having brand identifiers of some sort somewhere is important, as it increases accountability. And some things that are likely to be shuffled away, like laundry detergent, I don't really care about. But things that are likely to be out and about? Especially on you as a person? Brand visibility shouldn't be a factor imho.

So, I've edited a journal, been on journal editorial boards, and reviewed a lot. I'm skeptical that more transparency in peer review will make a difference at all. In fact, some of the proposed solutions might hurt a bit. In the very least, I think there's a tidal wave of change in publishing that's making traditional academic peer review moot.

The linked question is interesting for me to think about given one of my relatively recent experiences (this is all in the area of statistics, so kind of directly relevant). I was asked to review an article, and as a counterpoint to one of my concerns, the author cited an in-press paper in a fairly well-respected journal. So I go to look at it, and it makes little sense to me, in that it contradicts a bunch of other things that are known. I look at it closer, and it turns out there's a subtle but important notational error carried through much of the proofs that basically invalidates the whole paper.

So I contact the editor of that journal to feel out the response to writing a commentary about the issue, with a fairly detailed explanation of the flaw in the proofs. Instead of being receptive or at least neutral, the editor throws up all sorts of obstacles — not exactly threats, but strong discouragement in the form of a long list of criteria that had to be met, several of which were completely unnecessary. My colleagues (who are also editors of other journals) got even more upset than me, believing that the editor was trying to bury the error and so forth. One even threatened to expose the exchange on twitter or something.

The truth is, I don't know that I cared that much about this particular topic to really put the effort into writing a commentary, fighting with the editor to publish it, and skewering the author's ego in the process. My friends and I discussed just putting the commentary on an online archive, but it wasn't clear anyone would make the connection with the paper. Also, for unrelated reasons, I shortly afterward wrote a different paper that was more comprehensive in scope that sort of superceded that flawed proof anyway (that is, if someone read this paper of mine, the results of the first erroneous paper would probably seen as as irrelevant).

In this case, the flawed proof/paper was peer reviewed. Making the reviews transparent wouldn't have mattered because in the end the paper was published. Maybe one of the reviewers raised the issues but it was published anyway, so published reviews would tip a reader off? But at that point where are we? If I had done something (and maybe I still will?), I would have just published it in a public academic archive anyway. What, then, is the point of peer reviewed journals? Are we better off just posting papers publicly, and publicly commenting on them? Is stripping anonymity from reviewers a good or bad thing? Won't that discourage rigorous review, for fear of repercussions against reviewers? Is review really all that rigorous anyway?

My personal impression is that the volume of academic publishing has increased so much that it's impossible for readers to really keep up, and making it more difficult for scientific consensus to form completely. Publicly available papers in archives is a natural extension of this. What this means is that readers increasingly pick and choose which literature they read and cite, which truth they want to reinforce, and what truth they want to suppress. When you open up peer review to be public, those reviews become just another part of that literature. The peer reviews become blog and twitter posts, which is absolutely fine, but then a reader just selectively picks and chooses which what reviews and blog posts they cite, and so forth and so on.

For the record, I'm very much for open publishing, and open discussion of literature. I just think that academics hasn't wrestled with the implications of that, in terms of what it will look like (e.g., amplifying fads, decreased signal to noise ratio, increased feedback loops), and whether it's worthwhile to vigorously maintain anonymous peer review to have that as another form of literature evaluation. There's already a lot of public discussion of papers, and this will only increase regardless of what happens to peer review. Maybe the issue is who does the anonymous review? Maybe just opening up papers to anonymous commentary is the right way to go?

My experience with gel ink pens is that they're incredibly smooth to write with but that you go through refills a lot more often than with ballpoint or rollerballs.

I've settled on a Retro 51 Tornado. Nice price when I've bought them and they take a lot of different refills.

Your intuition is right but it's complicated.

This paper gives a discussion of different biases:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4504518/

There's a standard paper on this topic the authors I forget atm but all estimates will be biased. The best estimates are sort of unintuitive and account for estimated time-to-death and the time since diagnosis.

What's really amazing to me is the rendering quality, if that's the right word for it, the resolution. This seems different to me than the "structural realism" in the sense of how plausible the face is in it being representative. Not sure if there are terms for this but it's amazing to me how realistic things like skin texture are independent of "higher level" features.

For me, this whole thing goes in the category of "what the @#$ were they thinking?"

I'm not sure if I should interpret it as a isolated case of misjudgment, evidence of poor organizational features, overinterpreting the significance of this by outsiders (the Iowa caucuses are notoriously fuzzy, which is kinda the point of them, so maybe the party saw this as an appropriate test case?), technological naivete, or what.

Every time I read about this I'm amazed it isn't getting more attention in the wider press.