Amusingly, 15 min ago, the animation did not work on my MacOS Safari (Sequoia), but it was visible on Chrome. Now (1600 UTC-4), it is animated on Safari.
Apple Keychain has a number of old bugs that have caused me to have to resort to this strategy several times. The most common problem is having a secure note that you can open, but then immediately disappears (closes). Copying over an older keychain database can sometimes solve the problem.
>>> If I buy a can of soup and find glass in it, I have a valid claim against the manufacturer. It's a matter of holding someone accountable for fraud or negligence, not a matter of regulation. The proper route is a court, not a bureaucratic agency that preemptively dictates production methods on the assumption that every manufacturer is a potential prisoner.
This is a common conservative trope. We don't need regulation because customers can always sue. (Famous interview with Milton Friedman.) Good luck finding a lawyer who will sue because of some glass in your soup can, or, for more serious cases, who can out last (or match the spending of) a billion dollar corporation. Yes, sometimes the underdog wins. Rich people can sue, and may not need the governments regulatory help. For most people, there is absolutely no recourse, particular for technically complex things, like prescription drugs.
The idea that the legal system can consistently make better informed technical decisions than government scientists is not well supported by the evidence.
It is useful to distinguish between "effective" scientific fraud, where some set of fraudulent papers are published that drive a discipline in an unproductive direction, and "administrative" scientific fraud, where individuals use pseudo-scientific measures (H-index, rankings, etc) to make allocation decisions (grants, tenure, etc). This article suggests that administrative scientific fraud has become more accessible, but it is very unclear whether this is having a major impact on science as it is practiced.
Non-scientists often seem to think that if a paper is published, it is likely to be true. Most practicing scientists are much more skeptical. When I read a that paper sounds interesting in a high impact journal, I am constantly trying to figure out whether I should believe it. If it goes against a vast amount of science (e.g. bacteria that use arsenic rather than phosphorus in their DNA), I don't believe it (and can think of lots of ways to show that it is wrong). In lower impact journals, papers make claims that are not very surprising, so if they are fraudulent in some way, I don't care.
Science has to be reproducible, but more importantly, it must be possible to build on a set of results to extend them. Some results are hard to reproduce because the methods are technically challenging. But if results cannot be extended, they have little effect. Science really is self-correcting, and correction happens faster for results that matter. Not all fraud has the same impact. Most fraud is unfortunate, and should be reduced, but has a short lived impact.
The distinction between effective and administrative fraud is useful and I think underappreciated. A lot of the conversation in these threads conflates the two, which makes it hard to reason about what actually needs fixing.
I want to push back a little on "science is self-correcting" though. It's true in the limit, but correction has a latency, and that latency has real costs. In fields like nutrition, psychology, or pharmacology, a fraudulent or deeply flawed result can shape clinical guidelines, public policy, and drug development pipelines for a decade or more before the correction lands. The people harmed during that window don't get made whole by the eventual retraction.
The comparison I keep coming back to is fault tolerance in distributed systems. You can build a system that's "eventually consistent" and still have it be practically broken if convergence takes too long or if bad state propagates faster than corrections do. The fraud networks described in TFA are basically an adversarial workload against a system (peer review) that was designed for a much lower rate of bad input. Saying the system self-corrects is accurate, but it's not the same as saying the system is healthy or that the current correction rate is adequate.
I think the practical question isn't whether science corrects itself in theory but whether the feedback loops are fast enough relative to the rate of fraud production, and right now the answer seems pretty clearly no.
Re self-correcting science. In the area I am most familiar with (basic life sciences), correction happens pretty quickly. But I don’t worry about public policy much.
But I’m comfortable arguing that where science intersects with policy, fraud plays a very minor role. I suspect that most policy “mistakes” (policies that were adopted and then reversed) are more about the need for a policy in the absence of data (covid and masks), or subtle tradeoffs (covid and masks), or a policy choice that seems slightly better than an alternative (mammography) but also has poorly understood harms. Policy involves politics, and science unfortunately plays less of a role than one might like (and fraudulent science an even smaller role). This is not my field, but I cannot think of policies that were reversed because of discoveries of fraud (perhaps thalidomide and other drug approvals).
It is perhaps worth noting that the 25,000 bit flips/out of 470,000 crashes (in a week) are probably not coming from all Firefox users. It would be useful to know how many of those crashes (and bit flips) are happening on the same machine. And whether the crashes/bit flips continue on the same machine continue from week to week.
I can certainly imagine that a very small fraction of Firefox users are generating these results, so that bit flips are not a problem generally.
Nice display, but it starts off with misleading measurements of DNA. The spacing between DNA base pairs is 0.34 nm, so the 10 base pairs pictured are in fact 3.4 nm. But the DNA in a single human cell is about 2 meters, and chromosome lengths vary from 2 to 10 cm. I am skeptical of the hemoglobin vs ribosome sizes as well; hemoglobin has a molecular weight of about 60,000, while ribosomes weigh more than 5 million.
Before Postscript, tektronix 4010 was the language of graphics, at least for biologists drawing phylogenetic trees or reassociation curves. The phylip phylogenetics package, introduced around 1980, still has the option to generate trees in tek4010 format.
I agree with this, but given how much of the value of EVs is tied to the accessibility of a charger network, it seems like this really needs to be reported on the title somehow.
Even if Tesla is the only one doing this right now, I'm sure it'll be a thing in the future with other manufacturers and a proliferation of 3rd party repairs.
Tesla controls the supercharger network, vehicle registry and vehicle software, and nowhere in the process of acquiring the vehicle did the customer get notice that the car was banned from the network. Tesla has some culpability here since the title was clean.
People still think they own cars, and that they should be allowed to repair them without the blessing of the manufacturer. They don't expect to be banned from using their car because someone decided that using the DMCA to pervert the concept of ownership was a good thing.
No one is banning them from using their care. Just from plugging their car into a device that has enough power to kill anyone who happens to use that care because of shoddy repair work.
But the state confirmed the vehicle never had a salvaged title, so, what was the scam?
I wasn't even aware that it was possible for a car to be banned from the supercharger network. Sure, it makes sense in hindsight, but I wouldn't necessarily expect a used car dealer to know anything about this either.
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