The details of how this is done seems to matter quite a bit, and if I'm reading this[0] right, if the officers have the discretion about when to turn them on or off use of force might be higher compared to no body cams.
One thing I haven't seen in the discussion is the effect of the tax on the distribution of outcomes.
I'm not sure what the latest numbers are, but if 90% of startups are near 0 return for founders, and 1% are the home run swings which made it worth starting the company to begin with - then when do proposals affect the expected value for starting a company. This notebook doesn't show anything other than 'if you were going to make a bunch, you'll still have more than zero' which isn't useful.
Startups are in the land of "fat tails" - so talking about a policy saying it's fine for for most people since the people at the extreme in the fat tail are doing fine seems to be thinking under-critically.
If I can continue your analogy (though I admit it's a little confusing) - if a gang member is caught breaking the law and we have another law preventing prosecution, let's fix that bug.
Structural issues which create gangs need to be addressed, and it's true that convicting the gang members might detract from the need for those structural reform, but enforcing laws is still a part of the incentive system we have to encourage people to not break the law.
We should fix structural issues, but that doesn't mean we need to leave clear bugs in tact to increase pressure on fixing those issues.
When you say 'as long as the end user is not financially benefitting' - is the end user the lab conducting the test?
You said in an earlier comment that the reimbursement for testing is too low to justify buying expensive equipment. You are also proposing to charge half the reimbursed rate for it to run on someone else's equipment.
Are the current equipment owners expected to donate this crucial equipment, because if they are the bottleneck, shouldn't they be the ones compensated to encourage more equipment to be made available?
The innovation is personalized hydrogels built to avoid rejection, not the induced pluripotent stem cells which were re-differentiated into things. The key was the structural materials which hold those cells.
Did you have (even a vague) source for this - I'm willing to search for it given even a vague gesture? I think this indeed sounds like it could be strong evidence, so I'd love to see it. Indeed, I would also think that a high skill population living mixed with a low skill population would have a higher birth rate than a high skill population NOT near a low skill population.
Yours is not a unique sentiment, but I find it so disheartening. Vague laws enforced selectively are bad for the rule of law. Is the schadenfreude from sticking it to whatever American company is selected worth that?
This sounded interesting, do you have a link to this study? I was going to try to do this analysis for where I live, and after looking up median income for the area, I realized I wasn't sure what you meant by 'down payment and interest consume 100% of income.' Did you mean a 20% downpayment and interest on a loan would consume one year's worth of income... because that actually seems pretty cheap if a median income in my area was enough more than the 20% down payment for a median home in my area that it could also cover the interest for year...
Had you meant 3% + 1% PMI + 4% interest for an FHA consume 100% on median, because that definitely implies either high prices on houses or low median incomes.
1) A major difference is the fact that currently they are generally 'unfunded' in that the money isn't actually invested on your behalf.
2) The next is where the risk resides - even in cases where they are fully funded (ie: some model suggests that the returns on investment will be able to pay out obligations), there's still the issue of the risk models are wrong or investments underperform -that risk will still reside on the state to pony up the difference.
3) Lastly is the highly speculative nature of the obligation - most all pension plans use a subset of the worker's last years to determine the defined payment, so a common practice became to inform your (district, organization) that you intend to retire in 5 years, where they will then boost your pay for your last few years, thus providing a much larger pension. This esoteric issue is possibly dominating Illinois' financial problems as (from a few articles I read) retirees are receiving many times returns-compounded contributions, since their last 5 years are boosted so much over their average pay over the whole career. Gaming the system was not accounted for in the models.
It looks like a combination of semantic analysis not being there for the automation to work at the time and maybe some regulations issues (with each state probably having their own, I imagine compliance is/was more difficult)?
If I recall correctly from my bioinformatcs classes (years ago) - the non-coding DNA still serve many functions - a protective role by containing sequences which stabilize the structure of the DNA, or providing binding sites used in promoting or suppress gene expression. The non-coding are recognizable by different characteristics from the coding sections. Not to mention the fact that by definition, at least half the sequences are just the complement of a coding sequence - so putting in stop codons before and after on the complement would be useful to make sure it's not expressed. Add in structural sequences to create preferences of where it's safe to swap genes with the sister chromosome DNA during meiosis, and all sorts of other things, and you end up with quite a but of non-coding DNA still serving a purpose.
Is the process of adding 'rooms' which are actually arbitrary 'things' (like your laptop, company car, or spare parking permit which is picked up from reception) in calendar not a viable hack for some reason? I imagine this can scale to whatever you want to reserve.
This sounds like a great case for publishing negative results: it will result in meta-analysis about what practices routinely cause bad results and then those papers will be used to reduce the number of bad results. Labs keeping secrets in how to do research seems like a bug not a feature.
That's just the externalities around publishing negative results. The major reason being that it will tell people where the minefields are, resulting in people not all reproducing the same negative results.
[0] https://link.springer.com/article/10.1007/s11292-016-9261-3