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That is a pity as in the article they referenced the paper (as well as some others) that the article was based on. Since the one writing the article is not a journalist but actually one of the co-authors, it is also more accurate than many articles you may find. Anyhow, look at those: Cheng et al. Ocean Sci., 12, 925-935, 2016. Also of interest: Cheng et al Science Advances 2017 Vol. 3, no. 3, e1601545 Trenberth et al. JCLI 2016

You may be thinking of backtesting or hindcasting. Which is a way to look into the accuracy of temporal models. I.e. taking a certain time frame to build the model, build in assumptions in terms of forcings and then run the model and compare it with the full historic data set to see whether the assumptions are correct. More impressively, since many models were created a while ago, it is not possible to also look at the predictions people made a decade ago and see whether they hold and for a number of the most important ones, it seems to be the case.

A little while ago Bill Bowder has given his testimony to the Senate. While it is not specifically about the Trump administration, it provides the backstory the Magnitsky act and why Natalia Veselnitskaya was interested in it.

Actually I would be careful with generalizations in that regard. There are studies that indicate that sexual selection often favours dissmilarities in major histocompatibility complex genes. I.e. people prefer people who are genetically dissimilar (and hence likely to look different). The reason being that a larger variety in these genes offers selective advantages to combat pathogens. A difficulty here is the large numbers of covariates and the complexity of outcomes (such as stability of relationships). For example, having a similar background can lead to more stable relationships as one shares a similar language and beliefs.Also, people with same background may also be more genetically similar. If one only considers genetics, one may assume that the basic is genetic, whereas it just coincides with the actual determining factor.

I am always surprised how the discussion on this topic devolves every time. The discussion could very well end by stating that a varied diet with low amount of meat is associated with better health outcomes. Depending on the individual, some variations are healthier than others. If one had to choose between only meat diet or only vegetable diet, the latter is associated with better health. However, especially those that are prone to certain deficiencies (including children, elderly, etc.) benefit from at least some levels of meat (at which the negative effects of high-meat diets virtually vanish) or at least require supplements (which in itself can be problematic).

To clarify, the calculations were based on the nationwide likelihood of a white candidate being accepted with affirmative action (25%) and without (~26%). It is not the rate of students actually being impacted (Bowen and Brok). The impact is actually concentrated on the minority population. I will add that the calculations were done around 2000, but numbers from 2012 Harvard admission data also found a maximum increase of 1.2%- and that is under the assumption that none of the minorities would have gotten admitted without affirmative action (which is clearly laughable). If we want to discuss how many more white students would be admitted, the increase is less than 1% (I believe around 0.3%, but I have to hunt down the source again). Quotas would mostly impact Asians (the shift in admission chance is closer to 5% IIRC). However, I find it interesting that the discussion is often about how it unfairly benefits e.g. Hispanics or blacks but not how it actually also benefits whites over Asians. I.e. if you are Asian, it is more likely that a white person took your seat than a black one (simply because there are more white candidates). I will have to look at numbers, but I think especially in highly competitive schools abolishing affirmative action is likely to increase Asian population, rather than white. It is important to note that affirmative actions are not quotas. They are more like guidelines, which allows admission officers to take race (which often can be correlated with school districts) into account in what is described as a holistic approach. This also includes e.g. extracurricular activities. Especially the latter can be said to further disadvantage groups that have less access to such activities, be it for financial and/or infrastructure reasons.

Take a look at Sicarri's post and try to reconcile it with your assumption that fentanyl is a) replacing oxycodone in use, b) that it is pushed by the government and c) that its ban would solve the overdose deaths.

There are a number of viruses, including the family of Human endogenous retroviruses. There is a nice overview article that you may want to check out: Nelson et al. Mol Pathol 2003 11-18.

One tricky bit is that for prescription typically only total opioid prescriptions are monitored, but not the individual types. That information is more often indicated in overdose cases. However, as shown above, the number of fentanyl prescriptions remained steady over the last ~5 years, whereas overdose cases massively increased. So even if there were some kind of pressure, it apparently had no effect on prescription rates.

One thing that one should add that the effect for the majority is actually really small. Studies as early as in the late 90s (Kane 1998) have shown that racial preferences are a) concentrated in the top universities and b) even in extreme calculations the likelihood for admission of non-minority student barely changes (roughly around 1%).

Indeed. The problem is clearly multidimensional and at minimum better means for the treatment of addicts are needed, but also alternatives to pain control to reduce the significant proportion of addictions that arise from the legal use of prescription drugs. Unfortunately, as history has shown, if there is a demand, supply finds its way.

Excellent. I had hoped for didactic reasons, that OP would search for it, but since you did all the work, it should be sufficient to challenge the assumptions. One thing that I forgot to mention is the formulation of tamper-free oxycodone, which cannot be easily crushed. Its introduction is strongly correlated with the sharp increase in heroin use, further showing that addicts turn to illegal sources when deprived of one. Controlling legal routes of the substance in itself does not seem to be sufficient to curb deaths.

I think it depends on how you define digestion. Normally it would refer to an active process involving e.g. enzymatic actions. I guess, in a pinch you could also describe the release of compounds from a tablet as digestion, but personally I would find it slightly unusual. That being said, ibuprofen is usually delivered in a racematic formulation and after absorption by the body there is a conversion from the R- to the S-entatniomer, IIRC,

You are correct, of course. I mistyped.

I agree with that. But a few issues and I will let the thing rest. Most hospitals in Canada are not government owned, but run by non-profits. The financing is run by the (provincial) government as far as I understand. Moreover, in a malpractice lawsuit usually the medical provider him/herself is getting sued. This is why all physicians are covered by the medical protective association (which is basically a non-profit liability insurance). So in order to sue the government one would likely have to prove that somehow the practice is connected to something the government has issued, like for instance the Sexual Sterilization Act of Alberta. With regard to the tribunals, I would urge you to read up on the proceedings, even without the torture, there were flawed in many ways, including witnesses changing statements as to who may have thrown the fatal grenade. Either way, the proceedings have been tainted from the get go and it is unclear how it would have ended if it had ended in criminal court. Assuming that it is a sure thing is, at best, a gross distortion of the happenings. But that being said, it should not be an either or situation. Human rights have to upheld for all citizens.

In other words you cannot point to any specific regulation. Sorry, but you are pushing a narrative without evidence. In order to have discussion you should read some reports and maybe look at the odd graph. Let me ask you a few questions: a) which class of opioids has caused the most deaths in the last five years? b) are illegal or legal sources more commonly connected to fentanyl deaths? c) what are the currently the most commonly prescribed opioid drugs? d) are there regulations, and guidelines that affect opioids but exempts fentanyl? Unless you start to look and discuss data I see little value in continuing the conversation.

There is no comparison. First of all so far only one woman is attempting a lawsuit, the rest chose to remain unnamed and it is still unclear whether there will a class-action lawsuit. However, the report may add fuel to that matter. Second, the lawsuit cannot be targeted at the government, it will be against the health provider. I assume that their budget is more limited in terms of what a lawsuit might claim. Third, the Khadr lawsuit (which is off-topic) was based on violation of rights by the government as judged by the Supreme Court (I believe essentially when Canadian intelligence officers engaged in interrogation, but I would have to read up on the supreme court decision). As such the only decision your government could have made was fighting a losing legal battle. Fourth, even if there is circumstantial evidence, Khadr's trial and conviction is considered to be questionable by legal experts. So sorry, except it happening in Canada I do not see a lot of parallels to draw here.

I do not think that the snark is warranted.

You are telling a weird story. The arrest of MDs who were prescribing massive amounts of unneeded or fraudulent prescriptions is clearly not an example of government pushing fentanyl. Also, can you kindly point me to the regulations that would specifically target oxycodone but exempt fentanyl?

The DEA has no medical authority in the end it is the medical professional who makes the decision. There was a crackdown on illegal oxycontin distribution, which first led to a rise in heroin and fentanyl use. Much of the deaths by fentanyl are caused by heroin laced with fentanyl. If we consider prescription drugs as one route of addiction, it does not really matter on which drugs people get hooked on. If opioids of any kind are used for long-term treatment, addiction is almost a certain result. For this specific route alternatives have to be sought.

There are several things to consider. One is the fact that illegal production and distribution of fentanyl has increased since 2012. There is also an increased scrutiny for legal distribution. But even in health care systems that are public (as Canada) the rate of opioid deaths have been increasing in recent years. Interestingly in some areas oxyconting were removed from drug plans, yet overall death rates increased. The reason being that other opioids just rise in popularity. The rate is higher still in the US, but a private vs public health system is clearly insufficient to describe the effects. In both countries there is an overprescription, which ultimately indicates inadequacy in dealing with chronic pain.

What makes you think that the government is pushing fentanyl? Or oxycontin for that matter? Or do you equate not banning with pushing?

Yes. In fact ~5% of our genome is assumed to be of viral origin. it is relevant to note that they are also generally silent, i.e. they do not actively produce viral particle. One theory postulates that longer co-evolution results in viruses become less virulent and eventually just become passengers on the ride.

Actually, seems I am wrong again.

Hard to tell without looking at the actual data, but two possibilities are high template concentration leading to the software messing up baseline correction or, conversely, low concentration/inefficient reaction, starting off with non-exponential replication until template concentration reaches a threshold to allow higher amplification rates. The latter is rather unusual, though. First thing to test would be a dilution of the sample and see how the curve shifts.