CharonY

I will point out that op said something you "believe" to be true. My first thought is the level of evidence, but also the motivation to bring it out in the first place.

Sorry I missed this post earlier. So again, my criticism on your example is that the process was not flawed because it focused on First Nation people (i.e. using race as an indicator) but because of the assumption underlying (i.e. colonial attitude and white supremacist viewpoints). In addition the measure is punitive in nature, so as a better example I would like to see how a supportive race-based measure results in negative outcomes. With regard to positive outcomes, one aspect of affirmative action in college admission is that it is actually the only measure that has consistently increased diversity in the students body, which I consider a positive outcome. On the societal level, states with affirmative action have seen an increase in salary among underrepresented minorities due to access to higher education. Conversely, states that have banned such action have seen a decline in minorities attending said universities which has been associated with a decline in salaries (there is a recent article from Berkeley looking at the impact of proposition 209, for example). It has been suggested that in some cases affirmative action could place students in programs for which they are not well equipped, but there are studies in a number of countries who actually were unable to find such effects.

That depends mostly on how the current system is set up as well as whether there are historic carryovers. There are many studies around the world on many, many aspects of anti discrimination efforts and the overall theme seems to be that it is very difficult. In many areas anti discrimination laws barely move the needle and some even had negative effects. I would need to dig out things, as there is a huge heap of literature out there, but from memory (so apologies if I get something wrong), anti-discriminations laws in some countries (including Germany, USA and UK) seemed to protect retention of certain groups, but increased hiring discrimination in many areas. So, again, to evaluate benefit, you need to look at outcome, rather on the mechanism alone.

I am not sure whether you can frame it as that- after all one would need a very specific breakdown of the votes and I am not sure whether we got the data (the article is rather vague in that regard). However, some surveys indicate that those who could theoretically benefit most from affirmative action did vote more in favour than groups that would benefit least. But that aside, there is also the issue that minorities are not monolithic. As we were talking about privilege, there are increasing differences, including a rising proportion of immigrants, who generally are better of and tend to be more critical to measures such as affirmative action. Specifically with regard to Prop16 (and I have to add that I am not really familiar with it, just happened to skim the odd article), it seems that folks were also rather uncertain what the proposition would do specifically. In a survey of the Latino community foundation showed a narrow majority in favour of it, but 32% of responders actually thought that the proposition would actually mean that it would keep thinks as they are and block race as an criterion. Only 39% understood what the proposition would do (and among those 65% were in favour). So based on that small slice of info I think that there is no simple narrative that can be spun out of that proposition outcome.

And I ask again, was it based because it recognized race or was it bad because it had colonial assumptions and the resulting outcome? I am not familiar with the laws surrounding residential schools, but would it have been better if the system did not explicitly mentioned First Nation children, but only targeted children in certain areas, which just happened to be inhabited by First Nation communities? So again, should we evaluate policies solely based on their mechanisms or shouldn't we take the outcome into account?

To add to that, and to repeat a question that I do not feel has been adequately answered: why is using one criterion (e.g. race) inherently bad, if it leads to a more favourable outcome (say better health or education), whereas another one (e.g. test scores) are inherently good, if they lead to disparity and benefitting the wealthy? In other words, what is the basis to assume that certain factors are inherently bad, if not the outcomes that they cause?

And that is a big fallacy right here. Grades correlate with academic success, but not nearly as good as, say income. School districts explain more of the variation in grades than individual difference. I.e. grading is not an objective measure of performance, but rather select for folks who can afford the best preparation and schools. So if you use scores, you are in fact using a proxy for income (what you explicitly said you did not want to do). This, again is a failure of the system which creates in us the the belief that we are fair, while having a system in place that decidedly is not. I will note the graduate level however, things get shaken up a bit. I have found that scores are not a great indicator of individual performance anymore.

So you are saying denying a group of people opportunities is inherently the same as trying to provide them with the same opportunity as everyone else? Having a system that results in lower life expectancy in some folks is inherently as bad as one that tries to improve the outcome for vulnerable folks? Sorry I fail to follow that argument. As to MigL i would like to echo Zapatos'argument that AA are correction mechanism, especially as other more fundamental issues may never be resolved. And again we cannot just assume symmetry when it does not exist. Assume, for example a system of apartheid, but with equal distribution of power. Folks may behave badly to each other but inherently there is no reason to assume that one group wouldbe suppressed. If folks were racist in a system with equal power distribution, the outcome wouldn't require AA or similar measures. People would be dicks but again likely no systematic disenfranchisement. It is only when we add historic elements and power imbalance where we create an inherently unfair system, which we need to address.

I am not looking at the justification, but at the outcome. So just to clarify, you think that using certain measures are inherently negative, regardless of the outcome? Should we then or should we not for example investigate why certain outcomes such as health or education appear to correlate to certain degrees with things like associated race?

If I may add to that as a question to MigL, is it also independent on the outcome? I.e. if the outcome results in racial disparity it is as racist as a measure that results in equity. If so, I think one potential barrier in the discussion is that different definitions of racism are at play here.

I think it boils down to the issue that many people do not distinguish between institutional (or systemic) vs individual racism sufficiently nor is the context acknowledged. It ignores for example, that systemic racism can arise from measures that do not explicitly acknowledge race. Often it is phrased in the context of innocent mistakes, though they can also be part of a specific strategy. Atwater, a Republican strategist outlined the Souther strategy more explicitly: By using the broadest brush one could find one then becomes possible to equate measures that try to specifically balance out inequalities borne from such policies, with the unfair practice themselves and leverage such false dichotomies to undermine efforts to create a fairer playing field. In fact, some might even argue that because practices as mentioned in the quote do not explicitly mention race, they are somewhat less racist, which seems delusional to me at best and malicious at worst. Another issue is that many folks are so used to the unfair and faulty system, that they assume that this is natural or the the norm, whilst not realizing that all the rules are constructed, often with unfairness in mind. Of course it would be better to eradicate all unfair elements of the system (which extend far beyond things like education) but as we can see, there is a pushback even with those small measures, nevermind eradicating large, complicated systemic ones. This is in part where privileges plays a role. From a position of privilege, equality looks like a loss. Again, the reason why there are cases where race, gender or other attributes might need to be addressed specifically, is because there is a system that knowingly or not knowingly has created unfair disparity along those lines and either still creates it and/or have created such deep historic damages that the repercussions are still there and need to be addressed in order to overcome them (i.e. folks cannot boostrap themselves if someone stole their boots first). I should also add that this is a common misconception, racial quotas are explicitly forbidden in the US, but one can have efforts to increase diversity. I am not sure about the legal landscape in Canada in that regards but I believe that targets can be set internally to measure progress in creating diversity, which seems to be structurally similar. I wished that folks in sciences would be that rational. It is true that especially in medical sciences there is this huge knowledge gap and it is also true that most researchers are aware and would agree with that issue. However, for a long time it actually has been difficult to add diversity as a subject matter to a research proposal. Reviewers could, for example penalize studies that have very large cohorts if they try to address sex differences in their studies (as most at that time would simply create a male cohort). Funding agencies somewhat recently started addressing this issue by requiring researchers to at least address why they do not consider sex in their studies, but there is still a huge disparity in the type of research. A part is also due to lack of representation of high level female researchers. Minority research is even trickier to get funding (despite what some people might claim). It is again fairly recent that there are at least a few researchers who would look at such studies favourably. I personally had grants rejected at least partially because my proposed study cohort was not sufficiently representative of the broader population (i.e. had too many minorities ). Again, those are systemic issues, with having researchers/reviewers being not sufficiently diverse and propagating a certain assumption of normalcy that has massively hurt many aspects of our biological understanding.

On average fees are lower in Canada than in the US, but it is not exclusively due to how the system is financed. There are other differences that may not be universal, such as that in Canada there are often no tuition waivers for graduate students in natural sciences, whereas it is fairly common in the US. However, both are partially subsidized and both are massively higher than in countries where the costs are entirely or mostly met with public funds.

As others have mentioned, wealth and privilege are fundamentally different measures. Privilege is a relative assessment, if there is not disparity, there is no privilege. Wealth, on the other hand is an absolute measure. The education system in Canada and US seems to be more similar to me than you realize (coming from a third system). Public universities are also subsidized in the US and most of the tuition is actually carried by the states/provinces. You can find truly subsidized systems in e.g. Germany where you basically attend university for maybe 100-300 Euros, which typically also includes a public transit ticket. And here the question would be what the tie-breaker should be? Typically being a legacy student had the highest benefit, but also simply living in a good school district (as those boost your scores). Likewise being well-off or simply being in an area where you have access to extra-curricular activities increase your chances. What admission officers do is actually looking into personal backgrounds and folks with high scores but coming from traditionally underprivileged schools get a leg up. That to me sounds like evening the playing field as you mentioned before. What they do not do as some folks think is to bluntly boost folks based on race or ethnicity. Another common twist is to claim that folks actually discriminate against whites or Asians (using them as the well-known model immigrant argument). However, the actually implementation of these measures is that race-based limitations are lessened- to a degree. Universities are actually not allowed to specifically address structural racism (and again, if there are confusion about what that means I am happy to discuss this in another thread). In the US at least there is a ruling that universities are allowed to use a broad range of factors (but never race per se) in order to fulfil certain goals, such as increase diversity on campus, which has many benefits (and having led research groups and taught students in low- as well as high diversity system has made me a believer). As iNow has mentioned, the way we measure is inherently flawed and measures such as affirmative actions are imperfect measure to address at least some issues, but they have been grossly mischaracterized. It often neglects the structural issues we have by asserting that the way we rank our students without use of affirmative action is objective or (even worse) "normal" but it ignores the history of it and how folks with influence constructed our education system and the way we evaluate academic potential. It is interesting, for example that legacy and athletics (which both happen to be major reason for white student admissions) are not terribly controversial, whereas ethnic background as part of individual histories is. As a real example that I heard, two persons with similar scores, but one coming from a well-off family, with an alumnus parent. Another, resettled as a refugee child, struggling with the English during middle school but working their arse off to graduate top of their class. Sure you can abstract the whole story to a degree where you eliminate things like race or their country of origin. But to me that actually sounds more like the type of sanitary political correctness that some folks like to complain about so much. That is actually not true. Asian Americans were less beneficiaries of affirmative action, but rather they profited by having certain barriers removed that were in place. Of note, the majority of Asian Americans still support affirmative actions for underrepresented minorities, but they are not part of that group (as a whole). This is a whole different can of worms, as often Asians are viewed as a monolithic group but actually exhibit massive disparities within (the largest among all ethnic groups, IIRC). But as the group as a whole is comparatively small they are often leveraged for these types of discussions, whether they like it or not. In fact recent legal challenges against affirmative action have been using Asian Americans as an example why it is unfair (though again, it appears that Asian community is not quite on board with that). It is also a bit interesting to me that the whole admission process is viewed as if anything other than white is a result of affirmative action. It is kind of based on the assumption that white is the accepted norm and anything else is kind of an ancillary process. But this, again, is yet another can, but closely related to the structural issues mentioned before.

Yeah, it is odd that they accidentally injected some with half the planned dose, which is a weird thing to happen in a trial.

It is often difficult to predict how the immune system reacts and how (and whether) it generates long-lasting immunity. In this particular case I cannot tell you what happened, but it is common that the reaction of the immune system have weird, non-linear relationship. Which is why statements like "strengthening the immune system" are tricky as it consists of feed back loops on many levels involving many different cell types. There are cases where initial strong responses are not building up memory, for example, which might be the case here. However, it must also be noted that it could be an issue of small numbers, as the half-dosage group effectively splits the total cohort. So it could also be a statistical fluke at that point. I should also add that there is not just one immune response, the immune system fundamentally has different elements, and typically when we talk about vaccinations we look at the adaptive response. However, the innate immunity also plays a role and interacts with adaptive responses. And even more complicated, in vertebrates now also something similar to innate memory has been discovered (often called trained immunity).

The AstraZeneca vaccine seems to be working, too. They had 131 infections. However, they tested two dose regimens, with one (halved first dose and standard second dose) seemingly being more effective (90% vs 62%).

At this point it is pure fantasy. You might as well imagine some random sci-fi method and give it a cool name.

No we cannot do that, either. We take it from another cell.

The issue is when some archers are allowed to move and others are not.

You can enucleate a eukaryotic cell and put a new nucleus in. We cannot build cells.

I doubt it. It is more that before the trials mRNA vaccine candidates so far had low immunogenicity and it the approach was considered to have a low success rate. The technology was around for some time, but it was not considered to be that competitive to traditional approaches. That is also why the drugs were developed by somewhat smaller companies, which have been working on drugs since 2005/2013, respectively, rather than being adopted by the big pharmas. Especially in the middle of an outbreak you would want a vaccine that creates strong immediate responses rather than multiple dosages, which is likely another incentive to go the traditional route. Considering that up until now no mRNA vaccines had been approved it is a high-risk scenario where the vaccine might have failed for a number of reasons. On top, there is still the issue that we won't have any long-term data on mRNA vaccines. It is really because out of despair and necessity where mRNA vaccines have been propelled to prominence. And in the end, it is crucial to have a range of methods available as we won't have the time to gather sufficient data. Despite promising phase 3 results, we have no guarantee that it will play out the same way in the broader population.

It is actually still in a trial with around 60k people. I do not think that they have released results yet. One interesting bit about this one is that it is developed using traditional approaches and looking at the paper it also seems to have a faster immune response.

They still need to go phase III, though.

It depends on at least two things. First, the endpoint measurement. I.e. how did you determine a positive event. If a trial consists of regular testing of even asymptomatic folks your final infected cohort will contain cryptic infections. If you only measure symptomatic cases, your study will ignore those. I do think that the trials are likely only focusing on symptomatic events and are therefore comparable (but I could be wrong). The second issue is that the number may be derived from a differently sized infection cohort. If you only have very few infected folks the numbers you get can be highly biased. Therefore any efficacy measurement with a small cohort is unreliable. There are therefore target numbers that the study has to hit, which given infection rates turn out not to be a problem. For rarer diseases this can lead to very long trials. Yes that is the basic idea. You create two cohorts that typically are similar in composition (to avoid bias) and then let them out in the wild and see what happens. The Null hypothesis is that after some time both groups should have similar infection rates if the vaccine does not do anything. What folks hope to see is that among the (much smaller) infected group, we see disparity between treatment and control. The big challenge is to get enough folks infected and there is a risk of confounding factors leading to who gets infected in the first place. The idea is then that both (control and vaccinated group) are similar enough to each other to cancel that out. That is potentially not always the case. Just as a random example, it is possible that the vaccine does not work for elderly female Asian folks (for some reasons). But since so few are in either group we have no information about that.

It would fall until the emergency approval pipeline. Herd immunity would take at least another year according to projections, assuming there are no further restrictions.