I think the philosophical question is not as to which of our "models" (beliefs, ideas) are "exact representations of an external reality" (whatever that could even mean), but as to whether our beliefs and ideas can more or less reflect an external reality. — Janus

They do, some more than others. That's what I'm saying. We can't but believe in some external reality which our representations reflect, we also would be naïve in the extreme to not even believe we can be mistaken. So the question is already trivially answered.

Thus the only question of import is, given any particular belief, to what extent is is caused by an external reality and to what extent by internal assumptions. That it is, in some proportion, caused by both, is something we can't help but agree to, so it drops out of the conversation (or should). The actual proportions, in each case, are what matter.

At what point does the data on death from heart disease go from "prevalence" to "risk", exactly? As I said before, if you narrow the range it's still the prevelance -- just a more specific prevalence (like the prevalence of dying from heart disease for people over 65 and male versus overall prevalence). — Xtrix

The answer to your question is in the post. You even quoted it.

If we don't know the ORs, then failing to take them into account is irrelevant since they could be anything. If we know the ORs but ignore them, you're not basing your decision on risk anymore. — Isaac

Clearly I should have explained. If I know all the factors determining the fall of a coin, then the chance of it landing on either heads or tails is 1, I know it will land on tails because I know the starting state and all the variables determining its trajectory (assuming determinism - we can get into quantum fluctuations, but the definition doesn't require we do). It would no longer make sense for me to say the odds of this coin landing on heads is 50%, I know it's going to land on tails. The prevalence of coins landing on heads is still 50/100, that hasn't changed, but the odds have changed.

So the odds (chance/risk whatever term we use) are a measure of my uncertainty, whist the prevalence is a measure of the occurrence in a population.

You asked where we stop adding variables. Never. We include all variables. So what if there's an unknown variable? Well if, say, the starting position {S} (heads/tails) may affect the fall of a coin, but it's not a variable whose affect I know, then the chances of S(heads) making the coin more likely to land on heads is 50/50 (I don't know). The chances of S(tails) making the coin more likely to land on heads is also 50/50 (I don't know that either). I we multiply those two ORs by the un-affected prevalence, we still get 50% (0.5*0.5 - S(heads) + 0.5*0.5 - S(tails)). So we haven't ignored this unknown variable, it's just that its as likely to affect the result one way as it is another so including it doesn't affect the risk. If, however, we had a variable whose affect we did know but we excluded it, we're not doing risk assessment any more because we're not measuring our uncertainty, we're just talking about the frequency of some event within a population (prevalence).

Because we are wired to, yes? So it's all Kant by way of Darwin. — Srap Tasmaner

Sometimes. But the point I'm making is really just that it's scalar, not binomial. At one end is something like the very concept of an external world (totally wired in), at the other, mirages (we all know that we've probably mistaken the perception)...

We recognise that our models are guesses, an amalgam of external causes and internal assumptions. The question is over the proportions of each in any given representation. At one end we act as if there are few assumptions and mostly external causes, at the other end we act as if our representations are mostly assumption with a sprinkling of external causes to pin it all on.

If the relative proportions of a matter are in dispute, it's almost certainly some matter which is at neither end, so arguments demonstrating that such ends exist are not really relevant to those matters which are in dispute.

Since you can always gather more information, by your definition nothing is risk-based. — Xtrix

Risk is determined by variables. Assessing the impact of those variables is a risk-based decision. Ignoring them is not. It's nothing to do with always being able to get more data, it's about what we do with the data we've already got.

I was discussing was strokes -- whatever your discussing, I can only guess. — Xtrix

Why were you discussing only strokes? Did I imply the points I'm making applied only to strokes? I'm discussing the calculation of a variety of risks using known variables.

Let me try one more time: 150/10,000,000 = 0.000015%. That's some pretty easy mathematics. — Xtrix

I'm asking how you get the risk from the prevalence. You've just divided the total cases by the total population of the sample. That gives the prevalence. I'm asking for the maths you're using to get from there to the risk.

Let's say everyone in that group was over 65 -- what would someone's, age 65 years or older, odds be of getting a stroke in that case? — Xtrix

It would depend on their measures for any known variables affecting the likelihood of strokes - high blood pressure, atrial fibrillation, smoking, drinking too much alcohol, poor diet, a close relative who has had a stroke, high cholesterol, diabetes, being overweight, sickle cell disease, frequency of migraine with aura. All of these factors have ORs, you multiply the prevalence by the combined ORs for the person (combined dependant on co-variant factors). That's the risk. If we don't know the ORs, then failing to take them into account is irrelevant since they could be anything. If we know the ORs but ignore them, you're not basing your decision on risk anymore.

it's being fed to us by the government. What is worse, we can not communicate with the government, the government does not discuss with us. — baker

Yeah, something that's been consistently muddled here is the representation of data, via policy, and the actual data itself. It's true that a layman may not always be in a position to assess raw data (althought it's not impossible), but to infer data from policy requires a whole slew of assumptions about the institutions doing the policymaking, and we can't ask about those, nor about the degree of certainty.

If we imagine, hypothetically, a group of completely unbiased experts with no priors analysing the same corpus of evidence. If that corpus was 51% supportive of strategy x and 49% against, then every expert would support the strategy. Your poll of experts would come back with 100% support, but this is, obviously, a measure of the frequency of each binomial decision, not the frequency of different degrees of evidential support for it. If the corpus was 1% supportive of strategy x and 99% against, the poll of experts would come back exactly the same. In other words, the poll of experts clearly doesn't contain anywhere in it the data about certainty. For that you have to ask.

You say this as if your responding to something I've said. — Hanover

Oh, sorry. It was related to...

your argument is the "appeal to the stone" fallacy — Hanover

...which I should have clarified. The appeal to the stone was (so far as I understand it) supposed to refute idealism by referencing the fact that we treat things like stones as immutable facts of reality regardless of Berkeley's proposition. I'm saying the opposite. The fact that we treat stones that way has no bearing at all on the matters at issue. We all (Berkeley aside), treat some representations as immutable and others as not. The matter at issue is in the grey area where some would like to treat some given representation as immutable and others would rather not. Here the former team appeal to the stone, the latter appeal to mirages. Both are wrong because the matter at hand is clearly unlike either otherwise it wouldn't be in dispute.

Is this universal, or does it differ from person to person? — baker

I think some matters are set in stone and other vary. The very idea of an external reality I think is one such. For me, it's the difference between models within brain regions with high redundancy and models formed by the meta-structure of those regions. For example, one's model of the relationship between muscle movements and visuo-spatial awareness of limbs can be quite easily modified, but there's a structural relationship between the visual, spatial and proprioceptive areas and object vs spatial systems which I don't believe it's possible to modify.

Also, there's considerable evidence that models of things like basic physics develop in a relatively predictable order during cognitive development, so it seems likely that these are biologically driven (environmentally influenced) rather than the other way around. Whether that makes them impossible to genuinely doubt though is anyone's guess.

I mentioned the variety because I think talk of 'real' and 'not real' is just unhelpful here. We use models with differing degrees of certainty, that's all. There's no need for a binomial distinction.

In my example, the challenge is "try it and see", which still strikes me as an epistemically healthy attitude. — Srap Tasmaner

Depends on what you do with the 'see' bit. If I were unsure of the location of an oasis, would we verify it by looking down the road and 'seeing'? No, because we're used to mirages, they're part of our belief system already, so when we 'see' what looks like an oasis we automatically distrust that particular feedback from reality.

So when Hanover fails to lift the car, why trust that particular feedback from reality? It's not currently part of you system of beliefs that such feedbacks are unreliable - we know about mirages, we don't know about 'saw-a-man-fail-to-lift-a-car-but-really-he-did's.

The point I'm generally making here (and this goes for @Hanover as well) is that no-one assumes all of their models are exact representations of an external reality, and no-one assumes none of them are. The choice over which we behave as if were true and which we approach with uncertainty is a psychological issue, not a philosophical one.

Understanding that 150 out of 10 million is a low risk doesn’t warrant the term “expert,” true. — Xtrix

I have supported them with real data. I cited the study— and there are many more. — Xtrix

The claim of yours I'm disputing is that national prevalence rates are used to assess individual risk even when there are known varibles. So I don't know why you're responding as if I'd questioned your knowledge of what the national prevalence rates are.

The reason you and others continue on like this is because it’s been politicized. — Xtrix

And the reason why you continue on like you do is because you've found a flag you can waive which makes you feel like the virtuous hero with absolutey no risk of ostracisation from your group identity. We could psychoanalyse each other, or we could talk charitably. I don't mind which.

Risk analysis is done using national figures all the time. I did it myself — Xtrix

I'm talking about proper risk analysis, not whatever you just did. My claim is that it's not actually risk-based. What you call it, or think it is, is irrelevant.

Maybe it goes slightly above or below overall numbers — but not by much. Why?

Because 150 strokes out of 10 million people, for example, is astronomically low. — Xtrix

Show me the maths then. What is it about 150/10,000,000 as a prevalence rate which makes it impossible for any cohort to have a high risk. As far as I can see there's a potential cohort of 150 for whom the risk is 1.

If it turns out that 90% of those 150 people were over 65, that’s important to know — no doubt (especially if you’re over 65). Does that significantly change the overall odds? As I mentioned before: no, it doesn’t. It simply means if you’re over 65, you have a slightly greater chance of having a stroke after taking the vaccine. — Xtrix

That is changing the odds. It's literally what changing the odds is. You've taken one odds (the national prevalence), and you've changed them to get the risk for a 65 year old.

it doesn’t change the odds much at all — perhaps by 0.00001% or something to that effect. — Xtrix

For some variables that may well be the case. For others we know it's much higher. Obesity, for example has an OR of over 13. Age above 65 even higher, making your estimate more than a thousand-fold out.

How do I support this claim? With mathematics — which can be checked by everyone. — Xtrix

I've yet to see any mathematics, despite several requests.

that's not what you were asking for. Thus, it's not an example of what you were asking for. — Xtrix

So an example has to be exactly the thing itself? That's an unusual interpretation. I'll try to be more specific for you. Variables which we know to affect the risk from the virus (recall we're talking only about the risk of harming others - either by using up medical services or by transmitting the virus, or by contributing to one of the many social and economic consequences) are; Age, sex, obesity, comorbidities, social density, living arrangements, geographic location...and then there's all the variables which affect the social and economic consequences; trustworthiness of the corporations and institutions involved, stability of the economy involved, extent of foreign aid, the state of the virus, the infection rate in the rest of the world, the psychological effects of any course of action, the response of the media, the chaotic effects of mass rapid communication media like Twitter...These are the variables I'm talking about. all will affect the risk from any given course of action, some in known ways, others in unknown ways (but where the direction of change can be reliably predicted - ie reduce or increase the risk).

the 0.00015% still applies to you in the same way a roulette wheel does. — Xtrix

Your decision can be risked based without having individualized numbers for yourself, which don't exist. — Xtrix

Those risks are minuscule -- no matter how you slice the data. They remain so. — Xtrix

the national statistics are still important. If there are 150 strokes per 10 million cases, you can carve up the 150 into males and females, older and younger, etc. -- and I'm sure you'll get some variance (much more likely to occur in the 60 and older subset, for example). Does that really change the risk all that much? No, not at all. — Xtrix

But to argue there can't be "risk analysis" without doing so is disingenuous at best. — Xtrix

As I said to Tim on the other thread, I'm not conducting a poll. This is a discussion forum. You're not an expert on risk, so either you have a serious ego problem, or you need to support your assertions, repeating them contributes nothing to the discussion. If you think the national prevalence is still relevant to a risk-based decision even when we know that key variables affect the risk (variables we also know our values for), then you'll need to explain how. As it stands, risk analysis is not done using national prevalence figures, so if you think it ought to be, the onus is on you to explain how. Simply repeating the view over and over is not convincing.

I argued for reality mediated by perceptions, with an assertion there was an objective underlying reality that was dubiously knowable. — Hanover

Right. So in what cases does the dubious know-ability of reality come in to play? Is it a model you often use to counter the argument of your fried Bob, that he can fly to the moon? I'd wager no. It's a model used to counter the argument of Bill that he can lift 170kg if he believes he can. "No, your belief doesn't make something real, you either can lift 170kg or you can't" Of course you may already know about the placebo effect and so not counter this way, but this is about the effects you don't know, not the ones you do.

The difference, as far as I can tell, between anti-realism and idealism is that anti-realism is anti-realist about something. That something might be objects, moral laws, numbers...etc. To be anti-realist about everything I admit probably would sound a bit like idealism. So the distinction between the anti-realist and the realist is over the matter of what exactly is objectively real, not the matter of whether anything is.

My point is that the 'what' in question is rarely some limit that neither side will ever encounter anyway (@Srap Tasmaner's car-lifting example). Our agreement or otherwise as to the extent to which these far-off limits are real rarely enters the picture. The 'what' is always some matter which...matters, and here it's the extent to which reality limits our representations that is in question. The anti-realist wants to remove the shackles they so dislike, the direct realist wants a stick with which to beat his opponent on some matter of dispute and "it's objectively the case that..." makes a great stick.

But you want to make it about me, ↪Isaac
? Cool. :) — jorndoe

As I said to @Olivier5 above, the 'evidence on the ground' as you put it, the broad picture, is so utterly uninteresting entirely because it is so unarguably the case. COVID is a real pandemic, killing millions. The vaccine, lockdowns, masks and social distancing have all helped to bring down the numbers of people dying. All those techniques are generally safe and effective. No one in their right mind would argue against those positions, and, more importantly, no-one here has.

So the only interesting thing to discuss (for us laymen) is the response. The beliefs and tactics of the people - yourself being one of them - either advocating or dissenting from the set positions.

My little car weighs about 1100 kg. The current world record for a clean and jerk is 166 kg. — Srap Tasmaner

Yes, there are limits, the point is reality still doesn't arbitrate in the way naive realists would like here. Note the current record. We know there's a limit, we don't know where it is, so we're no closer to objective reality, only the pragmatic assumption of limits so extreme that they rarely feature in any real world implication of realism/anti-realism. Hanover can't lift the moon or fly to the sun, but when people argue about objective realism they're not doing so to disabuse others of such notions. They do so to lend authority to the very mundane parameters, the concretising of which anchors their belief systems against change. To disabuse others of quite possible extensions of our current limits that conflict with their preferred narratives.

But I've made this point already, I just thought I'd do it with a citation this time.

the problem tends to be exacerbated by the issue of funding. As in any other field, whoever provides the cash gains the ability to exert influence. And when foreign powers get involved, things can go seriously wrong very fast .... — Apollodorus

There's no obligation to take funding offers. I've turned down research opportunities because I didn't like the organisation funding them.

the one you're after — Isaac


? — jorndoe

Take a look back at the number of wildly sensationalist pro-establishment articles you've posted, without a single complaint about their tone or use of rhetoric. One turns up questioning the scientific establishment and you're suddenly a deconstructionalist.

Now see if you can get the joke.

As per this old comment, I'd watch out for the slant they put on their ("impartial") articles.
(And with "REVEALED", now a bit pseudo-sensational, too.) — jorndoe

The BMJ article is more measured.

I'll continue to look for the one you're after though "Everything's absolutely fine, no-one did anything wrong because all our scientists are saints who are incapable of any deception or bias, nothing to see here". I think possibly the NEJM ran that one, I'll check.

if you claim your time at the gym has really been paying off and you could lift my car over your head with ease, it's natural for me to say, "Prove it." At that point, I let reality do the talking for me. — Srap Tasmaner

Lovely bit of research to muddy those waters.

https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1460-9568.2008.06344.x?deniedAccessCustomisedMessage=&userIsAuthenticated=false

@Hanover's belief about whether the time at the gym has paid off affects his car-lifting abilities. External reality's not so strict an arbiter as you might like it to be here.

IMO China is run by brutal dictators with an appalling human-rights record and a very long history of suppressing ethnic and religious minorities. — Apollodorus

I don't think that need be relegated to an opinion.

how do you get rid of dodgy scientists and professors? — Apollodorus

First and foremost the fault lies with the scientific community. In my opinion...

1. Nothing which is not fully pre-registered, should be considered a valid study. Full stop. That means data gathering, exclusion policies, statistical methodology (including any code), and significance limits.

2. Studies which refuse to publish their raw data should likewise be rejected.

3. Journals should actively pursue conflict of interest statements - it's about the most important aspect of peer review and currently it's treated like it's a token exercise.

4. Journals should publish null results in good proportion to positive ones.

5. Industry should not be allowed to fund, lobby, or employ from key research fields.

For anyone who thinks the above sound like the sort of reasonable and fair standards good studies probably meet, none of the studies relating to COVID vaccine effectiveness has met these standards, not a single one.

The pandemic has done serious damage across the world. If China's rulers have any culpability in this, then I think it stands to reason that they should be held to account. — Apollodorus

It's not China we need to worry about. It's the extent to which the medical establishment are hopelessly tangled up in this. After having published a disgraceful set-piece letter to which leading geneticists obediently put their name, The Lancet initiates a 'task force' to look into the whole matter on which is the same fucking person who funded the damn thing and wrote the letter denying it was possible. If anything China are just being used as a conveniently deniable tool, just like offshore interrogation centres were.

https://www.bmj.com/content/375/bmj.n2414

This is the same academic establishment whose 'consensus' is apparently so beyond rational reproach.

The data is never good enough for you. — Olivier5

The data is fine. Not as good as it could be, but mostly fine. What I take issue with is the refusal to address it in favour of these huge broad brush simplifications that institutions like the media and public health announcements deal in.

If that's all anyone wants to discuss then this whole thread is pointless. There's nothing whatsoever of interest there.

-Are a lot of people dying from COVID? Yes. Tragic global event. Dull conversation.
-Are there discrepancies in the way COVID deaths are recorded which might have implications for risk analysis? Yes. Global import, much lower. Conversational interest, significantly higher.

-Is vaccination good public policy? Yes. Very important message to get across. Totally dull conversation.
-Are there issues with the vaccination program (even though they don't necessarily effect the overall public policy)? Yes. Not a very important public health message. A significantly more interesting topic of conversation.

If all you want to talk about is the easy, broad issue stuff that anyone sane already agrees with then I can't see how a discussion forum is the best place for you to pursue that interest, particularly one focused on philosophy.

the best estimate of risks — Olivier5

Is the prevalence of deaths from COVID the best estimate of risk available for any individual? Is the national R0 value the best available estimate of an individual's risk of transmission? Are global deaths to date the best available estimate of future global mortality risk? Is the current economic and social impact the best available estimate of future economic and social impact?

No, no, no, and no. And yet they're brought up again and again as if they were counter arguments to risk-based strategies.

Risk analysis is not perfect, but it's a damn sight more complex than the naïve presentation of national prevalence statistics we see posted here masquerading as serious analysis.

Don't you disagree all the time with me here? Ask yourself where does this compulsion to disagree come from. — Olivier5

I was referring to the disagreement/agreement alone. The thumbs up, the "I agree", the throwaway, emoji...

I do. You are asking others to do your homework for you. But nobody cares about you enough to give you these numbers... — Olivier5

So, no then.

One last try. If I say "if you don't shoot me, then I'll live to see another day" am I asking you to shoot me?

I trust nobody is stoping you from trying to calculate your individual risk. Don't ask others to calculate it for you though. We don't give a rat's ass. — Olivier5

Still having trouble with the actual line of argument I see.

if you can't produce figures for my risk then my decision is not risk based is it? — Isaac

Do you understand the point of this sentence at all? It's in the form if A then B right? So if A is the case, then B follows. How do you get out of that the notion that I think A ought or ought not to be the case? Talk me through the thought process that lead you from reading a perfect clear use of a conditional to a notion that I'm advocating for one of the elements in it.

Let me try to make it clearer. If I say "if you can't produce your ID then I can't let you in", am I suggesting that you ought to produce your ID? No. You could simply not produce your ID and I not let you in.

Or try "if you don't give me a pencil, I can't write my name", you might well still not give me a pencil and I not write my name, yes? Nothing in the line of argument advocates for you (or anyone ) providing me with personalised risk data, it is an argument claiming that without personalised risk data, the decision is not really about risk.

To be honest, I find the whole notion of agreeing and disagreeing in a medium like this completely baffling, but I'm here to learn.

There's that saying -- "People of substance don't post much on internet forums."
I agree with this, and its obviously ironic implication. — baker

Social media, and the way it shapes social beliefs, is the issue in the social sciences. Any social scientist who isn't deeply invested in finding out how these new modes of interaction work simply isn't doing their job properly, and any who think they can do so from the sidelines alone represents exactly the problem with social science.

Online communication would probably look quite different if everyone would post from their offices, fully dressed and presentable, with laced shoes. — baker

That's is entirely, without fail, the conduct of my posting habits. Except maybe the train or the canteen on occasion.

Great -- but that's not what you were asking for, when discussing "MY numbers."

If this counts as the kind of number you want, fine -- then simply divide the vaccine data into men and women, and compare rates of death. They'll be exceedingly low in both groups -- but at least you'll have what you wanted. — Xtrix

You asked for an example. You know what an example is, right?

If the probability of having a stroke is .000015%, that pertains to you as well -- as much so as a roulette wheel. — Xtrix

So there are no variables involved at all? Strokes are a random event, like the roulette ball? Do you have any supporting evidence for this. It's not my area of expertise, but I thought strokes had physiological causes.

So you agree the vaccines are safe. Fantastic.

So what's the problem? — Xtrix

Literally everything I've written over the last200 pages, but by all means don't let what I actually write get in the way of your little avatar of me against whom you're arguing, it's a fantastically grotesque golem and you seem to be having enormous fun fighting it, I wouldn't want to get in the way.

Above average for what? — Xtrix

The variables which influence the probabilities we're talking about. But I see from your roulette wheel example, that you're of the opinion that probabilities are not influenced by variables at all and that every event we might discuss is basically random like a roulette wheel. That would explain why you're having so much trouble understanding this. Of course it wouldn't explain why you bother, say, putting a seatbelt on. If your risk of dying in a car crash just is exactly the prevalence of car crash deaths then there's little point, you can't do anything about it, it's just random, like the roulette wheel...

When you want to weigh the risk of flying in an airplane --" sorry, it's just prevalence, and doesn't pertain to me, because there's not a number risk number for me specifically." — Xtrix

Well yes. The prevalence of dying in a plane crash as a measure of risk definitely doesn't apply to me if I don't fly. It doesn't apply to me if I only choose the safest airlines, it doesn't apply to me if fly six times a day, it doesn't apply to me if refuse to put the seatbelt on when instructed, it doesn't apply to me if I'm elderly, frail, or otherwise compromised... I'm delighted to have found such an unusual view of risk, but I'm struggling to see how it's maintained in the face of such obvious evidence to the contrary. The prevalence is a sum of the effects of all the variables, any individual will have their own unique measure in each variable, only the average in all variable will have a risk approximate to the prevalence. At least that's how it's normally done. You've yet to walk me through this new maths of your. So please...you have the prevalence of an event, your claim is that you can go directly to a calculation of the individual risk of that event without measuring any variables at all. This would turn the whole field of risk analysis on it's head, you do realise what a game-changing piece of mathematics you've stumbled on here?

And so on. It's chasing a fantasy. It's like the idea of limits in calculus -- you'll never get there — Xtrix

So we should never start? That seems a little daft. So assessing someone's risk for lung cancer you'd just take the prevalence of lung cancer deaths and say "that's it", yes? If another doctor said "what about the variables like smoking, sex, obesity, history, age..." you'd say "that's just chasing a fantasy, you can't get a truly individualised risk so don't even bother starting"?

you’re missing something vital about how bias, expectations , frames of reference and paradigms organize our thinking. — Joshs

So help me out. What is it that I'm missing.

That’s not what Kuhn said at all. You’re confusing him with Popper, whose approach is much more consonant with yours than Kuhn’s is. — Joshs

This is why this place fascinates me so much.

I've been in psychology for over 30 years, my views have changed a little over that time (rejecting behaviourism being the most significant) but generally I've been consistent enough that if people I know were to read anything of mine, they'd be fairly unsurprised by it's leanings. I don't seem to have trouble, out in the real world, I don't find even my worst critics have so totally misinterpreted the things I say as to make them appear almost opposite on any given issues. And then there's here... Do I write differently, I wonder, the brevity of the medium? Or perhaps I've always written so poorly but having my name on top of a paper, people know what to expect and interpret my nebulous and inaccurate writing accordingly? Who knows.

Anyway, it's been a pleasure, as always, to write something I thought fairly clearly expressed one thing, only to have it presented as almost the complete opposite by your good offices. It makes, at least for an element of genuine surprise in what can from others be fairly predictable responses. It does also make it quite difficult to actually get to grips with a topic though...

"Anyone's numbers"? What would that look like, exactly? Give me an example. — Xtrix

The RR for lung cancer and smoking is 6.99 for men and 5.09 for women.

If you play roulette, does the fact that the ball lands on black a little less than 50% of the time pertain to you when you make a bet? — Xtrix

Yes.

Or is there a more personalized number that you're looking for? — Xtrix

No. To my knowledge none of the variables determining the fall of a roulette ball pertain to the individual betting. The game's designed that way.

Saying "But I'm special" doesn't exempt you from the laws of probability, I'm sorry to say. — Xtrix

What have the laws of probability got to do with it. I'm talking about heterogeneity in the probabilities themselves, not the laws governing them.

what you're arguing about, mainly, is (a) -- and so I gave you (or Baker, I don't remember -- but you came into the conversation at that point) the statistics. — Xtrix

I've not once suggested the vaccine is 'dangerous'.

why? Because you're "above average." Can you see the mistake in this? — Xtrix

No. That's why I'm asking you to explain. Are you suggesting that nobody is above average (or below it)? Otherwise I can't see why you'd find such a claim so obviously erroneous.

You can choose a parameter: the specific airline through time. How much time? A decade? The last year?

You can choose by country, and compare countries.

Yes, that's possible. What's the point? That we should do the same with vaccinations as well? Sure -- and don't you think this has been done? — Xtrix

Yes, it has been done.

if what you're asking for is, "what's MY number"? I'm afraid that's not possible. Ever. — Xtrix

Yes. That's the point I'm making.

if you can't produce figures for my risk then my decision is not risk based is it? — Isaac

You understand the use of conditionals, yes.

Then you simply do not understand the difference, a failure of understanding having nothing to do with any current or any past issue. Ask your experts not what the vaccine is, but whether taking it is better than not taking it, both in terms of individual and family well-being, and the well-being of the larger community. And the consensus becomes, yes, it is better to take it. — tim wood

Consensus was not the claim. Certainty was.

So demonstrate the necessary link between consensus and certainty.

Start by listing the factors that make a theory more certain.

Then show that theories which benefit from consensus necessarily (or even mostly) have greater values in these variables than theories which do not.

That would support your argument. Anything less is just assertion.

Certainty. And in each its own sense, but still certainty. Your mother loves you. Your girlfriend loves you. Both certain. But the same kind of certainty? Are you safe in a sinkable boat, as opposed to being in the sea? Yes. Are you safe in an unsinkable boat as opposed to being in the sea? Yes. Both the same, at the same time both different. And so forth. Work out the rest for yourself. — tim wood

You're associating the Covid vaccine response to things like 2+2=4, wearing a bulletproof vest, and (in other places) the earth being flat, and other such clearly true matters. But these matters differ from the case of Covid vaccinations in one key way (that way being crucial to their veracity). No-one disagrees with them. Not one professor of geology will claim the earth is flat, not one battle-medic will claim bullet-proof vests are worse than nothing, not one mathematician will claim 2+2=4...not a single one.

There are dozens of properly qualified experts, professors in relevant fields employed at bone fide universities who disagree with the Covid response to various extents. I don't see how you can claim certainty (rhetorical or otherwise) when there's disagreement among the experts on the matter.

How would science progress if the theory of only a few experts were to be treated always as a certain falsity?

The similarity between 2=2+4 and Covid vaccination was the question. The properties they share. We could do Bullet-proof vests in the case of being shot at if you like. Find me an professor in gunshot wounds at a bone fide university who claims that you'd be better off without the vest.

To repeat, I'm asking you what properties these matters share such that they can both (all) be referred to by the same term in some sense.

There is too much at stake, politically. — Michael Zwingli

Explain? Say, the FDA claim the vaccine is 95% effective,but it turns out they were overplaying their hand and it's only 60% effective, less after six months. What political fallout are you anticipating? Won't the FDA just blame the rush, the emergency, the limited data they had to work with... I'm not following what it is you think would be at stake.

We have an organisation with a proven track record of approving drugs which later turn out to be largely ineffective or whose effectiveness is found to be overstated, an organisation heavily lobbied by the industries who benefit from these approvals, whose data is provided by the organisations who benefit from these approvals and which has a demonstrable revolving door of cushy consultancy jobs as reward for good behaviour. They're tasked with testing the effectiveness of a vaccine, but unlike their usual vaccines, this one is set to be a veritable gold mine for the pharmaceuticals and they have a whole slew of excuses already lined up for why they fluffed the approval. You're suggesting that in those circumstances it's less likely that they'd give an overly confident approval?

You apparently have no idea what the word means or signifies, nor when nor how. Get a life; learn something. — tim wood

Educate me then. What is it that links 2=2+4 and the issues around the Covid vaccination. What properties do they share such that both are apodictic?

I think given the high-profile nature of the COVID epidemic, most if not all of that "hanky-panky" was surely forestalled. — Michael Zwingli

Why would you think that? What would be the comeback on the FDA if the vaccine was not as effective as they claimed? They're hardly going to be taken out and shot are they? The main aim is the revolving door into a well-paid consultancy job with one of the major pharmaceuticals. So long as that's not at risk, I don't see why they'd take any more care here.

Or, if you'd prefer, there's the FDA approval of the HPV vaccine where...

a recent review showed that design problems in the HPV vaccine trials, most of which were led by academics but sponsored by industry, made it difficult to evaluate the extent to which the vaccine prevented cervical cancer — Rees CP, Brhlikova P, Pollock AM. Will HPV vaccination prevent cervical cancer? J R Soc Med2020

Last year the FDA said it was “committed to use an advisory committee composed of independent experts to ensure deliberations about authorisation or licensure are transparent for the public.”1 But in a statement, the FDA told The BMJ that it did not believe a meeting was necessary ahead of the expected granting of full approval.
Kim Witczak, a drug safety advocate who serves as a consumer representative on the FDA’s Psychopharmacologic Drugs Advisory Committee,4 said the decision removed an important mechanism for scrutinising the data.
Diana Zuckerman, president of the National Center for Health Research, who has also spoken at recent VRBPAC meetings, told The BMJ, “It’s obvious that the FDA has no intention of hearing anyone else’s opinion.

a general surety that the FDA would not allow vaccines onto the market which endangered people by severely lacking efficacy, — Michael Zwingli

On June 7, the FDA approved aducanumab for the treatment of Alzheimer's disease. The drug received accelerated approval because it showed it could reduce the rate of amyloid plaque on scans. What remains uncertain is whether this reduction in plaque means Alzheimer's patients live longer or better lives -- and notably, the totality of the clinical trial data do not show that. Moreover, the drug has various side effects and a whopping price tag: $56,000 a year.
In response to the FDA's approval, three members of the Peripheral and Central Nervous System Drugs Advisory Committee who opposed approval of the drug, quit the panel in protest. Aaron Kesselheim, MD, JD, MPH, a Harvard professor called the drug "problematic," and argued that there was little evidence it would help patients. Writing in The Atlantic, Nicholas Bagley, JD, and Rachel Sacks, JD, MPH, estimate that if the drug is prescribed to just one-third of eligible patients, it would cost Medicare $112 billion a year -- a massive figure that dwarfs any other medication.

You question the reality of the pandemic? You question the efficacy of the vaccine(s)? You question the general hazard to the well-being of the community and its several members that unvaccinated people represent? — tim wood

No, yes and yes. But his has nothing to do with the line of argument. This is not "write some things we think about Covid", it's a supposed to be a discussion. You know... you say something, I say something in response, you say something in response to that...have you come across that type of thing before?

You claimed that the issues around the Covid vaccination were apodictic, like 2+2=4. I said that 2+2=4 benefits from every single mathematics professor in the world agreeing with it - a crucial part of what makes it apodictic.

Since this is not the case with issues around the Covid vaccine, you seem to have redefined 'apodictic' to mean 'things I think are true'. I'm enquiring about your grounds for that redefinition.

If you'd rather not bother actually supporting the claims you make, but just vent whatever happens to occur to you, then I suggest you try Twitter.

Indeed I hold it is. There is the issue of the greater good against a pandemic. No question about either - no reasonable question, at any rate. The pandemic is real, the benefits of the vaccine are demonstrated. And the validity of general vaccination as a strategy against disease well-established. The argument is over, and was over when it began. All that remains is the whining, and the news routinely reports that ceases when the whiner or his get sick or die. — tim wood

I wasn't asking you to confirm your opinion. I'm not conducting a poll. This is a discussion forum, I was asking you to support it, not repeat it.

So the contingent/indeterminate v. the apodictic. 2+2=4 and that's an end of it, and somtimes the Germans are better and sometimes the Brazilians. The question here being if there is anything apodictic about Covid vaccination. And I think there is. — tim wood

Then find me the fully qualified mathematician employed as a professor in mathematics at a bone fide university who claims that 2+2 does not equal four. If you can do that, you can establish that there can be apodictic claims which are nonetheless opposed by such experts in their field. Otherwise, I think the onus is on you to demonstrate that despite this quite relevant and substantial difference, the issue of Covid vaccination is nonetheless apodictic.

Because your doctor could give a more customized treatment plan and "risk profile" for you, given that he or she presumably has more information about you. — Xtrix

Did you even bother to read the list of risks I presaged the enquiry with? Only around half of them were of a medical nature. So again, why would a doctor know anything about them?

How would I know what your numbers are? I know nothing about you. — Xtrix

I'm using me as an example. The point is you don't know anyone's numbers You only know the prevalence.

For someone who claims to care about statistics, this is pretty embarrassing. — Xtrix

Well, that would be disappointing for sure. So where have I gone wrong? Talk me through the correct process for risk analysis.

The absurdity of your argument can be demonstrated fairly easily by switching from this particular vaccine to the measles or smallpox or polio vaccines. Much easier to see the silliness there. — Xtrix

OK, go for it then.

Because if you can't produce figures for my risk then my decision is not risk based is it? — Isaac


Which is like saying we cannot calculate the risk of anything, if it isn't individualized to our specific situation. Which is nonsense. — Xtrix

Explain. In my experience this is exactly the case and always has been, so if you've been taught differently. Where exactly did you learn your statistics from?

If one wants to understand the risks involved in flying in an airplane, one can look up crash statistics. If one wants to understand the risks of a vaccine, one can look up the potential negative effects of the vaccine. — Xtrix

Again, you'll have to walk me through the maths here because it's clearly so advanced that I haven't come across it yet. How do we go from the prevalence of plane crash deaths or the prevalence of adverse responses to vaccination to a risk profile for some individual without any variables?

In this case, the COVID vaccines are extremely safe. It far outweighs the risks of being infected with COVID, and it helps stop the spread of COVID. — Xtrix

So you keep saying, yet I'm still not seeing how this is a response to any individual deciding not to take the vaccine.

We have an activity: x. The risk of dying or being harmed by x is shown to be extremely low statistically -- say, 1 in 10 million. You can further crunch the numbers if you'd like, but this is enough to tell anyone what they need to know about x. — Xtrix

This seems to be a repeat of the claim above. Talk me through the maths. How do you get from this prevalence figure to a relative risk?

First of all, "average" in terms of what? By what metric? — Xtrix

Average in terms of the mean. The mean probability from a probability distribution.

These numbers have nothing to do with "average" -- not the ones I'm talking about, regarding death from the vaccination. — Xtrix

So you're saying the risk figures for death from vaccination are not distributed about a mean? They're what? Absolute figures? Have no distribution at all? I don't understand how they could not have a distribution.

The risk of taking the vaccine can be calculated. Just as your risk of crashing in an airplane can be calculated as well. — Xtrix

Again, show me how.

How do we know the risk? Because we can calculate the number of flights and the number of crashes. — Xtrix

...which gives you the prevalence. We'd normally then run tests to discover variables and analyse the effect of each to come up with a risk profile for each multivariate, but you're saying we can do without all that somehow, but you're stopping short of explaining this new maths.

This is how we approach anything. — Xtrix

As I say, this is news to me. It's not how I've ever approached anything. Perhaps you could give me an example of a relative risk being calculated using prevalence of outcome alone

To say "Well the odds of a plane crashing only pertains to the AVERAGE person, after all, and I'm not average" is just an absurdity. — Xtrix

So if I don't fly my risk of dying in a plane crash is still the prevalence of plane crash deaths? It's an 'absurdity' to suggest that my not flying is a factor affecting my risk of dying in a plane crash even though it doesn't affect the prevalence of plane crash deaths? Is this more of this modern new method of statistical analysis that I've missed?