I didn't argue people aren't as smart as me. I'm saying people shouldn't be arguing about things they don't have an education in. To assume everyone here has a background in science is ludicrous. How are people supposed to know that things are safe if they don't know how the experiments are done or why it is done that way? Because they're told that it is safe? Anti-vaxxers are told that it is unsafe. Both people know just as much as the other they just believe different authorities. Yes people should listen to the scientists but unless they themselves have a background in science how should they know that the scientists should be trusted or which ones to trust? Dr Andrew Wakefield started the whole anti-vaxx thing and he himself was a scientists, a fraudulent scientists but he had a PHD.
Here is how you come to a conclusion - following logic and scientific proof.
First - the person you named is a proven fraundster, who has lost the approbation to perform as a medical doctor in his country.
https://en.wikipedia.org/wiki/Andrew_Wakefield
https://briandeer.com/mmr/lancet-summary.htm
Why - and how do you prove it.
He had undisclosed financial incentives to promote a scare story - before he first did any research.
He talked about the syndrom he'd discover - before he'd done the research to discover the syndrom.
The evidence he presented was a small scale study (15 people picked for their symptoms) after which he started to go on a media circuit, which is also highly unusual
The end result was them getting public research funds in the millions and distributing them at their own disgression, until the (high incentive) of fraud was found out. That research (the one where you look at this at scale) never got finished.
--
Also - he aimed to 'prove' the effect of one combination vaccine - not vaccines in general, so whenever you make the 'ideological' jump to 'all vaccines' - its your fault. Not what he was saying.
--
Why did it work as a media play? You had a smart, eloquent middle class physician - who liked (partly because of an undisclosed financial incentive) to drum up media attention around his person. A FUD based message. And a general public, who in addition to trying to simplify things down to a level where people can easily digest things, were also confronted with the vaccine under contention being a combination vaccine against three illnesses -- which gets condensed down to 'all vaccines dangerous' because thats how 'the public mind' works - under uncertainty, aiming for complexity reduction.
Nothing unusual there, even expected.
--
"But hes also a scientist!"
Crowds look up to leadership figures, in periods of distress, to help them make up their minds. People in white coats are prime level 'influencer' material in that sense, especially if they are good looking and can talk.
Science doesnt make that shortcut. Science essentially is a bunch of techniques, that are employed, so you arrive at conclusions independent of the person. So a bunch of techniques, aimed at removing bias from the occasion.
One of those techniques is standardized statistical testing -- where the chance of something being a statistical fluke becomes smaller, and smaller - the more people you are testing. If your initial study only relies on 15 patients, which you handpicked -- its has no statistical validity. Meaning - it can be part of the beginning of looking at a phenomenon, but it cant be statistical proof. And statistical proof is what would actually change practices. And would be needed to come to a conclusion in a case like this.
But why trust statistics -- ? Essentially, because in the medical space they are usually good.
Why? Because the way to ask for/mark down a certain illness is well standardized (Hospitals participating in studies, have forms, that have to be written in a certain way to prevent bias). To get large scale studies, they are spread across different people that are in control of getting the data, that are not affiliated with the study, the data is then collected and whatever massaging you might be doing on the data front, will be put up against 'sanity checks', which makes it hard to falsify the results of your study to gain a certain result - because doing so, would lead to statistical abnormalities, that usually can be caught at large scale. In addition to that any of your findings, and the data you provide will go through a 'jury of your peers', who will risk their reputation by greenlighting your study results.
So essentially, if you are not running the studies yourself, its hard to falsify results. Which is the entire reason for the method.
--
"But science isnt always right.."
Yes, and here are the ways it fails most often:
Observation bias: You seeing something you'd expect to see. Thats countered by you not running the study.
Statistical fluke: Thats countered by making the studies big. (And applying mathematical criteria for what is 'significant')
Results can not be reproduced: Thats countered by you having to write down your process in a way that other people can duplicate the research - then they look, if they can replicate your results. At this point you have nothing to do with that process anymore.
People tried to reproduce his results, they never could.
Confirmation bias: This basically matters a bunch in the design stage of a study, so what your colleagues in a field think is 'state of the art' (scientific canon), will influence how you look at things, and induce implicit biases. (You dont look at all the alternatives, or...) Which is tried to be offset by the method how you formulate your design questions, but hardly ever is -- in the end, most of science has come to the conclusion that science needs to be 'falsification based' (deductive logic, not inductive logic), so you take your interest, you operationalize your research question, and then you try falsify it -- using criteria that removes sophistry (= what people might do that are good at talking), only if you cant falsify something, it is presumed 'true' in the end. And that 'truth' is not universal, but only holds as long as someone else cant disprove it. Thats what students and your pears are incentiviced to do btw - to get scientific renown. In the end this doesnt always work - but hey, you are trying..
But luckily for our case - confirmation bias on part of the entire scientific field was not what lead the study in conception - so thats not a likely issue where stuff 'did go wrong'.
Predictions: Thats an entirely different field, because you arent going off data, but the presumption that certain trends will develop the same in the future. Essentially predictions are hard.
But luckily for our case - studies were data driven (past occurences), and deductive, so thats not a likely issue where stuff 'did go wrong'.
The last two are also why you are looking for 'scientific consensus' essentially meaning "most of my colleagues think the same". This is not 'hard data' but used in cases, where you dont have that (predictions, ...).
--
So in the end this is the logic you'd use to come to a decision on weither you should believe in a persons position or not.
You dont just read 'they have a white coat and a title' and call it a day ("I'm listening to science, yay!"). Except that the mob always does.
Because of complexity reduction. But thats well known, and thats why there are fallbacks in the scientific process to objectify, remove biases, separate questionaires from researchers, use big numbers to get higher statistical certainty... and so on and so forth.
And in the case you are promoting you have a guy, with 15 test subjects and a media blizz campaign, who was bought by an industry lawyer (lobbyist) to produce a certain result, and then got research funds in the millions, but never produced the 'reliable' results.
Whats scientifically reliable? Something that has reliability, reproducibility and validity.
reliability: Are the results statistically viable and do they lead to the causal result you are proposing, in the opinions of your peers (other scientists).
reproducibility: Can the results be independently reproduced (following the same method)
validity: Does it measure, what it aims to measure,
Thats science.
Science is a process. Not a charged up half god in white, you should believe in, because - look at his coat.
If you find incongruences in that process, in any case - good on you, you are doing it right, you are trying to falsify a proposal.
But also remember, sophistry is out, so you cant win with verbiage, or making everyone worried. You have to win on facts.
edit: Oh, and you also _have_ to disclose affiliations (financial incetiives) which he also didnt do. Its not easy getting your approbation taken away..
@
Xdqwerty:
