Maybe that's the case in your area of research. In mine (math, physics) it definitely isn't. So I would be a bit more careful about the wording here. ("80% of science" – what science?)

P < 0.05 is outdated at this point, for anything truly ground breaking p < 0.005 or < 0.0005 is probably a better choice, and even then I would ask "Where did you get your dataset from and did you combine (!!!) datasets from multiple orgs."

The methodology is deeply flawed, given that you haven't stopped accidental p-hacking (publication bias) and deliberate p-hacking (researcher data mining, e.g adding endpoints after looking at results), which compounds to create fake results with astronomically tiny p-values.

You can only trust single, extremely large, canonical RCTs which were announced in advance, and in which you are confident there is no survivorship bias in terms of the possibility that this RCT would have been cancelled had the results been thought to be negative halfway through.

Epidemiology (victim of researcher p-hacking and impossible to deal with confounders) or meta-analysis of RCTs or single small RCTs or RCTs that weren't announced in advance (victim of publication bias) should be taken with a grain of salt. If you accept conclusions drawn from these things at face value, be prepared to accept anything, because the methodology you've accepted is proven to be easily capable of demonstrating any fake phenomenon as true.

There are so many ways that are studies can be flawed either accidentally or purposefully. I truly assume most studies are not purposefully fraudulent - people, by and large, are honest... but I do believe there are enough problems with our current methods that most studies are not truly accurate.

Having a publish clinical trial regimen - created before your study starts - helps with a lot of this. It answers how you segment patients, match patients, handle patient dropout, and specifies what you are trying to compare for outcomes.

Is it the end-all be-all? obviously not. I don't know what the true answer is.

Its actually my job.

What are you designing new experiments for? Are you taking results in one cell like and condition and trying to transfer them to new cell lines and conditions?

Are you trying to reproduce the same data in the same cel lines/organisms?

There's such a huge wide array of what your could be taking about, but based on my experience in life sciences what you say does not seem the least bit realistic, in my first interpretation of what you are saying.

Also its worth noting that I am not claiming my experience is the end-all be-all. I am stating that, from my experience, I have incredible distrust for many studies that are published with 'amazing' results until peer reviewed preferably on disparate datasets.

My experience is based around outcome based studies of the effect of drugs/treatment/regimens in oncology and oncology adjacent fields. This includes drugs treated alongside traditional cancer regimens to assist with managing adverse events and toxicities.

Other fields may not have this reproducibility problem. Mine does. Even if the study design if perfect, and I can't imagine most are, the data itself can be questionable.

Consider - what dataset would you use to identify if patients taking keytruda had a higher incidence of high blood pressure?

You can use data from an EHR, licensed for deidentified studies, but EHR data is a burnt down trailer park of questionableness and its use in studies has been laughed at in many conferences.

You can use data from individual enrolled patients (for a clinical study) but then the cost is extremely high vs a non interventional observational study using other data methods. The value of the data is likely to be higher, but since it costs more to collect maybe you are only in a few regions that may have a higher prevalence or incidence of this anyway. Troublesome.

What about insurance data? You can get it cheaply, if you have high blood pressure GOOD doctors are likely to medicate you with a drug meant to treat it, and you can get it across the country. Seems good right? And it is, as you can generally draw an implication of high-blood-pressure->treatment-with-drug-x. So for a yes/no study it can help, but what if the base condition causes high blood pressure and we want to tell if the drug causes a HIGHER amount of high blood pressure than others. Insurance data by itself may not be enough to tell this data.

So what do you do? You are stuck with no great answers.... and this is assuming your study design is perfect.

So you buy multiple datasets in some third party health marketplace, and someone gets the great idea to combine the datasets to increase the n value. Well, too bad those datasets have a high overlap. So you have attributed a higher power to the study than is relevent.

I hope this explains more about the concerns I have. Though, I suppose, it may mean that this account is now dead. I will have to think further. Anyway, hope you have a great day.

You may disagree with the experiences I have had as it may not be in alignment with your thoughts and ideals, and it still doesnt make you a bad person. It doesn't make me a bad person either.

Even then, I would worry that the results may be caused by some confounder in the original dataset/design instead of something you can trust.

One factor contributing to this. In natural sciences, you take other people's papers as truth and build on that. In theoretical physics on the other hand the _first step_ is you reproduce their results.

In theoretical physics, one of a researcher's main concern is to not to make wrong claims. Granted this risk aversion has its own downsides, but the upside is that he is extremely careful on what he takes to be true. So it's not true that not reproducing the research you rely on has limited benefit. It has the huge benefit that the researcher convinces himself he's not introducing wrong premises. Research is already difficult enough without making mistakes in this silly way.

If your research is mathematical or involves a lot of engineering, you are building on earlier results. In many cases, your own results will depend on the correctness of earlier results in a measurable way. You end up replicating others' research without even trying.

Empirical research is harder. You cite earlier results, but there is no clear connection between their correctness and your results. Especially if effect size is small. Earlier research has more effect on the framework you use to interpret your results than on the results.

Academic researchers rarely replicate others' results, because it's expensive and not particularly interesting. People typically come to the academia because they want to work on something they personally find interesting. If you want to have experienced scientists working on something administrators tell them to do, you better pay industry-level salaries.

As for physics, well it depends. Laboratory physics has produced the finest predictions in any science by several orders of magnitude. Quantum Electrodynamics is freakishly accurate. On the other hand it’s hard for me to see cosmology, to gently pick on an easy target, as more than extremely well researched and plausible science fiction. Then you have particle physics which has excellent laboratory equipment and produced fantastic results, but which has, in the opinion of at least one elite particle physicist personally known to me, perhaps painted itself into a corner. The Standard Model is good enough for government work, but nobody believes it’s the best possible theory.

For physics, it depends.. is it just "applied math" (so, verified easily), is it a CERN-type (LHC,...) experiment (hard to replicate, unless well.. you work at CERN), where many many people process the data, or is it something that is done only in your "lab", and hard for others to replicate.

On the other hand, finding thousands of patients and running a study is practically always hard and expensive.

But what this logic fails to consider is that people who graduate from Harvard aren’t successful simply because they went to Harvard. Their success comes from many attributes like their intelligence, etc that advanced courses are designed to separate the cream.

So then they organize and legitimize their power (removing merit and replacing with lotto or affirmation quotas) by claiming the existing system is racist. When you ask for specific examples they respond that it’s “systemic” and although no one can detect it, it’s imbued in everything. The solution is “anti-racism” which means to make up for past discrimination by systematizing present and future discrimination. This is why your HR department probably has a commissar on it now. They might call it DEI Officer or sone other bullshit job title.

This is what social sciences have contributed the last 40 years.

"This is what social sciences have contributed the last 40 years." This statement implies that's the entirety of what they have contributed which is false.

Anyways - you seem to like to take this line all the time - "where's the evidence". It's everywhere. It isn't my job to keep you informed of the world you occupy. Either willfully or not, your inability to keep up on developments isn't an excise to demand "sources" when you have access to the same search engines as everyone else. This information isn't difficult to find.

Yes, some people use "where's the evidence" as a conversational gambit to try to shut down discussion they don't like. (And if you provide evidence, they may say "that's only one source, got any others?") And if they're being dishonest in asking, there's no point supplying the evidence they request; it is useless to try to have a conversation with those who will not listen.

On the other hand... when you make a claim, the burden of evidence is actually on you, not the other person. And if you say "you have access to the same search engines as everyone else", well, that's true. On the other hand, one person writes a post, and ten people read it, or a hundred people, or a thousand. Making the thousand do the searching, instead of having the one writer do it, is really inefficient.

This leaves you at "do the work of providing the evidence, but don't feed the dishonest trolls", which is... well, at best it's not very actionable advice.

I told you I was torn...

I mean, affirmative action is literally this in practice.

By proposing a math curriculum that requires teaching all students the same material, regardless of their ability, with the aim of increasing social equality.

I'm OK with that aim; but I know from my own experience that trying to teach calculus to someone that's not ready for it isn't just a waste of effort, it's disastrously counter-productive (I totally fell out of love with maths when I was taught integration, failed to "get" it, and my well-regarded teacher didn't get why I didn't get it).

My understanding is that nowadays in UK state schools, maths is largely student-paced, using worksheets; they've given up on trying to get a whole class of students to all understand the same stuff. That's partly because a set of worksheets is much easier to come by than a good maths teacher, of course.

I'm not a maths teacher, and I don't know enough about the California curriculum arguments to have a view.

But after becoming a scientist, coming across so many fraudulent papers, so much non-reproducible and poorly done research. And seeing how it's affected my own, the thing that's dearest to me, having to build on top of those results and work in that global environment. It's been heart breaking, I feel no love for science anymore.

I spend most of my career reanalyzing others' data and combining it together into larger datasets, in molecular biology and genomics. The only time I encountered mistakes it was from my own labeling errors or bugs, pre-publication. And in pre-publications datasets I would sometimes detect accidental swaps on the labels of samples as part of QC checks.

“Sokal Squared” is a great example of the problems in the field.

https://en.wikipedia.org/wiki/Grievance_studies_affair

Regarding the reproducibility crisis:

https://en.wikipedia.org/wiki/Replication_crisis

As the saying goes, science advances one funeral at a time, but it does advance.

It seems overall you can still have an optimistic point of view of science while accepting it does not work as well as it could.

It's a race to the bottom, and how can we ask that people compromise the quality of their work to compete when the only motivation for doing this work is the love of the craft. It's certainly not the money, or the environment, or the work-life balance, or the prestige.

When in the trenches of science this is literally your job. What seems like the likely hypothesis, what model that explains the data is good or bad.

Papers are not textbooks. They are the boiling cauldron from with some bits eventually emerged as fully cooked facts.

The only way that I can square others' experience of science with my own is if they take the Discussion sections, which are free-form extrapolation about future directions, and treat them as if they were asserted as truth.

I'm talking about malicious, fraudulent results. Made up numbers, code obfuscated and manipulated to do things different from what's being claimed. I resent the implication that my issues stem from a naive, idealistic reading of the discussion section rather than a thorough examination of the methods.

Sorting the good from the bad is one thing, creating and evaluating models, good models or bad models is one thing. Having to compete AND CITE fraudulent work, lies, imaginary models to be able to participate in the system is not "literally" science. And it's not the job any self-respecting scientist should want to do.

The more money is involved, the more fraud to expect. This should not surprise: fraud goes where the money is. And where there is money, the stakes are higher.

But I have seen reprehensible behavior even in opponents of the Younger Dryas Impact Hypothesis, where practically no money seemed to be at stake.

To that end, does anyone know of any list of techniques for spotting or identifying fraud in scientific works? This is a subject that I wish somebody would write a book on, so I am curious as to what techniques people use for this purpose.

But: science isn't really self correcting. Someone has to step up and fight to correct it, every single time. Spend some time learning about this problem - as I have - and you will find the overriding attitude is one of despair. Science isn't self correcting, it's arguably self corrupting:

1. There's no incentive to pick fights with colleagues so it almost never happens

2. Even when someone does pick that fight the institutions go to ground and defend their people, so there's no outcome.

3. The first response of journals and universities on being informed of fraud is to turn around and tell the fraudster everything, so there's no way to keep fraud detection techniques secret.

4. And usually after that they ask the fraudster to submit a "correction" (i.e. higher quality fake). The idea that you should maybe NOT let a fraudster have a second try once caught, does not seem to occur to the brightest of sparks that run our scientific institutions. There are actually cases where this has happened and then the original complainants spotted that the newly submitted correction was also fraudulent.

How do these papers get spotted? Spend time on PubPeer. It's a site where people compare notes on dodgy papers and how they're being detected. Also read the blogs of people like Elizabeth Bik, Smut Clyde, read the old blog posts by Joe Hilgard when he was still in academia, follow https://twitter.com/steamtraen

tl;dr There's a range of techniques used for different fields, often by looking for re-used images or data across papers that shouldn't be re-using them, or by spotting internal inconsistencies in reported data tables.

Do all of them do this?

There appear to be no limits to how absurd this phenomenon can get. Here's an example:

https://pubpeer.com/publications/7611C2EEE5789028895D8BD02A1...

There is no question that a very significant portion is wrong and some of it is fraud, but I feel like this is the wrong summary takeaway. Science isn’t the reason that science is messed up, people are the reason. All fields of human endeavor suffer from the same problems due to emotional and political and selfish people. It’s more like, welcome to humanity. Science is actually the best thing we’ve got, there is no alternative that has less BS and more truth. The 10% or so of science that’s right has transformed the earth in the last century.

I worry about framing this the right way, about the subtleties of how you say it, because there is currently a war being waged on public trust in science, and to some degree that anti-science war is being won. It’s potentially damaging to say “most of science is wrong” and just stop there. That’s a misleading framing in my opinion. In order to fix the funding problems, society as a whole needs to have trust in science, to believe that the majority of people doing science are politically impartial and also not wasting money or lining their own pockets, to believe that scientific progress is human progress.

It’s important to note that the incentive problems you cite mostly aren’t caused my any malicious intent. Disagreeing with someone else’s research, in my experience, isn’t often done with the primary goal of holding back good research, it’s done because the researchers actually disagree on the science, and the reviewer actually believes the proposed paper isn’t complete or correct or up to publication standards. Moreover, for science it’s very important for researchers to be critical of each other. That is part of why we need more replication study.

A lot of things look like science and use the word “science” in them but don’t use the process of science to make their claims to truth. This is useful because how can you argue with “the science”?

Yeah, totally agreed. It doesn’t even make sense to suggest that testing to check whether things work or not is the wrong process. The scientific method is tautologically true, right? This is one of the reasons I cringe at the yard signs in my neighborhood that declare “science is real”, as if it needed an affirmation. Somehow that seems to give more credibility to the idea that science might not be real, whatever that means. Of course science is real. We don’t have modern houses or cars or computers without, sillies.

Trying to manipulate people like this is guaranteed to backfire long term. People will realize that it's being done and trust things coming from the world of science even less. Instead we need to acknowledge that there are real problems in how we practice and communicate about science and take visible steps to fix them.

I agree completely we should fix the problems, and I have no problem openly discussing what those problems are. In order to do that there needs to be hope that fixing the problems is a viable and likely-to-succeed activity. Summarizing all of science activity as broken is neither accurate nor helpful in terms of fixing the problems, right? That really is a framing problem because it is not broadly true, the parent poster implied that the practice of science is the problem, when it isn’t the problem. The problem is that people are involved, and science is actually one of the least problematic things we do. It’s incorrect to call out science as broken without comparing it to all other fields.

If everyone is convinced that science is a complete and total waste, and people are opposed to spending tax money to fund it, we will not be able to fix the existing problems. If we believe something about science specifically is broken, and not with the rest of the world, then we will come to the wrong conclusion about what is broken and be unable to fix the existing problems.

You mustn't forget that universities are only one player of many in the science system. And the main task of some universities rather is education and not research.

There is a lot of funding going to universities, and a lot going to specific projects. I think maybe the main model for research funding generally is that funding doesn’t just appear, people have to go ask for it in the form of a grant proposal. Those grants typically once granted go 40% to the university anyway. Universities, for their part, have been absorbing money for larger and more expensive administrations for the last 30-40 years, and it’s out of hand. Most people I know practicing science feel the opposite of what you said - that less funding should go to the university and more directly toward funding research.

Science is losing the battle for public trust because it wants to simultaneously be an infallible source of truth and this messy, chaotic discipline where we tumble towards an approximate answer. It gets defined as a one or the other when it's convenient.

In the first breath: Oh, X% of all published papers are wrong? No big deal, that's just how science works. Can we have another 100 billion of taxpayer dollars please?

In the second breath: The Science Says vaccines are safe and effective. Take it or get fired.

The US currently somewhat operates on the principle that companies are allowed to make and enforce their own rules, as long as they’re legal. And there’s a long list of things you must do if you don’t want to get fired, including work forty hours a week, and not be a jerk to your co-workers. Do you think companies should not be allowed to fire people who choose to do things that can hurt the company’s bottom line? Do you want the government to monitor businesses more than it does today?

Science funding is complicated and political, but the high level summary of the situation is that the public funds science right now because that’s what the public wants, because a good chunk of society understands that doing science has proven to be a great investment. It would be a bummer if the public decided not to fund science or education, that sounds like the fastest way for the US to become irrelevant globally.

Anyway, what is the alternative to doing science? Do you like your computer/car/cell phone? Do you want to see technological progress stop? Can you name a better approach to seeking truth than the scientific method? What has ever proven to be more effective than science?

Even $5 to someone with a long history of finding scientific fraud puts you on the right side of history: https://www.patreon.com/elisabethbik

I’ve been donating for years and I’ve never been more proud of that decision.

That way the only possible competition will be number of citations. The pressure will be for quality, not quantity.

Well, popularity, anyway. While popularity is sometimes a useful proxy for quality, that's not always the case.

Performance Metrics always result in people gaming the system, and impact scores have quickly become unreliable.

The point of citations isn’t simply an index of prior research it’s there to inform readers of the writers context.

Research should be put into the proper context in the field, not based on what the writer personally looked at. If a researcher's context is myopic enough not to include relevant prior work known or done by reviewers, then the research itself is of questionable value. If someone submits work that purports to be novel, yet they haven't done a proper literature review to include relevant studies, I'd say that is itself deceptive and more actively harmful to the field as a whole.

The same is true to a lesser extent for any research. Now if the field has discovered some flaw in what was done then things go well beyond the simple need for a citation.

And this doesn't even touch upon the fact that research that's going to take 5 years is going to be well-funded, and you'll have to write interim reports over that period. When you get 5 years of funding, you don't get that all at once. During that time, you'll have to answer for advances in the field and justify why the research is still worth doing.

As to other field moving on, it can be a reason to reject the paper in it’s entirety but has zero impact on the results which is the only thing that actually matters. Papers aren’t textbooks, the goal is to communicate what was done and what happened not inform the reader of some wider context.

In the end if I am reading 30 papers on some topic I really want them to be as short and clear as possible. And for topics I keep up with I sure don’t need this fluff.

And a literature review is part of what was done, always. If what you said were true, there would be no point in a literature review at all. Instead, every paper includes one because researchers understand it's an intrinsic part of research. That's what makes it research instead of just search: research is a systematic process that involves, in every definition of the process I've ever come across, a literature review. I challenge you to find an example of peer reviewed research that doesn't contain one.

https://cdn2.hubspot.net/hubfs/232514/Einstein%20E=mc2%20(pp...

But, I don’t disagree that someone should keep up with the literature. Including it as part of a paper is what I disagree with.

A direct search on the CDC 6600 yielded 27^5 + 84^5 + 110^5 + 133^5 = 144^5

as the smallest instance in which four fifth powers sum to a fifth power. This is a counterexample to a conjecture by Euler [1] that at least n nth powers are required to sum to an nth power, 1 > 2.

And that’s the paper. They could have gone into great detail about the program used etc, but it clearly communicates what was done and the results so why bother.

How would you go about redoing exactly what Lander and Parkin did? You can’t because they don’t really say. Isn’t this whole thread about a lack of reproducible studies resulting in fraud?

But anyway, I like what you’re doing here because you’re beginning to document why the modern peer review system was developed in the first place in the 70s. Sounds like a good topic for a research paper.

Many modern papers are of this form. If you have some specific data as recent enough to be valid I could provide one but I am not going to just pick a paper from 1990 and you say nope not recent enough.

Another is for posterity and for future generations. If I give the paper you cited to a student, they can be wowed at its brevity and impressed by its genius, but they learn nothing.

I get you’re trying to prove your point but all you’ve done is solidify my position in my mind that literature reviews are essential to good research. You’ve given me a great topic for my talk to our incoming class of Ph.D. students in a couple weeks, so thanks for that, I mean it. Cheers.

O well, there’s a reason science advances one retirement at a time.

Just got annoyed you tried to weasel out of picking a date and tried to pretend you had won the argument.

It’s probably about the worst in any field dominated by studies and statistics. Harder sciences are harder to fake as bad results can be more conclusively falsified.

It’s quite useful to listen to Buffet and Munger. They’ve accumulated lots of wisdom.

“You get what you reward for” https://youtu.be/hJYLJRr3hEY

This hour of Munger is well worth it:

https://youtu.be/4ICaAKuAudQ

Here’s the transcript:

https://fs.blog/great-talks/psychology-human-misjudgment/

I'm not sure if it is a good idea to try to optimize the scientific process for fraud resilience. In the end, we still rely on people doing the right thing most of the time.

He said something exactly the same, and his conscious wouldn't allow him to work in the field of science.

He left the field many years ago. He delivers mails now.

You’ll find similar physics research for example in nuclear power, optics, quantum computers, telecommunications, engines.. all kinds of engineering really. Chemistry is also quite relevant and there are new, stronger materials being engineered all the time based on research.

It’s definitely not all just 1900s physics driving everything, even if you say that for some reason anything researched then doesn’t fall under the 80% of science that doesn’t work (which GP didn’t).

Much of what you think of as science came from engineers.

GPS relies very little on 20th century science, beyond GR corrections.

The science behind orbital mechanics is just Newton's Laws, stuff thoroughly settled centuries ago.

But your example of GPS, and others' of "rocket science", show that you have even shakier ground for opinion, along with insufficient respect for engineering. You are not alone in that: scientists get good publicity. They even get dedicated press offices at universities.

Engineering is about making things that work. GPS is very firmly on the side of a thing that works. Likewise, rockets. People sometimes use those when doing science.

So your trotting GPS out as an example of correct science did not in any way illustrate what you imagined.

Are particle accelerators a better example for you, in that they wouldn’t actually work if 80-90% of science is wrong? Or is particle physics also actually engineering and nothing to do with science?

Anyway, my guess at this point is that we both agree on lots of the same technologies that actually work, just not on if general relativity or physics or chemistry are technically science or engineering, and therefore whether they would fall under the “90% of science doesn’t work” statement. Its hard for me to imagine engineering without a dependency on scientific knowledge, but it’s interesting that that’s a valid point of view out there.

A particle accelerator is a tool used for conducting science experiments. That they work, for that purpose, is purely a product of engineering.

At issue is not "whether science works". It is, rather, what percentage of published papers in science journals are crap, and advance the field not at all. The people in the best position to know say they are appalled at how many are.

Would they all say 80%+? Obviously not. Do any? Absolutely.

> I can say I believe 80% of science wrong AND not reproducible, 10% being an outright fraud (10% being legit).

.. which I interpreted to be a statement on "whether science works."

If we instead constrain that to 80% of science that was posted recently in journals, and mainly not in hard sciences, then I could totally get behind that. But I don't think that's what they said, and I think that's why I've been confused by this whole thread.

I don’t think it’s remotely accurate to describe GPS as “socialist”. It was a military project. There’s a long list of military projects with more funding than GPS that have been invented and implemented since then.

Starlink is mostly a marketing thing, and is mostly based on science that had been funded during the Cold War.

The years you cite are when drone tech was developed and deployed in combat, and cryptography improved. The DoD funds all kinds of research through the university system that isn't public, you may have no idea what it brought us because it's too recent. The DoD is funding all kinds of projects today, despite our capitalist tendencies, for example: https://www.defense.gov/News/Releases/Release/Article/309821...

I don't know what you mean about Starlink being marketing. They've deployed more satellites than all other satellites to date combined. You said you thought a project this size wasn't doable today, yet there it is. It seems like you're arbitrarily judging what projects you believe are worthy of consideration in order to support a preconceived notion. Why do you believe GPS involved more invention or development than Starlink, drones, cryptography, machine learning, or anything else? GPS technology was also developed before the US Navstar project began, the science already existed and it wasn't some kind of lone independent invention.

The system of which the military is a major pillar is definitely also an economic system, and the fact that a major part of that system (the military "sub-system", in this instance) was run in a way that was antithetic to the stated ideology of that "all encompassing" system as a whole ("capitalism", in this instance) was quite interesting.

I'll give you drones, even though the drones that have had most of an impact in the present war are the consumer-oriented ones, which are not directly the work of any military system (I'm talking about the small drones that help with artillery targeting). The Bayraktars were quite rapidly neutralised by the Russians once they got the hang of it, and at this point they're merely a PR thing.

Cryptography is also a result of Cold War funding, in fact it's one of the quintessential results of that war when it comes to our industry.

> Why do you believe GPS involved more invention or development than Starlink, drones, cryptography, machine learning, or anything else?

Didn't say that, quite the contrary, most of those are the result of direct and sustained Government funding via the military, i.e. what I called socialism. Again, Starlink would have remained a pipe-dream without Reagan's 1980s Star Wars Program.

Anyway, I'm happy for the current status-quo, i.e. for the best and brightest in our industry golden hand-cuffed at FAANG companies, spending their best years worrying about their comps and about KPIs and OKRs, had they been part of a Manhattan-like or Apollo-like Government-run system then things would have been much, much, much worse (in terms of peace on this planet, that is).

Then you also need a realignment of the entire academic system as well. A new professor spending 50% of their time redoing the experiments of others, especially on capital expenditures and grad student time is going to be at a severe disadvantage against others who spent 100% of their time building their own research agenda.

We'd probably need a whole new degree that's like a PhD, but whose dissertation isn't a novel extension of the field, but reproduction of other studies. Because as it is, a grad student can spend up to a decade on a Ph.D. just doing novel research. Now you want them to spend 50% of their time on reproduction? So is a Ph.D. supposed to take up to 20 years with your proposal? Or does a dissertation contain 50% less novel research?

Certainly we should have funding for reproduction studies, but it's not enough to just have a grant; you have to have a valid career path doing such work. That doesn't exist today.

I don't think that would work - those positions would go empty. People apply for grad school because they want to do original research. On the other hand, once people are already in the academic pipeline and they run into struggles advancing from postdoc to assistant prof or maintaining funding as an assistant prof, I think a lot of people would take a 50/50 grant if lets them keep one foot in the door for original research. They aren't going to turn their noses up at the only grants they are competitive for.

You do raise a good point that labs with 50/50 grants wouldn't have as good of a value proposition for prospective grad students as labs doing 100% original research. I'm not sure what the solution is there.

They would if it doesn't make them competitive when it comes time for tenure review. Reproducing research doesn't get one tenure, so accepting such grants would mean tacitly admitting you should also start looking for a new position in a couple years when you go up for review. That's why I said we need an realignment of incentives across academia in addition to these grants, which would give a career path to people. Maybe it's worth it to create positions for people who just reproduce others' research, I don't know.

Humans are not incentive-following automata, though we have incentive-following tendencies.

This is the biggest problem in my view. My work in R&D taught me that most of the time we don't produce anything. It's high risk. But it's high in rewards, often in adjacent areas not primarily the focus of the initial brief.

Surely all serious investors understand this. Research is something we do for marginal returns. It's not an "innovation factory". With things currently stacked against risk, research can only yield tepid results.

Not necessarily when the investor is an academic institution or a government.

It would appear that this isn’t really “Science” if the ideal of research is being veered away from so much.

Vested interests suffocating the process.

The official line was that it was not airborne, and that if it were, masks wouldn't help. It turned out they were relying on a definition of "airborne" that only applied to tuberculosis. It really is airborne by an actually useful definition, in a way where masks can help. (And, incidentally, where those clear plastic barriers at stores don't.)

There were and are plenty of scientists critical of the CDC. Immediately after officials lied about masks being ineffective, prominent scientists voiced harsh criticisms. They were not harangued for being anti-science or conspiracy theorists.

On the other hand, people who fundamentally did not grasp what mRNA is, or who believed that COVID caused no more deaths than a flu, or who touted "medicines" that had no demonstrated efficacy—they were deservedly criticized. Unfortunately, the criticism wasn't enough to prevent many of them from making quite a bit of money peddling their beliefs.

But in the spirit of helping, roughly 6 seconds of Googling in regards to your question turned up this https://www.healthaffairs.org/doi/10.1377/hlthaff.2021.01072

This is not the least bit true.

There was a PBS interview with one of the scientists on President Biden's Covid advisory council who spoke up about how disappointed he was with his colleagues in public health who would not speak out against the mob on the efficacy of cloth face masks to protect against an airborne virus.

https://www.pbs.org/wnet/amanpour-and-company/video/do-masks...

we need to get humble scientists: the ones which do science with the goal to find the truth but not one which just want to be right and have too much pride admitting wrong.

If this could survive for 15 years before anyone notices anything wrong then how is it not the sane response to wait for more mRNA studies before mandating it for billions of people?

There appear to be few of us who are inherently mistrustful of others; in recent times, that instinct has proven to be quite beneficial.

(If you can discuss the fine points between "lab leak theory" and "result of genetic manipulation" without mentioning any politician or anything that came out of a fb page or entertainment channel with "news" in its name that's a good discussion to have

Yes, but the problem is, that the remaining 10% were treated the same way.

(but I think, the numbers are actually more like 98% BS and 2 % legitimate, fact based doubt)

Dissenting opinions were censored by the millions across social media.

Meanwhile, anyone who felt the lab leak theory was at least worth investigating was accused of being a Russian, Trumpist, anti-science piece of shit.

Daszak's paper was obvious bullshit. Not in hindsight, not on close reading, but on immediate reading by anyone with basic experience and logic. Yet across government, media and academia it was cited as the definitive scientific position on the matter, case closed, stfu.

... So if you're going to blame people for mixing their discussion with corporate news and political stunts, then you're going to have to share that blame with all responsible parties. They've fully earned the ire and distrust which many across the political spectrum now hold them in.

And we still haven't had a proper investigation in Wuhan, there's been no accountability for Daszak's conflict of interest, there's been no one held to account for the unprecedented censorship across Twitter and FB. No corporate media have been held responsible for their bullying and their bullshit.

If you want people to have smarter discussions about this, I'd remember the above before accusing everyone of just 'getting their info from politicians and FB'.

Somehow that was anti-vaxx.

Google it man: FB and Twitter deleted MILLIONS of posts. They flagged hundreds of millions more as potentially disinformation, reducing engagement by ~90%.

The NYT said themselves that the media failed us on this - eventually, in May last year. [0] Still, they didn't acknowledge their own role, and put it in the opinion section.

And here you are, a year later, carrying water for them. You're not alone - many seem oblivious to their manipulation. It's bizarre, and quite scary.

"How easy it is to make people believe a lie, and how hard it is to undo that work again!"

[0] - https://www.nytimes.com/2021/05/31/opinion/media-lab-leak-th...

Also how do you know those posts didn't have content that violated those companies rules?

That may be your fundamental misunderstanding here.

Censoring millions of posts and drastically reducing engagement on hundreds of millions more has a very serious effect.

I'm aware, because I sought that information out - but most people I talk to still have lingering misinformation on those subjects. You yourself seemed to think there wasn't any such censorship, before the goalposts were moved. I'm reminded of the narcissist's prayer.

> how do you know those posts didn't have content that violated those companies rules?

Maybe many did violate the companies rules. But the rules were wrong-headed. Legitimate and necessary debate was stifled and perverted at a global scale, and up until half an hour ago you hadn't even heard of it.