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How Common Is Scientific Misconduct?
Hugh Pickens writes "The image of scientists as objective seekers of truth is periodically jeopardized by the discovery of a major scientific fraud. Recent scandals like Hwang Woo-Suk's fake stem-cell lines or Jan Hendrik Schön's duplicated graphs showed how easy it can be for a scientist to publish fabricated data in the most prestigious journals. Daniele Fanelli has an interesting paper on PLoS ONE where she performs a meta-analysis synthesizing previous surveys to determine the frequency with which scientists fabricate and falsify data, or commit other forms of scientific misconduct. A pooled, weighted average of 1.97% of scientists admitted to having fabricated, falsified or modified data or results at least once — a serious form of misconduct by any standard — and up to 33.7% admitted other questionable research practices. In surveys asking about the behavior of colleagues, admission rates were 14.12% for falsification, and up to 72% for other questionable research practices. Misconduct was reported more frequently by medical/pharmacological researchers than others. 'Considering that these surveys ask sensitive questions and have other limitations, it appears likely that this is a conservative estimate of the true prevalence of scientific misconduct,' writes Fanelli. 'It is likely that, if on average 2% of scientists admit to have falsified research at least once and up to 34% admit other questionable research practices, the actual frequencies of misconduct could be higher than this.'"
Scientists are humans too and a job won't change some humans from being cheats.
Of all scientific articles I have read there are no apparent copy-cat actions I could even think of. However, pure ignorance and clumsiness are very very frequent. I can live with typos and errors, if they don't change the big picture.
However, cheating is another thing. I am aware of people presenting facts technically correct, but in deceitful manners which give the impression the background research is well done. However, scrutinze what was actually done, it falls apart. Yet, what can you do about that. If do you call attention to it, you risk becomining a whiner. And, who wants to be that?
It is often cited that crappy, broken or incomplete code is often shoved out the door by business in order to meet deadlines. Quality or even truth are sacrificed for business reasons.
Why would R&D be any different? Big business often exhibit quota and other incentives for patent filing and the like. Outside funding sources pressure even pure research activities so that they can get their hands on new technology or even for silly things like a name being recorded as "first to" do something.
I am actually a bit surprised that the numbers aren't a bit higher.
If we accept that scientists are human like anyone else, we accept that scientists, like others, will make mistakes that get bigger and go more wrong than they anticipated. Some may intentionally commit fraud.
How common is scientific misconduct relative to other types of misconduct seems a more relevant question.
Also: What can we do to decrease it and how can we lessen its impact.
But if there are so many examples of scientists providing fake data how do i know the results of the survey in the FA are correct?
corrupt police officer ? corrupt politician ? cooking book finance people ? manager breaking some rules or "making up data" to justify their projects ? And I padd many others. Is it above or below average ? If below average then the reputation is earned.
C. Sagan : A demon haunted world:
http://www.amazon.com/gp/product/0345409469/
visit randi.org
And how exactly are we supposed to believe her study?
The television will not be revolutionized.
and up to 33.7% admitted other questionable research practices.
I wonder if this refers to shortcuts taken because its common knowledge, Such as, if you use water as a control lubricant, you might test its wetness, density, purity, viscosity, etc, to compare against water with a slippery polymer in it. I wonder if these "questionable" practices involved taking distilled water, making sure its pure distilled water, and then pulling the other factors off of charts for distilled water or if "Questionable" means something far worse.
The reason i bring this up is because hindsight is 20/20 and everybody knows every mistake that they've made, if they're smart and that's what they're fessing up to.
Is it sad that I am more likely to recognize you and your posts by your sig than your name or UID?
... and 78% of the surveys are made up on the spot.
Disclaimer: I'm a scientist.
Scientist will behave much better as soon as society (or perhaps the government at least) understands that if you want reliable information, you actually have to treat your scientist well.
Now, do not got me wrong, some countries, especially the US, invest quite a lot in science. But the problem is that the whole system is rotten to the core. It makes almost no sense at all for a young graduate to stay in a University/Institute. Pay will be low, and you have (in most countries) no job security. In Europe you either get a nice job at a company, or you go around taking post-docs for 5-10 years, hoping to get lucky. Working crazy hours with no holidays. For most, in the end, they go to a company anyway (having lost quite a lot of money in the process).
Often you are expected to go abroad, and unless you are lucky this leaves you with no good way to take care of your pension. Then if you want to return, somebody else took your place at university.
There is 2 ways to stay in the system: either you are lucky or you lie like hell.
Now, people may say that if your good you do not need luck. But remember that for high impact publications you need a lot more then good ideas and good skills. In research it is perfectly normal to conclude after 2 years that your hypothesis is false. This is great science, it also is hardly publishable in a good journal. People like positive results, and the reviewer system actually encourages you to confirm generally accepted ideas, not to falsify them.
Well, I could go on but I am sure others will.
To be honest, I do not even get angry anymore when I suspect someone may have done something "questionable". It's just sad.
The truth is the way that scientific institutions are set up isn't very scientific. There is definitely an attempt at oversight and impartiality but it's very easily corrupted by a wide variety of people with a wide variety of interests and ulterior motives. There aren't nearly enough checks and balances.
There are many things wrong with the system. Some include:
- Almost anyone can commission a study, write a book etc. and it's left to the scientific community to place value on that work. Viewed on it's own, without knowledge of the scientific community's opinion it can be difficult to tell how valid the work is. For example Wolfram's "New Science" has been largely debunked as mostly a rehash of old ideas (minus accreditation) but it took some time for this to become clear and in the meantime it was popularized in the press as a breakthrough work.
- The only real form of moderation is whether or not work has made it into a respected journal. Other scientists are then expected to publish corroborating work etc. However, until this is done, it is very difficult to judge the validity of the work, and papers get published that are later discredited. (Cold fusion anyone?) Likewise, work that should be published is often initially rejected. The primary motivation of a lot of the scientific journals is financial gain. In fact the entire publishing system is an antiquated remnant of the last 2 centuries and doesn't belong in an Internet connected world, yet publication is still the primary tool by which a scientist's work gets recognized.
- Speaking of antiquated the institutions, committees and governing bodies of science are about as scientific as a mother's group - it's all professional bitching and posturing for status. Real monkey hierarchy stuff. A lot of decisions get made on the basis of status. It's particularly bad for applied science professions like the medical profession where you hear stories about doctors who should have been prevented from practicing continuing for many years before being disciplined or quietly removed. At the senior level, scientists are often more politician than anything else as then need to secure funding and approval from political bodies. Then you see students who have to work their way up in status being treated like crap "paying their dues" as noted in a story posted a few days ago about a student who died in a chemical fire.
- Speaking of status, there is an emphasis on using scientific jargon to exclude the community at large. Some scientific ideas require complex specialized language and university post graduate mathematics to understand, and so require such specialized language. However even simple concepts must be described in overly complex specialized language to be accepted for journal publication. This is absolutely backward. We should have a system that requires simplified language where possible and a layman's overview attached early in the document. Instead, reading a scientific paper if you're not a specialist in the field is an art that you learn when you do post graduate work. If you assess a published article for readability you'll find the statistics you generate tell you that it's dense and difficult to understand. There are journals and subjects that allow simpler and informal
language but they are the exception rather than the rule and usually apply as addendum publications for applied fields. (Again I'm thinking of medicine. My own post grad work is in astronomy so I'm very much a lay reader when it comes to medicine, and when I've tried to read medical papers it's usually been an interesting excercise). Any real simplified content seems to get presented in slide form at conferences and presentations are often a better way of getting an overview.
I could go on about the shortcomings of various scientific institutions but I won't.
My point is that when you have a system that is so open to corruption, with so few checks and balances, and so much baggage inherited from institutions that began in the dark ages, it's no surprise that you end up with science that's much less than perfect.
These posts express my own personal views, not those of my employer
Definitely they sometimes fudge their data so that it will support their theories. Scientists are human and not perfect, it's part of human nature. That is where peer review comes in. A true scientist s work has to stand up to peer review and this is where the fudging of data is often uncovered. The problem is that much of the research going on is cloaked in secrecy by governments and corporations and proper peer review doesn't happen.
This brings to mind an incident in history where the scientist was right but his data was just too good. I'm talking about Gregor Mendel and his work on genetics. Later statistical analysis of his data indicates that it was very unlikely that he got that data. He probably got very close to the experiment result that he predicted but it was not good enough so he fudged his results. It wasn't until long after that this inconsistency in the data was uncovered. Was he right? Absolutely he was but his data is suspect nonetheless.
A number of my friends are scientists and some have told me they bodge the results now and again to match what they were expecting.
In that case, they're not scientists. If they fudge results, they are simply invalidating their experimental data by repeating their initial hypothesis as a result without bothering to challenge it.
I can understand commercial pressures for funding and so forth may be important to the researcher, but in many cases it saves everybody a lot of time if negative results are published to start with. Sure, they will rarely earn anyone a Nobel Prize, but we have to accept that a lot of what science is about is repetitious or tedious donkey-work.
2% - one in 50 - committing fraud to get ahead (or simply to keep their job) in a very competitive, volatile career environment. Sounds like it's in the right ballpark, and probably comparable to other professions. Some people are so career and status driven, and so unconcerned with the effects of their actions on other people, that they will break rules and cut corners no matter what the field.
I do question the other figures though, simply because "questionable research conduct" is such a very nebulous kind of categorization. You can delimit it in very different ways, all perfectly reasonable. You could even effectively decide which number you want then define the term in such a way that you reach it (a practice that would most likely be included in the term). Notably, the author excludes plagiarism, even though that is a serious offense in research for good reason, and one that I'd expect most surveys to include, not drop.
Also, the numbers for incidents by colleagues is rather pointless, since there is no indication of how many those colleagues are. If each participant has had a minimum total of eight colleagues altogether in their career up until this point, then the 14% rate fits very well with the self-reported 2% above. But of course, the participants do not know how many incidents they missed, and the number of times the mistakenly thought fraud was taking place is unknown. I would be very hesitant in trying to read anything at all into the numbers about witnessed incidents.
Trust the Computer. The Computer is your friend.
Scientists are humans, just like anyone else. Frankly, I think 1.97% is pretty low considering it is the combined total of all "fabricated, falsified or modified data or results". Notice that all of those aren't quite equal either. "Tweaking" results to tease out the answer you want (while still unethical and damaging to scholarship) is not as bad as outright falsification. Especially since it is not always clear where the line is between "modifying data", and doing valid statistical analysis like throwing away outliers. Yes, there are standards for outliers, but they are not universal, and confounding factors can occur during the experiment that make ethical decisions more difficult (i.e. the tester didn't read part of the script right, test subject's cell phone went off during test, survey answer was ambiguous and hard to read, the list goes on.)
The reality is that no one study should be taken as fact in isolation. It should either be corroborated by existing evidence (i.e. - it shines a new light on existing theories without contradiction), or by similar studies validating the results, or both.
Nutrition is a perfect example. How many studies have come out in the past 20 years that directly contradict (or seem to) prior studies done in that area? If someone followed each new "discovery" intently, they'd be so screwed up in their eating habits they'd probably end up being malnourished. However, looking back over a series of seemingly contradictory studies, we can see patterns which we've been able to make more sense of. We now have a greater understanding of "good" vs. "bad" cholesterol and the idea that fats aren't necessarily the root of all evil, and many similar findings. We still don't know all the answers, but we know lots more than any one study told us. This is how research works. It is also why graduate students writing dissertations are required to include a large section on "related work" so that they can get the full appreciation for where their research fits into the big picture, rather than basing their entire hypothesis on just one study or finding which might be contradicted in the next conference.
It starts while you are graduating.
A big chunk, quite a huge piece of graduation diploms, certificates etc. (depends on each country) are based in the most rabid form of falsifications - "copy/past". They are presented as something new, at least as a "new" variation of a well known theme, however there is nothing new on it. Just the same stufff written in different words.
The sad fact is that faculties and science departments accept it.
The good thing is that the large majority of these graduates will stay well away from science. Yes, they still will make damage, ex. CEO I had to deal with. He claimed in every possible corner he finished Oxford in finances (he did study in Oxford) but was unable to calculate an average. The guy sent the company 2 million dollars directly under the bottom and we had a great time, full of all sorts of fun, to recover the damage.
But some of these people do enter science! And that's where things start to go boost. I saw some people getting high positions on faculties just for one fact - they write too much and speak a lot. Really, nothing else. A seminar costs money, you send this bla-bla-bla over there. It is not a big matter that he hasn't found nothing new except a new way to describe gravity in words and funny pics. He goes there, makes his new discovery a literature best-seller, puts everyone wondering about his colorful PowerPoint diagrams. That's all folks! Seminar's monny is in the safe. And your bla-bla-bla will be published in the next Annals. So, more monny-monny may come.
Really I think that analysis are terribly skewed. My belief is that we have a lot more crap going around, desguised in small and very specific publications that no ones take into account. Why? Because it's crap from the very start! So why to take the task to read it? But such attitude hides the real dimension of the problem.
I see plenty of comments here of folk expecting some scientists will do bad things for gain/fame/award. However, science demands reproducible results and peer review. That's a safety net that catches a lot of bad science.
I find it odd that this is all based on Meta Analysis, which itself is still highly suspect.
Sig Battery depleted. Reverting to safe mode.
4 days ago on that same forum was a post about "Mars robots may have destroyed evidence of life". Scientists didn't fabricate false proofs there but simply made an unconcious mistake to prove their own preconceptions...
The funding for the "research" is provided by an entity with an agenda other than pure research, e.g. having a vested interest in a particular outcome or finding. Nowhere is this more common that in the U.S. pharmaceutical industry, where entire ersatz journals have been published to provide the appearance of well-documented and peer-reviewed research.
Beyond jailing those involved in such grand misconduct, I don't know where to draw the line, but I believe that separating profit from research, as far as possible, is a good first step. And yes, I am indeed advocating that medical research be "socialized". I have nothing against corporate profits, but when truth, not to mention the public good, takes a back seat to profits, the system is broken when viewed from any impartial perspective.
nt
when I did chemistry at 6th form college (UK term, in US I suppose you'd call it senior high?), I recall doing a practical test in chemistry (titration) where you had some mystery chemicals and a colour change. the experiment was rigged so that it was somewhat like a reaction we'd already seen, but was in fact something quite different. the instructions were to make accurate measurements first, draw the appropriate graphs and *then* speculate on the mystery ingredients.
it turned out that we'd never encountered the particular reagents before, and if you did the test accurately you'd have realised it wasn't the old familiar reaction, but had to be something new - the figures would simply not add up. however, a significant number of people rejigged their results to match the known reaction and failed the test totally for two reasons, first being for failing to make accurate measurements and secondly for faking the results.
I am surprised it is this small. I am sure part of the liars (which is what they are) are doing it for fame and to be the one. Others (liars too) are doing it to keep their jobs, whether that be to get money to do science, or just to cling on. And forget turning someone in. It will ruin your career.
Can we please put a stop to all these people citing peer review as a sort of wonder cure?
I peer review a lot of papers. And yes, it catches a lot of bad science. But most of that is just, bad experimental design, bad writing skills, wrong conclusions, uninteresting stuff, etc.
There is nothing I can do against some smart guy who makes up all the numbers, but knows enough of statistics to make it look plausible. It is often not feasible, or even impossible to redo the experiments. I never heard anybody do that anyway (maybe because you get 2-3 weeks to do your review, whereas the work would take half a year at least).
There's a big gray area. For instance, the Millikan oil drop experiment, which established quantization of charge, was arguably fraudulent. Millikan threw out all the data he didn't like, and then stated in his paper that he had never thrown out any data. His result was correct, but the way he went about proving it was ethically suspect.
Find free books.
Of course, there is a chronic lack of ability in science to find the bad ideas...
In the physical sciences it should be possible. Except under conditions of woolly thinking. The whole point of the scientific method is to make your best attempt to experimentally DISPROVE your hypothesis. You can never prove it, but you can hedge it about with so many conditions that it can be accepted as being true.
Obviously this isn't (I think) necessarily all that helpful in "pure" mathematics, but my maths education is only 1st-year Uni level, so I'm not qualified to expound on this.
From:
http://www.its.caltech.edu/~dg/crunch_art.html
"""
The crises that face science are not limited to jobs and research funds. Those are bad enough, but they are just the beginning. Under stress from those problems, other parts of the scientific enterprise have started showing signs of distress. One of the most essential is the matter of honesty and ethical behavior among scientists.
The public and the scientific community have both been shocked in recent years by an increasing number of cases of fraud committed by scientists. There is little doubt that the perpetrators in these cases felt themselves under intense pressure to compete for scarce resources, even by cheating if necessary. As the pressure increases, this kind of dishonesty is almost sure to become more common.
Other kinds of dishonesty will also become more common. For example, peer review, one of the crucial pillars of the whole edifice, is in critical danger. Peer review is used by scientific journals to decide what papers to publish, and by granting agencies such as the National Science Foundation to decide what research to support. Journals in most cases, and agencies in some cases operate by sending manuscripts or research proposals to referees who are recognized experts on the scientific issues in question, and whose identity will not be revealed to the authors of the papers or proposals. Obviously, good decisions on what research should be supported and what results should be published are crucial to the proper functioning of science.
Peer review is usually quite a good way to identify valid science. Of course, a referee will occasionally fail to appreciate a truly visionary or revolutionary idea, but by and large, peer review works pretty well so long as scientific validity is the only issue at stake. However, it is not at all suited to arbitrate an intense competition for research funds or for editorial space in prestigious journals. There are many reasons for this, not the least being the fact that the referees have an obvious conflict of interest, since they are themselves competitors for the same resources. This point seems to be another one of those relativistic anomalies, obvious to any outside observer, but invisible to those of us who are falling into the black hole. It would take impossibly high ethical standards for referees to avoid taking advantage of their privileged anonymity to advance their own interests, but as time goes on, more and more referees have their ethical standards eroded as a consequence of having themselves been victimized by unfair reviews when they were authors. Peer review is thus one among many examples of practices that were well suited to the time of exponential expansion, but will become increasingly dysfunctional in the difficult future we face.
We must find a radically different social structure to organize research and education in science after The Big Crunch. That is not meant to be an exhortation. It is meant simply to be a statement of a fact known to be true with mathematical certainty, if science is to survive at all. The new structure will come about by evolution rather than design, because, for one thing, neither I nor anyone else has the faintest idea of what it will turn out to be, and for another, even if we did know where we are going to end up, we scientists have never been very good at guiding our own destiny. Only this much is sure: the era of exponential expansion will be replaced by an era of constraint. Because it will be unplanned, the transition is likely to be messy and painful for the participants. In fact, as we have seen, it already is. Ignoring the pain for the moment, however, I would like to look ahead and speculate on some conditions that must be met if science is to have a future as well as a past.
"""
A 21st century issue: the irony of technologies of abundance in the hands of those still thinking in terms of scarcity.
You're right, except it's not what science "is", but what science "should be", and in practice your postulate is infeasible. Science is very much like selling carrot at a vegetable market, you are rewarded for being aggressive, not for being honest. There have been various social systems based on the assumption that people are inherently good and honest, and for all I know, they all failed miserably. The most successful theories are based on assumption that people are selfish, manipulative bastards. We need a system, in which being a selfish, manipulative bastard can benefit the others. For example, what if paper submissions, proposals, and paper reviews were never anonymous, but instead publicly available for scrutiny? I don't know if that would help, but intuition tells me that extreme transparency could go a long way making us all more fair and honest.
in agreement on Global Warming being caused by humans. Gee for a topic that actually isn't agreed on by all scientists, and that apparently could be riddled with faked or misinterpreted data we get told all day long that we are heathens if we don't believe the empirical scientific evidence. In fact if we don't tow the scientific line we must be dolts and shoved to the side as nutcases. Matter of fact we are about to make trillion dollar "Green" Cap and Trade laws all based on this Scientific Evidence, the heck with the evidence to the contrary.
That's how you teach it. Been doing that myself while supervising entry level lab session at university. You tempt em to "modify" their results early and let em face the wrath of their supervisor. Take-home lesson: It is tempting and easy to adapt data to your expectations, but YOU SHALL NOT DO IT.
Ubi solitudinem faciunt, pacem appellant.
According to a rigorous scientific study I just conducted, 7.
The survey percentages given are obviously fabricated
There have been various social systems based on the assumption that people are inherently good and honest, and for all I know, they all failed miserably.
There is apparently a management model that illustrates a given system as being like a tree full of monkeys. The monkeys at the top of the tree can look down, and all they see is monkeys. Whereas the monkeys at the bottom of the tree looking up only see assholes.
Sure, self-aggrandising bastards will take a lot of the kudos, perhaps at the expense of others more deserving. There is probably nothing that can prevent that. But my point regarding the actual conduct of research still applies. The application of the scientific method in an attempt to disprove any given hypothesis is what the real work is about. As soon as you discard that and attempt to work from the other direction, you cease to be a scientist and become a marketroid instead.
I am an experimental physicist in solid state physics. I think this subject in low to medium-prone to misconduct. Lets analyze the different aspects of it:
a) Motivation: getting your thesis/paper finished quicker/better, getting research money
b) Control Is there a control actually considering scientific behavior to be a fundamental good or is it just important that nothing is uncovered?
c) Ways of misbehaviour (i only write down what happened in the range of what i have seen/recognized(e.g. in other groups papers) or friends told me what they saw. I exclude friends of friends stories): Unclear formulation of experimental hypotheses *before* the experiment ("fishing in the dark"), not noting all people involved as authors, mentioning people not involved as authors, post-selection of experimental data supporting a hypothesis. incorrect labeling of data (e.g. different sample of same type etc), sabotage of co-workers experiments, beautification of data (the line between nonlinear filtering and faking is a thin one).
d) Ways of reporting without shooting yourself in your foot: ????? None?
e) Education towards it: negative (if you report results in lab courses which dont match the supervisors expectation, you get in trouble instead of turning the device on an measuring again. This educates people to copy last years results.
So let me summarize: the subtleness of some ways of manipulation coming together with a lack of control, education, and ways of reporting without getting damaged while seeing a good expected reward for bending the rules of science a little has turned many good people bad. Imagine a Bank where the money in the evening is not counted, the people are eductaed to just take a little bit, nobody is interested if some money is missing.
How many researchers are having sex with the lab chimps?
Have gnu, will travel.
If you think being a scientist sucks, try working on a factory floor.
Leaving aside your questionable assertion that being a factory worker is far worse than being a scientist, the more relevant comparison would be to jobs that require similar levels of education and competence. A compelling case can be made that the education and competence required to be a scientist is similar to that of a medical doctor, lawyer or high level engineer.
The problem with a career in science is that it is like a career in acting. Sure, there's the super stars at the top who are doing extremely well for themselves but then pretty much everyone else is struggling just to feed their families.
Of course, there are struggling actors who obviously don't have what it takes to be actors and there are struggling scientists who obviously don't have what it takes to be scientists. There are also, however, huge numbers of actors and scientists who are doing everything right and who are just as talented as the guys at the top but who somehow just didn't get their big break - and who, as a result, are struggling to feed their families.
So, what's the problem? Well, a lot of young are encouraged to embark on the long and arduous path to become scientists with the belief that they will eventually command salaries on par with careers that require similar levels of education and competence (medical doctors, lawyers, etc.). Unfortunately for them, when they final complete the dozen or so years of training to become scientists, they realize that they are overwhelmingly likely to command a salary on par with mid-level factory workers.
Eventually as knowledge about expected science salaries becomes more widespread, "the market" will probably adjust and young people who are considering careers in science will have enough information about expected salaries to choose other careers such as medicine, law, or management.
If the USA, for example, doesn't want to be a world leader in scientific research then that's totally fine. It's unfortunate for people who have already committed to a career in science but, with any luck, today's young people will choose other careers and complaints about low pay for scientists will go away because there won't be any scientists left to complain.
So, how many years of training do you need to work on a factory floor?
sic transit gloria mundi
You do the same thing with inclined ramp experiments in physics. The students know the relationship between the ramp angle and the speed the marble should be going, but they should get results that are pretty close but not quite right on because they haven't accounted for the rotational momentum of the marbles.
I wasn't advocating being a marketroid; I was pointing out that people naturally become marketroids, and instead of talking about ethics, we need to design the system to be marketroid-tolerant (where by "-tolerant", i mean as in Byzantine fault-tolerant). The monkey model you pointed to is consistent with what I said. As we grow to the top of the tree, we become manipulative, and more likely to look down on others whether it is justifiable or not. So the system inevitably manipulates us to become more of a marketroid ourselves, whether we like it or not. Is there some way marketroids can be manipulated? Surely, by telling them they are being immoral is not going to help. They view themselves as victims of the evil system, trying to follow the implicit principles of becoming successful. We humans have an amazing ability to justify our own mistakes and our flaws, and portray them as beautiful, noble, righteous, or find ways to push the blame onto others.
So, how many years of training do you need to work on a factory floor?
Obviously a lot more than the academic or managerial world gives credit for, as those companies that work on creating a positive and empowering culture for those so called drones tend to be the ones that succeed.
This is my sig.
The problem with a career in science is that it is like a career in acting. Sure, there's the super stars at the top who are doing extremely well for themselves but then pretty much everyone else is struggling just to feed their families.
Salaries for Chemists
Geology
You've got chemists coming out of the gate making almost 70k a year, moving up to 120k a year as their career progresses. Oh, and by the way, physicists and materials people would probably be making more in the USA if there was more domestic manufacturing. Don't need too many physicists if your economy is based on bad banking and real estate. Think about that, when you decide which car to buy. [hint buy made-in-usa]
This is my sig.
Oh yeah? Well, I'm going to do a meta-meta-analysis to see how common meta-analyses are fraudulently conducted.
you actually have to treat your scientist well.
You talk about working two years on an experiment to find out your hypothesis is wrong? Cry me a river. There's tons of people that work for two years, five years, ten years, pitching in to build up a business, and then they'll get bumped out on the street because some jackass guy in bufukistan can do it cheaper.
I think that you are missing the gp's point.
ASAICT he is saying that good research jobs *are* cushy ( which they should be - it's important to reward competent researchers ) but that we dont reward good research properly.
Working 2 years and producing a strong negative result is good science, but it doesnt get you published in a good journal. So, when you embark on a two year project as a post doc to test a hypothesis and get a negative result, what do you do? Get another post doc, and be severely underpaid for another 2 years? Leave science altogether? Or fabricate results. None of those are good options for a good researcher and, until we as a society start rewarding people for good science and not just exciting results, we will continue to have people inflating the excitement of their work.
As far as your analogy goes, I think it would be better to say that someone works 2, 5, 10 years to develop a *profitable* business and then be kicked out on the street when someone else develops a less profitable business. Does that happen? Probably, but I'll bet that it's pretty rare.
For example what are they trying to say here:
A pooled, weighted average of 1.97% of scientists admitted to having fabricated, falsified or modified data or results at least once â" a serious form of misconduct by any standard â" and up to 33.7% admitted other questionable research practices. In surveys asking about the behavior of colleagues, admission rates were 14.12% for falsification, and up to 72% for other questionable research practices.
All this depends on how they defined the questions. A narrow question "Have you fabricated data?" will result in a low number. A broad question "Have you ever done an experiment that you now think was not properly controlled?" will give a close to a 100% positive answers.
Is it surprising that if 2% of scientist falsify data 72% will now about that?
Not having done their own ground work the only think they can do is to tweak the statistics. Is anyone surprised that it didn't make it to a peer reviewed journal ??
Having said that i don't claim that scientific misconduct does not take place. Most of the research (I am talking about the academic biomedical field) is done by underpaid and overworked grad students and postdocs on tight schedules. They are under pressure to move on with their carriers and get some resemblance of normal life. Their supervisors are on tight schedules to produce results for grant reports and publications so they can get funded. Many universities (I would say most) even have goals of achieving external funding defined as dollars per square foot of lab space. If you don't look like you can bring money at the desired rate you are not hired as a PI, no matter how sound, innovative and important your work may be.
This pressure naturally makes people to take shortcuts. But all this is built into the system and there are safeguards. Poor quality research is harder to push into higher impact journals. Good data is reproduced by different groups using different methods and the predictions based on it are experimentally confirmed. So the bad stuff get's sifted out and the sound research gets incorporated into the base knowledge on which future work is built upon.
If anyone wants to reorganize the current system, they should first have a good plan on how to make it better. Preferably it will be tested on a small scale and shown to work as expected.
But in many occasions it takes a ridiculously long time. Aether
Einstein went from disproving the existance of Aether to, well, proving that that "nothing" is really "something." If only we'd had some term for "that thing that's there when we move all the rest of the stuff out."
If your incentives are aligned wrongly, policing will only go so far: it's like trying to destroy black markets by hiring more cops.
Most people don't go into science because they want to fabricate data. Sure, people want to be famous, but most of this data being fabricated isn't even anything that would make you famous (only a handful of high-profile examples are). You need a culture that neither encourages nor rewards attempts to meta-game the academic system, and a system that does not encourage gaming it, by for example judging scientists on some quantitative measure of their publication count multiplied by impact factor and citation count.
It's hard enough to answer difficult questions when everyone in question is acting in good faith, self-examining their own work before publishing it, and generally trying their best to do a good job. It's impossible if you're making some number of people feel they have no choice but to grit their teeth and publish papers they know are somewhat spun or not as good as they could've been. Let the scientists do their damn job, and stop the ranking/numbers game.
Of course, you can't just give everyone a big salary and free reign to spend the next 20 years doing whatever they want. But I would argue that you really need an evaluation of the quality of a scientist, not the quality of their output. Is this person insightful, knowledgeable, committed to doing good research, plugged in to what the real questions in their field are, has a plausible approach to answering them, etc.? If so, leave them the hell alone and let them decide how to best communicate their results, whether that be a flurry of 10 papers a year or one every 2 years.
In short, academic publishing is supposed to be about communication: you legitimately have something you think other people would want to read. Adding incentives based on the amount and type of that communication leads to people basically forcing themselves to communicate when they wouldn't have chosen to otherwise, because they need the lines on their CV; this does not improve the quality of the academic literature.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
"Our scientific systems and institutions should have better checks and balances. Many jobs/professions including monitoring and auditing to prevent corruption as standard."
checks = independent repeatability
balance = independent peer review
"We can do better!"
If any anyone has a more robust system with a better track record than science, I'm all ears.
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
Working 2 years and producing a strong negative result is good science, but it doesnt get you published in a good journal.
My point is that it is a general statement of the human condition that you have to be right. You can work for two years and produce a strong negative result in any field of life. To create a product and release it, is, ultimately, an experiment. If I spend two years working on a product, then sell it, and find out x,y,z is wrong with it. Will I have learned a lot? Yes. But, it doesn't help pay the bills. Makes no difference in science, or the real world.
Indeed, if someone did spend two years researching something and then finding out that their model was wrong in some way, I'd be willing to bet that there are a dozen other scientists saying, "well, I could have told you so.", just as much as there are in any other field.
You have to be right.
This is my sig.
With the cheating level of undergraduates rumored to be around half, I wonder have this declines to only two percent by the time you got your PhD? Two answers: (1) Science cheating is under-reported, or (2) scientists check each other results especially if they are important. I'm in computational physics where its fairly straight-forward to replicate another's results. Cheaters are discovered quickly. Other lab-based fields may not be as easy to get caught.
Working 2 years and producing a strong negative result is good science, but it doesnt get you published in a good journal.
My point is that it is a general statement of the human condition that you have to be right.
Certainly.
But a strong negative result is being 'right'
If I set out to test the hypothesis that strawberries cause cancer, and I find that they do not, and I can quantify the extent to which they do not, then I have succeeded. But Nature probably still wont publish my paper that says that strawberries do not cause cancer. ( Please dont criticize me for this example - I realize someone who sets out to test the hypothesis that strawberries cause cancer probably shouldnt be a researcher - I just chose the example to make a point. A better example would be whether or not histone flavors are relevant in DNA accessibility )
My point is that it is a general statement of the human condition that you have to be right. You can work for two years and produce a strong negative result in any field of life. To create a product and release it, is, ultimately, an experiment. If I spend two years working on a product, then sell it, and find out x,y,z is wrong with it. Will I have learned a lot? Yes. But, it doesn't help pay the bills.
Of course, but the point of releasing a product isnt to determine whether or not it is a good product. It's to make a successful product. A better analogy would be a consulting firm that was hired to determine whether or not a product release will be successful. Like scientists, this hypothetical consulting firm could be 'right' whether or not they said the product would be successful. To extend the analogy, what if the firm got paid more if they said the product would be successful? Dont you think that would bias their results?
Indeed, if someone did spend two years researching something and then finding out that their model was wrong in some way,
It's important to make a distinction between a model being wrong, and it not telling you what you expected to see. If I model global warming, and my model's predictions dont line up with reality, I've failed at being a scientist and dont deserve to be published. However, if my model predicts that global temperatures are unrelated to CO2 levels and future observations validate my results, then I've been successful ( and a good scientist ) but I bet I wont get nearly as much stimulus money as if my model had predicted the opposite.
HTML never fails, it is I who failed to set the right conditions for HTML to cooperate. ;)
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
I don't know what the specifics are for other countries, but here in Australia, a law is being drafted that any research that is done that in some way receives government money (grant, paper, etc), must retain all data (both non-simulated and simulated) *forever* and be publicly available. The time between publication and release of data is what is taking time to draft.
It will be a little while yet before it becomes mandatory. Clearly we are talking about major infrastructure as well as significant cultural change.
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I understand what you are saying and I think your strawberry example is great becaause it highlights the problem - many negative results are obvious and paying attention to them is a waste of time. If however there was a prevailing view that strawberries did cause cancer then a negative result would be interesting enough to publish. An good example is vaccines and autisim.
Your CO2 example is not so good, you are forgetting that the "model" part of the term "computer model" has nothing to do with software. I don't think it's an exageragion to say that if you had a convincing model that showed where Tyndal and/or Fourier fucked up then people would be throwing money at you.
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
Option 3: Those students that need to cheat in order to do well by and large don't go to graduate school, either because they're not smart enough or because they simply don't care.
If one does not show the validity of (many different) measurement instruments such as the surveys (re-)examined in TFA, it is fairly impossible to draw any valid conclusions in any meta-analysis. The alternative is to assume the validity of the originals. In this case, we are to assume that that the responses provided by people who are saying that they have not been honest are true, as well as assuming that the person(s) who created the instruments and/or reports derived from them and not just fabricating the results in part or in whole. And now with this meta-analysis we have to add another layer of unsupportable assumption of validity. Cripes, what a mess. But once you ask the question you have to ask it all the way down, and the question has to be asked.
One solution is to do independent replication. But for replications to be used to test the original results, enough of them have to be done to give an adequate statistical test of the comparison. It's tough enough just to get a decent experiment funded -- getting a replication funded is nigh impossible. And multiple replications? Forget it. Plus, in the publish-or-perish climate, damn few are willing to devote their time and energy to extensive work that gets little to no publishing credit. It's amazing we get anything done, much less further the progress of the science.
"I may be synthetic, but I'm not stupid." -- Bishop 341-B
What? No reference to global warming research here? Is this thing on?
Have you got any idea how difficult it is to refute an experimental outcome, at least in the less exact sciences?
That's the difference between science and pseudo science. There is vast amounts of pseudo science out there. Much of it looks very respectable too.
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Every bit of the data regarding second hand smoke has been contrived. The Robert Wood Johnson Foundation paid just through 2005 over 446 MILLION DOLLARS for tobacco control. 99 million to the ACS, ALA, AHA for bans. 84 million to create/fund Tobacco-Free Kids. RWJF was created by the founder of Johnson & Johnson. RWJF owns tens of millions of shares of J&J stock. J&J sells Nicotine Replacement Therapy products (CESSATION). With that kind of money any real data proving second hand smoke as a non-issue was hidden away! Only false "science" is used for this kind of social engineering.
It seems scientific misconduct is perfectly acceptable, in fact, condoned, when it comes to tobacco control. In PLoS Medicine, I attempted to get Stanton Glantz to declare his competing interests. He has received 1.5 million dollars in grants and UCSF has received 36 million dollars from the Robert Wood Johnson Foundation. There aren't many who don't know who the RJWF is but for those who do not, they were created by the founder of Johnson & Johnson. RWJF owns tens of millions of shares of J&J stock. Who sells the NRT products? J&J. In fact, RWJF paid, just through 2005, 446 million dollars in tobacco control grants. Some grants to ACS had Medicare pay for NRT. An RWJF national program director was involved in writing the federal guidelines that tells doctors they have to push the drugs, that the patient should NOT try to quit cold turkey. NRT has a 98.4% failure rate for quitting 1 year or longer. The former CEO of RWJF heads a 10 million dollar grant at UCSF, Center for Smoking Cessation Leadership Center (compliments of RWJF). Glantz and UCSF stand to gain a ton more grant money from RWJF and should have to declare competing interests. http://www.plosmedicine.org/annotation/getCommentary.action?target=info%3Adoi%2F10.1371%2Fjournal.pmed.0050178 Then you have the University of Minnesota and Elizabeth Klein from Ohio State University passing a recent tobacco control study off. The abstract states that exemptions from smoking bans for standalone bars have been considered to ease the economic burden for bars...so she collects employment data for bars...AND RESTAURANTS. She figures nothing in for lack of compliance to the law (in Ohio, year 2 after the ban there were over 7,000 complaints and investigations-HIGH compliance?). She does not say how many businesses were bars. In Minnesota, bars are outnumbered by restaurants 3 to 1. ClearWay Minnesota paid for this study and in the grant prosal it states "We believe that this research will provide public health officials and tobacco control advocates with information that can help shape adoption and implementation of CIA policies, and prevent their repeal." and "The proposed study ⦠will contribute to MPAAT's (now ClearWay) overall mission by providing information that enables adoption and successful implementation of policies to protect employees and the general public from secondhand smoke exposure." Think this study has no bias or stated outcomes desired? IT'S IN THE GRANT PROPOSAL!! And her article proclaiming no harm to bars and restaurants has been published everywhere with TV and the radio picking it up. This study has so many holes in it that if it were the Titanic, it wouldn't have made it out of the harbor. So...we issued a press release. http://news.prnewswire.com/DisplayReleaseContent.aspx?ACCT=104&STORY=/www/story/05-29-2009/0005034690&EDATE The problem is when "science" is bastardized to fit a social engineering scheme, science will never be trusted when it will need to be trusted. I'm disgusted with dung being passed off as valid. It has to stop.
Your CO2 example is not so good, you are forgetting that the "model" part of the term "computer model" has nothing to do with software. I don't think it's an exageragion to say that if you had a convincing model that showed where Tyndal and/or Fourier fucked up then people would be throwing money at you
And that's actually an understatement, and the fact that such a model does not exist, despite the obvious ticket to instant fame and fortune, tends to be the ultimate achilles heel in any argument of a GW denier. If they don't believe in the model that shows CO2 causes global warming, then, where's their alternative model that can be tested?
This is my sig.
after being around smokers, and why do i want to vomit just from the smell on their clothing.
Yes, that's how I feel when I'm around lots of perfumes and colognes. Doesn't mean I want them banned or that anyone has the right to ban them!
Not all areas have sufficient checks and balances. In fact, I hereby propound Business_Kid's law, that the effectiveness of the checks and balances in a scientific field are in inverse proportion to the media exposure in the public media. I think stem cell research is an exception to the above law, but it's good elsewhere. In my area (Electronics hardware) everything can be replicated, and very few headlines appear. Other areas are all headlines and very short on experimentally repeatable substance, for example Evolution. As for peer review: Galileo and Copernicus would have been silenced by peer review, as the ID movement is today in scientific journals. The real question is: How do you overcome bias?
I know why they were testing it to see how fast the planet was moving in the aether not to test if the aether existed.
Their notes are still available.