Rust Buckets: Not your father's Navy

[mind_messing]

ORIGINAL: RangerJoe

There is this famous research paper, often cited:

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

http://frontierpsychiatrist.co.uk/the-r ... -examined/

On the troubling trail of psychiatry’s pseudopatients stunt
Susannah Cahalan’s investigation of the social-psychology experiment that saw healthy people sent to mental hospitals finds inconsistencies — Alison Abbott reviews.

frontierpsychiatrist.co.uk/the-rosenhan-experiment-examined/

The Great Pretender: The Undercover Mission that Changed Our Understanding of Madness
Susannah Cahalan

n January 1973, Science (along with Nature, the most influential general science journal in the world) published an article that immediately captured major media attention. David Rosenhan, a Stanford social psychologist, reported that eight pseudo-patients had presented themselves at a variety of mental hospitals, 12 in all, complaining that they were hearing voices saying ‘hollow, empty and thud’, but otherwise behaving completely normally.

All of them, he reported, were promptly admitted, and all but one diagnosed as suffering from schizophrenia (the other receiving the somewhat more hopeful diagnosis of manic depressive psychosis). It took weeks for them to be released, though they were instructed to show no symptoms once admitted. When they were finally discharged, they received the damning diagnosis of ‘schizophrenia in remission’, a label that promised to compromise their futures ever afterwards.
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https://www.spectator.co.uk/article/how ... ck-decades

Review: 'The Great Pretender,' by Susannah Cahalan
NONFICTION: A thrilling and lively work of investigative journalism unmasks a 1970s study that fundamentally changed the discipline of psychiatry.
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In her acclaimed debut, “Brain on Fire: My Month of Madness,” Susannah Cahalan documented the psychotic break she suffered at 24, a terrifying episode that ended happily when it was determined that she had a completely curable autoimmune disorder — a neurological problem rather than a psychiatric one. What she had been saved from became achingly clear when, on tour for the book, she was told about another young woman with the same condition. Misdiagnosed and mistreated for two years instead of just a month, this woman’s cognitive abilities had grown so diminished that she could no longer care for herself.

Stunned by the precariousness of psychiatric diagnosis and the disastrous outcomes it can sometimes cause, Cahalan began the investigation documented in “The Great Pretender.” This vital book, full of intelligence and brio, is a must-read for anyone who has mental illness issues somewhere in their life — i.e., everyone.

Cahalan’s main focus is a study conducted in the 1970s by the late David Rosenhan of Stanford University. In it, eight patients, including Rosenhan himself, managed to get themselves diagnosed with schizophrenia and checked into mental wards simply by showing up and claiming that they were hearing voices. The “pseudo-patients” then spent from two weeks to 52 days institutionalized, treated and medicated (Rosenhan taught them to “cheek” their drugs) until they got themselves released, often with difficulty.

When the results of this study were published in Science magazine, humiliation rocked the psychiatric profession. The most significant long-range effects of Rosenhan’s landmark work included the widespread closing of hospitals and the vigorous revision and expansion of the Diagnostic and Statistical Manual of Mental Disorders — the DSM-III. This book, “as important to psychiatrists as the Constitution is to the U.S. government or the Bible is to Christians,” according to one of Cahalan’s sources, was written with the specter of those eight false diagnoses hanging over every page.

Cahalan’s main focus is a study conducted in the 1970s by the late David Rosenhan of Stanford University. In it, eight patients, including Rosenhan himself, managed to get themselves diagnosed with schizophrenia and checked into mental wards simply by showing up and claiming that they were hearing voices. The “pseudo-patients” then spent from two weeks to 52 days institutionalized, treated and medicated (Rosenhan taught them to “cheek” their drugs) until they got themselves released, often with difficulty.

When the results of this study were published in Science magazine, humiliation rocked the psychiatric profession. The most significant long-range effects of Rosenhan’s landmark work included the widespread closing of hospitals and the vigorous revision and expansion of the Diagnostic and Statistical Manual of Mental Disorders — the DSM-III. This book, “as important to psychiatrists as the Constitution is to the U.S. government or the Bible is to Christians,” according to one of Cahalan’s sources, was written with the specter of those eight false diagnoses hanging over every page.
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https://www.startribune.com/review-the- ... 564217782/

Science isn't fixed. Look at the advances that have been made in climate science over the past thirty years or so.

You may find this interesting as well.

[mind_messing]

ORIGINAL: RangerJoe

ORIGINAL: mind_messing

ORIGINAL: RangerJoe




Prison and fines imply a judicial trial, hence a judge and/or a jury. Can you comprehend things like that or does stuff like that have to be written out for you?

Oh, of course. Which is why I'd be interested to hear about the practicalities of how you'd ensure the judge and jury were presented the facts of the case properly.

For a hypothetical example to illustrate the point:

Let's say PhD student "A" is on trial for academic dishonesty in a paper on a computerized model of (let's just say) winged insect breeding patterns in tropical environments. The number of people able to comment on either (1) the biological aspect relating to the insects or (2) the computerized aspect will be small. The number able to do both will be smaller still.

Ask that question of a prosecutor. You want me to prove everything yet you make statements with no backing and when you are asked to show where said information is coming from, you do not answer - instead you get abusive. You also do not state what dishonest was in the paper. Insufficient information.

I thought that was a legitimate question to ask you of your proposal to challenge academic malpractice. If you're going to suggest subjecting people to financial penalties or incarceration, it would be a comfort to know that it was a well-thought out process.

As for where I'm getting my information, you've still not read the paper on the first page of the thread, have you?

For our hypothetical paper, seeing as you seem to be keen to engage with this, lets say that the accusation of dishonesty was that the code was deliberately manipulated to produce results divergent from previous research. The defence denies this. The results are outwith the margin of error from previous research, but not by a large degree.

[RangerJoe]

ORIGINAL: mind_messing

ORIGINAL: RangerJoe

ORIGINAL: mind_messing




Oh, of course. Which is why I'd be interested to hear about the practicalities of how you'd ensure the judge and jury were presented the facts of the case properly.

For a hypothetical example to illustrate the point:

Let's say PhD student "A" is on trial for academic dishonesty in a paper on a computerized model of (let's just say) winged insect breeding patterns in tropical environments. The number of people able to comment on either (1) the biological aspect relating to the insects or (2) the computerized aspect will be small. The number able to do both will be smaller still.

Ask that question of a prosecutor. You want me to prove everything yet you make statements with no backing and when you are asked to show where said information is coming from, you do not answer - instead you get abusive. You also do not state what dishonest was in the paper. Insufficient information.

I thought that was a legitimate question to ask you of your proposal to challenge academic malpractice. If you're going to suggest subjecting people to financial penalties or incarceration, it would be a comfort to know that it was a well-thought out process.

As for where I'm getting my information, you've still not read the paper on the first page of the thread, have you?

For our hypothetical paper, seeing as you seem to be keen to engage with this, lets say that the accusation of dishonesty was that the code was deliberately manipulated to produce results divergent from previous research. The defence denies this. The results are outwith the margin of error from previous research, but not by a large degree.

Fraud for monetary gain is illegal.

[mind_messing]

ORIGINAL: RangerJoe

ORIGINAL: mind_messing

ORIGINAL: RangerJoe




Ask that question of a prosecutor. You want me to prove everything yet you make statements with no backing and when you are asked to show where said information is coming from, you do not answer - instead you get abusive. You also do not state what dishonest was in the paper. Insufficient information.

I thought that was a legitimate question to ask you of your proposal to challenge academic malpractice. If you're going to suggest subjecting people to financial penalties or incarceration, it would be a comfort to know that it was a well-thought out process.

As for where I'm getting my information, you've still not read the paper on the first page of the thread, have you?

For our hypothetical paper, seeing as you seem to be keen to engage with this, lets say that the accusation of dishonesty was that the code was deliberately manipulated to produce results divergent from previous research. The defence denies this. The results are outwith the margin of error from previous research, but not by a large degree.

Fraud for monetary gain is illegal.

That's correct, fraud is in fact against the law.

What I was looking to see was some insight into how your proposed system would provide sufficient technical information to the jury to determine if the accusation is substantive or not, given the constraints outlined previously.

[RangerJoe]

ORIGINAL: mind_messing

ORIGINAL: RangerJoe

There is this famous research paper, often cited:

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

http://frontierpsychiatrist.co.uk/the-r ... -examined/

On the troubling trail of psychiatry’s pseudopatients stunt
Susannah Cahalan’s investigation of the social-psychology experiment that saw healthy people sent to mental hospitals finds inconsistencies — Alison Abbott reviews.

frontierpsychiatrist.co.uk/the-rosenhan-experiment-examined/

The Great Pretender: The Undercover Mission that Changed Our Understanding of Madness
Susannah Cahalan

n January 1973, Science (along with Nature, the most influential general science journal in the world) published an article that immediately captured major media attention. David Rosenhan, a Stanford social psychologist, reported that eight pseudo-patients had presented themselves at a variety of mental hospitals, 12 in all, complaining that they were hearing voices saying ‘hollow, empty and thud’, but otherwise behaving completely normally.

All of them, he reported, were promptly admitted, and all but one diagnosed as suffering from schizophrenia (the other receiving the somewhat more hopeful diagnosis of manic depressive psychosis). It took weeks for them to be released, though they were instructed to show no symptoms once admitted. When they were finally discharged, they received the damning diagnosis of ‘schizophrenia in remission’, a label that promised to compromise their futures ever afterwards.
.
.
.

https://www.spectator.co.uk/article/how ... ck-decades

Review: 'The Great Pretender,' by Susannah Cahalan
NONFICTION: A thrilling and lively work of investigative journalism unmasks a 1970s study that fundamentally changed the discipline of psychiatry.
.
.
.
In her acclaimed debut, “Brain on Fire: My Month of Madness,” Susannah Cahalan documented the psychotic break she suffered at 24, a terrifying episode that ended happily when it was determined that she had a completely curable autoimmune disorder — a neurological problem rather than a psychiatric one. What she had been saved from became achingly clear when, on tour for the book, she was told about another young woman with the same condition. Misdiagnosed and mistreated for two years instead of just a month, this woman’s cognitive abilities had grown so diminished that she could no longer care for herself.

Stunned by the precariousness of psychiatric diagnosis and the disastrous outcomes it can sometimes cause, Cahalan began the investigation documented in “The Great Pretender.” This vital book, full of intelligence and brio, is a must-read for anyone who has mental illness issues somewhere in their life — i.e., everyone.

Cahalan’s main focus is a study conducted in the 1970s by the late David Rosenhan of Stanford University. In it, eight patients, including Rosenhan himself, managed to get themselves diagnosed with schizophrenia and checked into mental wards simply by showing up and claiming that they were hearing voices. The “pseudo-patients” then spent from two weeks to 52 days institutionalized, treated and medicated (Rosenhan taught them to “cheek” their drugs) until they got themselves released, often with difficulty.

When the results of this study were published in Science magazine, humiliation rocked the psychiatric profession. The most significant long-range effects of Rosenhan’s landmark work included the widespread closing of hospitals and the vigorous revision and expansion of the Diagnostic and Statistical Manual of Mental Disorders — the DSM-III. This book, “as important to psychiatrists as the Constitution is to the U.S. government or the Bible is to Christians,” according to one of Cahalan’s sources, was written with the specter of those eight false diagnoses hanging over every page.

Cahalan’s main focus is a study conducted in the 1970s by the late David Rosenhan of Stanford University. In it, eight patients, including Rosenhan himself, managed to get themselves diagnosed with schizophrenia and checked into mental wards simply by showing up and claiming that they were hearing voices. The “pseudo-patients” then spent from two weeks to 52 days institutionalized, treated and medicated (Rosenhan taught them to “cheek” their drugs) until they got themselves released, often with difficulty.

When the results of this study were published in Science magazine, humiliation rocked the psychiatric profession. The most significant long-range effects of Rosenhan’s landmark work included the widespread closing of hospitals and the vigorous revision and expansion of the Diagnostic and Statistical Manual of Mental Disorders — the DSM-III. This book, “as important to psychiatrists as the Constitution is to the U.S. government or the Bible is to Christians,” according to one of Cahalan’s sources, was written with the specter of those eight false diagnoses hanging over every page.
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.
.

https://www.startribune.com/review-the- ... 564217782/

Science isn't fixed. Look at the advances that have been made in climate science over the past thirty years or so.

You may find this interesting as well.

It went from a new ice age, to global warming, to climate change. Guess what? The climate is variable and is always changing from one getting colder to one getting hotter. The climate is never static. There are many variables that go into it and we do not know all of the variables nor their values.

[BBfanboy]

We may not be totally responsible for climate change, but we are exacerbating it and the only things we can do to slow it is to drastically cut back on our own inputs. The question of whether it is cyclical or not is spurious. It is happening and we are going to feel the consequences, so we need to do something to mitigate what we can.

[RangerJoe]

If Climate Models Are Wrong For 2020, How Can They Get 2100 Right?

https://principia-scientific.com/if-cli ... 100-right/

Flawed Climate Models

The atmosphere is about 0.8˚ Celsius warmer than it was in 1850. Given that the atmospheric concentration of carbon dioxide has risen 40 percent since 1750 and that CO2 is a greenhouse gas, a reasonable hypothesis is that the increase in CO2 has caused, and is causing, global warming.

But a hypothesis is just that. We have virtually no ability to run controlled experiments, such as raising and lowering CO2 levels in the atmosphere and measuring the resulting change in temperatures. What else can we do? We can build elaborate computer models that use physics to calculate how energy flows into, through, and out of our planet’s land, water, and atmosphere. Indeed, such models have been created and are frequently used today to make dire predictions about the fate of our Earth.

The problem is that these models have serious limitations that drastically limit their value in making predictions and in guiding policy. Specifically, three major problems exist. They are described below, and each one alone is enough to make one doubt the predictions. All three together deal a devastating blow to the forecasts of the current models.

Measurement Error
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Scientists present measurement error by describing the range around their measurements. They might, for example, say that a temperature is 20˚C ±0.5˚C. The temperature is probably 20.0˚C, but it could reasonably be as high as 20.5˚C or as low as 19.5˚C.

Now consider the temperatures that are recorded by weather stations around the world.

Patrick Frank is a scientist at the Stanford Synchrotron Radiation Lightsource (SSRL), part of the SLAC National Accelerator Laboratory at Stanford University. Frank has published papers that explain how the errors in temperatures recorded by weather stations have been incorrectly handled. Temperature readings, he finds, have errors over twice as large as generally recognized. Based on this, Frank stated, in a 2011 article in Energy & Environment, “…the 1856–2004 global surface air temperature anomaly with its 95% confidence interval is 0.8˚C ± 0.98˚C.” The error bars are wider than the measured increase. It looks as if there’s an upward temperature trend, but we can’t tell definitively. We cannot reject the hypothesis that the world’s temperature has not changed at all.

The Sun’s Energy
Climate models are used to assess the CO2-global warming hypothesis and to quantify the human-caused CO2 “fingerprint.”

How big is the human-caused CO2 fingerprint compared to other uncertainties in our climate model? For tracking energy flows in our model, we use watts per square meter (Wm–2). The sun’s energy that reaches the Earth’s atmosphere provides 342 Wm–2—an average of day and night, poles and equator—keeping it warm enough for us to thrive. The estimated extra energy from excess CO2—the annual anthropogenic greenhouse gas contribution—is far smaller, according to Frank, at 0.036 Wm–2, or 0.01 percent of the sun’s energy. If our estimate of the sun’s energy were off by more than 0.01 percent, that error would swamp the estimated extra energy from excess CO2. Unfortunately, the sun isn’t the only uncertainty we need to consider.

Cloud Errors
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What is the net effect of cloudiness? Clouds lead to a cooler atmosphere by reducing the sun’s net energy by approximately 28 Wm–2. Without clouds, more energy would reach the ground and our atmosphere would be much warmer. Why are clouds hard to model? They are amorphous; they reside at different altitudes and are layered on top of each other, making them hard to discern; they aren’t solid; they come in many different types; and scientists don’t fully understand how they form. As a result, clouds are modeled poorly. This contributes an average uncertainty of ±4.0 Wm–2 to the atmospheric thermal energy budget of a simulated atmosphere during a projection of global temperature. This thermal uncertainty is 110 times as large as the estimated annual extra energy from excess CO2. If our climate model’s calculation of clouds were off by just 0.9 percent—0.036 is 0.9 percent of 4.0—that error would swamp the estimated extra energy from excess CO2. The total combined errors in our climate model are estimated be about 150 Wm–2, which is over 4,000 times as large as the estimated annual extra energy from higher CO2 concentrations. Can we isolate such a faint signal?
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Other Complications

Even the relationship between CO2 concentrations and temperature is complicated.

The glacial record shows geological periods with rising CO2 and global cooling and periods with low levels of atmospheric CO2 and global warming. Indeed, according to a 2001 article in Climate Research by astrophysicist and geoscientist Willie Soon and his colleagues, “atmospheric CO2 tends to follow rather than lead temperature and biosphere changes.”

A large proportion of the warming that occurred in the 20th century occurred in the first half of the century, when the amount of anthropogenic CO2 in the air was one quarter of the total amount there now. The rate of warming then was very similar to the rate of warming recently. We can’t have it both ways. The current warming can’t be unambiguously caused by anthropogenic CO2 emissions if an earlier period experienced the same type of warming without the offending emissions.
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Climate Model Errors

Before we put too much credence in any climate model, we need to assess its predictions. The following points highlight some of the difficulties of current models.

Vancouver, British Columbia, warmed by a full degree in the first 20 years of the 20th century, then cooled by two degrees over the next 40 years, and then warmed to the end the century, ending almost where it started. None of the six climate models tested by the IPCC reproduced this pattern. Further, according to scientist Patrick Frank in a 2015 article in Energy & Environment, the projected temperature trends of the models, which all employed the same theories and historical data, were as far apart as 2.5˚C.

According to a 2002 article by climate scientists Vitaly Semenov and Lennart Bengtsson in Climate Dynamics, climate models have done a poor job of matching known global rainfall totals and patterns.

Climate models have been subjected to “perfect model tests,” in which the they were used to project a reference climate and then, with some minor tweaks to initial conditions, recreate temperatures in that same reference climate. This is basically asking a model to do the same thing twice, a task for which it should be ideally suited. In these tests, Frank found, the results in the first year correlated very well between the two runs, but years 2-9 showed such poor correlation that the results could have been random. Failing a perfect model test shows that the results aren’t stable and suggests a fundamental inability of the models to predict the climate.

The ultimate test for a climate model is the accuracy of its predictions. But the models predicted that there would be much greater warming between 1998 and 2014 than actually happened. If the models were doing a good job, their predictions would cluster symmetrically around the actual measured temperatures. That was not the case here; a mere 2.4 percent of the predictions undershot actual temperatures and 97.6 percent overshot, according to Cato Institute climatologist Patrick Michaels, former MIT meteorologist Richard Lindzen, and Cato Institute climate researcher Chip Knappenberger. Climate models as a group have been “running hot,” predicting about 2.2 times as much warming as actually occurred over 1998–2014. Of course, this doesn’t mean that no warming is occurring, but, rather, that the models’ forecasts were exaggerated.

Conclusions

If someone with a hand-held stopwatch tells you that a runner cut his time by 0.00005 seconds, you should be skeptical. If someone with a climate model tells you that a 0.036 Wm–2 CO2 signal can be detected within an environment of 150 Wm–2 error, you should be just as skeptical.

As Willie Soon and his coauthors found, “Our current lack of understanding of the Earth’s climate system does not allow us to determine reliably the magnitude of climate change that will be caused by anthropogenic CO2 emissions, let alone whether this change will be for better or for worse.”

https://www.hoover.org/research/flawed-climate-models

[Panjack]

I will foolishly respond to some of the issues thrown out above.

1. I spent many years on the editorial board of a academic publication. I saw no examples of fraud but only examples of poorly thought out and implemented research. However, one time an unhappy author, who had his paper rejected by the journal, hired a lawyer who then threatened the journal, and each member of the editorial board, for some legally unclear reason related to bad faith. In response, we had to hire a lawyer. Many lawyer's bills later, the journal edged toward bankruptcy. We had to settle not because the unhappy author had a plausible case but because we were running out of money.

Generalizing: the vast majority of academic journals can't afford to get involved in any legal battles as they don't have much money in their coffers. Any proposal to have a journal engage in activities that might lead to legal battles (such as proposed above related to them punishing authors who the journal believes engaged in fraud of some sort) will not get very far with the journals themselves.

2. Many academic authors will be financially stressed to post some sort of bond. For example, my son will soon submit his first academic article, but as a poor graduate student he struggles to pay his rent each month. But what if he had to come up with, say, $5000 for a bond? That's not happening.

3. A good portion of academic research is very complex and, to tell you the truth, possibly filled to lots of small "errors." This is not because of bad faith but because of mistakes, oversights, and random events that just occur. Plus, you often face having to decide which of 3 or 4 or 5 possible assumptions to make at dozens of decision points. You might have little guidance about what is the "correct" assumptions because, well, some are not testable. You do your best, and hope you haven't done anything too dumb. But, if some journal decides that some mistakes and some assumptions were not just someone doing the best they could but, instead, were motivated by fraud then you have a big problem as an author.

It is true some obvious fraud occurs, but it is extremely rare. Establishing some heavy-handed punitive system to address this rare event will have negative consequences that in total would likely vastly exceed the benefit of any bad actors caught.

In any case, many journals in many fields have established systems to not necessarily address fraud but to lower the cost of replication. For instance, some journals required the posting of all data used along with all computer code behind the article. Low-cost replication is very important because the academic world generally gives little reward to the replication of previous results but lowering the cost will increase replication articles. As a side effects, such emphasis on public posting of data/computer programs will reduce fraud. Indeed, this is likely the best thing to do to address fraud. Anything more will likely lead to negative unintended consequences. Most fraud is caught, I think, by people getting the data and saying, "that doesn't look right to me." (Unfortunately, in some fields and in some research, data can't be publicly releases, such as medical records.)

Finally, about climate science: it is noteworthy that those who attack climate science are often associated with right-wing think tanks. Nothing necessarily wrong with that, of course. But, more importantly, the quality of the work done by such people is very low: lots of fancy terms thrown out to make it look like something important as occurred but often little of consequence is revealed.

In any case, the evidence is overwhelming that the average world temperature has grown since the dawn of the industrial age and that the release of greenhouse gasses is the most likely cause of this increase. Of course, the world climate system is massively complex, and we likely will never be able to precisely model it. Yes, huge uncertainties exist and, yes, imposed over any trend are cycles of many other things. Such a situation is not an argument against human-caused climate change. Indeed, it is what you'd expect in a complex system.

Further, even if the probability of a really bad outcome is fairly low, the cost of this very bad outcome is huge. A parallel situation: the odds that my house will burn down is very low. Yet, the cost to me of such a fire is so large that I willingly pay for my house insurance each year. I grumble at the premium each year but I won't go without such insurance. (Of course, I also willingly pay for my earthquake insurance each year although it has something like a 50k deductible!) Anti-climate change policies are best seen as insurance.

[RangerJoe]

Here is a bunch of links to various articles:

https://realclimatescience.com/2021/02/ ... ople-warm/

[RangerJoe]

ORIGINAL: Panjack

I will foolishly respond to some of the issues thrown out above.

1. I spent many years on the editorial board of a academic publication. I saw no examples of fraud but only examples of poorly thought out and implemented research. However, one time an unhappy author, who had his paper rejected by the journal, hired a lawyer who then threatened the journal, and each member of the editorial board, for some legally unclear reason related to bad faith. In response, we had to hire a lawyer. Many lawyer's bills later, the journal edged toward bankruptcy. We had to settle not because the unhappy author had a plausible case but because we were running out of money.

Generalizing: the vast majority of academic journals can't afford to get involved in any legal battles as they don't have much money in their coffers. Any proposal to have a journal engage in activities that might lead to legal battles (such as proposed above related to them punishing authors who the journal believes engaged in fraud of some sort) will not get very far with the journals themselves.

2. Many academic authors will be financially stressed to post some sort of bond. For example, my son will soon submit his first academic article, but as a poor graduate student he struggles to pay his rent each month. But what if he had to come up with, say, $5000 for a bond? That's not happening.

3. A good portion of academic research is very complex and, to tell you the truth, possibly filled to lots of small "errors." This is not because of bad faith but because of mistakes, oversights, and random events that just occur. Plus, you often face having to decide which of 3 or 4 or 5 possible assumptions to make at dozens of decision points. You might have little guidance about what is the "correct" assumptions because, well, some are not testable. You do your best, and hope you haven't done anything too dumb. But, if some journal decides that some mistakes and some assumptions were not just someone doing the best they could but, instead, were motivated by fraud then you have a big problem as an author.

It is true some obvious fraud occurs, but it is extremely rare. Establishing some heavy-handed punitive system to address this rare event will have negative consequences that in total would likely vastly exceed the benefit of any bad actors caught.

In any case, many journals in many fields have established systems to not necessarily address fraud but to lower the cost of replication. For instance, some journals required the posting of all data used along with all computer code behind the article. Low-cost replication is very important because the academic world generally gives little reward to the replication of previous results but lowering the cost will increase replication articles. As a side effects, such emphasis on public posting of data/computer programs will reduce fraud. Indeed, this is likely the best thing to do to address fraud. Anything more will likely lead to negative unintended consequences. Most fraud is caught, I think, by people getting the data and saying, "that doesn't look right to me." (Unfortunately, in some fields and in some research, data can't be publicly releases, such as medical records.)

Finally, about climate science: it is noteworthy that those who attack climate science are often associated with right-wing think tanks. Nothing necessarily wrong with that, of course. But, more importantly, the quality of the work done by such people is very low: lots of fancy terms thrown out to make it look like something important as occurred but often little of consequence is revealed.

In any case, the evidence is overwhelming that the average world temperature has grown since the dawn of the industrial age and that the release of greenhouse gasses is the most likely cause of this increase. Of course, the world climate system is massively complex, and we likely will never be able to precisely model it. Yes, huge uncertainties exist and, yes, imposed over any trend are cycles of many other things. Such a situation is not an argument against human-caused climate change. Indeed, it is what you'd expect in a complex system.

Further, even if the probability of a really bad outcome is fairly low, the cost of this very bad outcome is huge. A parallel situation: the odds that my house will burn down is very low. Yet, the cost to me of such a fire is so large that I willingly pay for my house insurance each year. I grumble at the premium each year but I won't go without such insurance. (Of course, I also willingly pay for my earthquake insurance each year although it has something like a 50k deductible!) Anti-climate change policies are best seen as insurance.

In some of the links that I posted, some people were being investigated by prosecutors. One person even fled a country to evade prosecution. That is how that should be handled.

As far as publishing, that is a privilige that the journals provide. It is not mandatory for them to print all research articles of whomever wants them published. It is like any other business established which reserves the right to do business with a person or not to do business with a person. As far as the cost of legal fees, have the losing side pay the winning sides legal fees - that includes the lawyer on the other side as well.

[Panjack]

Pick one article you'd like to discuss, and I'll discuss it with you. Won't that be fun and enlightening?

[Panjack]

I guess my anecdote of a journal facing bankruptcy when faced with a lawsuit didn't take with you.

[RangerJoe]

ORIGINAL: Panjack

I guess my anecdote of a journal facing bankruptcy when faced with a lawsuit didn't take with you.

Actually, I have been busy and that should be another thread.