Category Archives: ethics

How Lucky Is Too Lucky in Minecraft?

Earlier this year, a cheating scandal erupted in the world of competitive computer gaming, where a Minecraft player recorded a world-record setting speedrunning round that was too good to be true.

Here's how PC Gamer described the controversy, which involves a popular Minecraft player who goes by the moniker "Dream":

Dream's popularity is largely thanks to the YouTuber's Minecraft speedrun videos, where he tries to complete the game as fast as possible, and their Minecraft manhunt series, which is ridiculously popular. Dream's speedruns continually break records and make the Minecraft world speedrun leaderboard, to the astonishment of many viewers. During this success, suspicions arose about the legitimacy of some of his runs, and in particular, accusations arose about Dream tampering with the game to get better luck.

The accusations arose in October 2020 from a fellow Minecraft speedrunner (whose tweets have since been deleted) who reported seeing higher RNG drops for key items in a run submitted by Dream earlier that month, the same run that placed 5th on the world leaderboards.

Minecraft speedruns are officiated by a team of moderators from speedrun.com and this accusation prompted the team to investigate. In December, they released a 29-page long research paper and accompanying YouTube video summarizing the two-month investigation.

Here's the video for the official moderator's analysis, which is a little over 14 minutes long. Don't watch it yet. Just scroll past it for now and come back to it if you want to later....

The reason we've suggested holding off in watching the official video is because there's a much better video that explains how unlikely the world record-setting accomplishment was, featuring Matt Parker. At nearly 40 minutes long, it is nearly three times the time investment to watch, but you'll be rewarded with a much better appreciation of why Speedrun.com's officials ultimately rescinded Dream's world-record setting title for being "too lucky."

Now for the real mystery. Other than for establishing bragging rights, why does any of this matter?

A potential financial motive can be found in the PC Gamer article:

With 15.4 million subscribers and many of his videos hitting anywhere between 20-60 million views, it's safe to say that 2020 was one heck of a year for the Minecraft YouTuber, Dream. The speedrunner quickly rose to fame, gaining millions of followers so quickly that his subscriber count grew by 12 million between January and November last year alone.

Those rapid growth stats led us to ask "how much is having someone watch a video on YouTube worth to the video's creator?"

Vloggergear answered that question back in 2018, which is useful because even though the values may have changed in the years since, the method for finding the value to a Youtube content creator will be similar.

YouTube uses a method called CPM or “Cost Per Mille” which is a marketing term for cost per 1,000 views or in some cases impressions. Typically the CPM for YouTuber can range from 20 cents to $10 per 1,000 views. But typically an average channel will get about $1.50 – $3 per 1,000 views.

Let's say Dream's channel is at the bottom of the "average" scale. At $1.50 per 1,000 views of just one speedrun video, 20 million views could net $30,000.

A survey of Dream's YouTube channel indicates a posting frequency of 1-2 videos per month. We counted 23 videos that were clearly less than a year old, with a cumulative view total of 842 million. At $1.50 per 1,000 views, that's $1.263 million. And that is a low end estimate.

That revenue, even in the face of the Minecraft speedrunning scandal, perhaps explains Dream's response to having a world record title revoked:

It's a thorough report and, many statistical graphs and math calculations later, the team came to the conclusion that Dream was cheating by modifying the game. When moderators announced their decision, Dream categorically denied the accusation but has since respectfully accepted the team's conclusion without admitting fault.

When you're on track to collect over $1.2 million a year as a low end estimate for making online videos of your video game playing results, there's not much point in spending a lot of time contesting the statistical evidence for the sake of holding onto a title. Especially if like Dream, you can continue averaging between 30 and 38 million views per the handful of YouTube videos posted since the controversy erupted. It's also why the officials really aren't all that upset either. Plus, we haven't even mentioned Dream's revenue stream from merch yet, which we understand is pretty substantial in its own right.

In a lot of ways, it's a modern day replay of the 1950s quiz show scandals.

Now's the point in time to go back to the officials' 14 minute YouTube video if you like. Or to rethink your career choices.

Reliving a Day of Panic in the Coronavirus Pandemic

Today marks the anniversary of the most pivotal moment in New York Governor Cuomo's COVID nursing home deaths scandals. Because one year ago today, Governor Cuomo and senior members of his administration reached the point of panic as they struggled to address the greatest challenge of his tenure in office.

We originally presented that story on 12 May 2020. Today, we're re-running that original article, in which we recreated critical information that influenced the most consequential decision Governor Cuomo made on that day. The deadly repercussions of what resulted from that day of panic are still rippling through New York and making national news a year later. Let's get started....


COVID-19 - Martin Sanchez via Unsplash: https://unsplash.com/photos/Tzoe6VCvQYg

We're fascinated with how politicians use data and models in setting the policies they pursue, where knowing both what they knew and when they knew it can explain a lot about why they made the choices they did at the time they made them.

To that end, we've been paying attention to how Governor Andrew Cuomo has been managing the difficult task of coping with the coronavirus epidemic in New York, and in New York City in particular, which has been the focal point for both the number of cases and the spread of the SARS-CoV-2 coronavirus across the United States. We've assembled a timeline of Governor Cuomo discussing the predictive models for how fast the coronavirus infection would spread within New York, which provides insight into how that information affected his decisions for how to allocate the limited health care resources over which he had influence during the worst part of the epidemic in his state.

We're going to pick up the action shortly after 7 March 2020, the date Governor Cuomo declared a state of emergency because of the coronavirus epidemic in New York, when the number of coronavirus cases within the state had 'soared' to 89. The following article is the earliest in which we find a reference to coronavirus modeling projections for New York City, which had been put together by New York City Mayor Bill de Blasio's staff:

9 March 2020: Coronavirus Cases in New York State Rise to 105:

Mayor Bill de Blasio said Sunday that the city had 13 confirmed cases, including a new case of a man in the Bronx. Based on modeling, his team estimated there could be 100 cases in the next two or three weeks, but for most people, the illness would result in very mild symptoms.

Three days later, New York City had nearly reached that total and was set to blast through it, prompting Governor Cuomo to ban all public events with more than 500 people in attendance and to require gatherings with fewer than 500 people to cut capacity by 50%. The faster than previously projected growth in the number of COVID-19 infections drove a change in public policy.

Four days after that, Governor Cuomo had clearly been presented with projections that showed the exponential growth in the number of cases that had gotten underway in New York.

16 March 2020 - Audio & Rush Transcript: Governor Cuomo is a Guest on CNN's Cuomo Prime Time:

"I see a wave and the wave is going to break on the health care system ... You take any numerical projections on any of the models and our health care system has no capacity to deal with it."...

"Yeah. I think you look at that trajectory, just go dot, dot, dot, dot, connect the dots with a pencil. You look at that arc, we're up to about 900 cases in New York. It's doubling on a weekly basis. You draw that arc, you understand we only have 53,000 hospital beds total, 3,000 ICU beds, we go over the top very soon."

At this point, Governor Cuomo was beginning to appreciate that the thousands of hospital beds across the state of New York were really a scarce resource. He expanded on that realization the next day after an overnight surge in the number of reported cases:

17 March 2020 - Video, Audio, Photos & Rush Transcript: Governor Cuomo Announces Three-Way Agreement with Legislature on Paid Sick Leave Bill to Provide Immediate Assistance for New Yorkers Impacted By COVID-19:

"There is a curve, everyone's talked about the curve, everyone's talked about the height and the speed of the curve and flattening the curve. I've said that curve is going to turn into a wave and the wave is going to crash on the hospital system.

I've said that from day one because that's what the numbers would dictate and this is about numbers and this is about facts. This is not about prophecies or science fiction movies. We have months and moths of data as to how this virus operates. You can go back to China. That's now five, six months of experience. So just project from what you know. You don't have to guess.

We have 53,000 hospital beds in the State of New York. We have 3,000 ICU beds. Right now the hospitalization rate is running between 15 and 19 percent from our sample of the tests we take. We have 19.5 million people in the State of New York. We have spent much time with many experts projecting what the virus could actually do, going back, getting the China numbers, the South Korea numbers, the Italy numbers, looking at our rate of spread because we're trying to determine what is the apex of that curve, what is the consequence so we can match it to the capacity of the health care system. Match it to the capacity of the health care system. That is the entire exercise.

The, quote on quote, experts, and by the way there are no phenomenal experts in this area. They're all using the same data that the virus has shown over the past few months in other countries, but there are extrapolating from that data.

The expected peak is around 45 days. That can be plus or minus depending on what we do. They are expecting as many as 55,000 to 110,000 hospital beds will be needed at that point. That my friends is the problem that we have been talking about since we began this exercise. You take the 55,000 to 110,000 hospital beds and compare it to a capacity of 53,000 beds and you understand the challenge."

Faced with the potential shortage of needing 110,000 beds and only having 53,000 to provide care to coronavirus patients in New York, Governor Cuomo lobbied President Trump for support, which resulted in President Trump ordering the U.S. Navy's hospital ship USNS Comfort to sail to New York City the next day, and also lobbied for the U.S. Army's Corps of Engineers to begin identifying public facilities in New York City to be converted for use as temporary hospitals to handle the projected overflow of coronavirus patients from regular hospitals.

USNS Comfort would arrive in New York City on 30 March 2020, and the Army Corps of Engineers would have 1,000 beds ready at New York City's Javits Center ready on 27 March 2020, and were working to expand it to a 2,500 bed temporary hospital facility by 1 April 2020. But during the time in between, the updated projections of the coronavirus models led Governor Cuomo to panic.

24 March 2020: Andrew Cuomo: Apex of coronavirus outbreak in NY two or three weeks away:

Cuomo, speaking at his daily COVD-19 briefing in Manhattan, said the state's projection models now suggest the apex of the coronavirus crisis could hit New York within 14 to 21 days, rather than the 45 days the state projected late last week.

He likened it to a "bullet train" headed for New York, urging the federal government to deploy as many ventilators and as much protective medical gear it can to the state as quickly as possible.

"Where are they?" Cuomo said. "Where are the ventilators? Where are the masks? Where are the gowns? Where are they?”

At this point, we should show what one of the more influential coronavirus models that Governor Cuomo was using looked like. The following chart is taken from the Institute for Health Metrics and Evaluation (IHME)'s 25 March 2020 projections showing its estimates of the minimum, likely, and maximum number of additional hospital beds that would be needed in the state of New York to care for the model's expected surge of coronavirus patients.

IHME Forecast of All Hospital Beds Required for COVID-19 Care Beyond Available Capacity in New York State, Projection from 25 March 2020

This is just one of several coronavirus models whose projections were being combined and presented to Governor Cuomo by consultants from McKinsey & Co., where the IHME's coronavirus model's projections for New York are consistent with the figures and timing of a peak cited by Governor Cuomo in the days preceding his panic.

Faced with what appeared to be an imminent shortage of hospital beds and other medical resources, the Cuomo administration appears to have adopted an emergency triage strategy, one that would have devastatingly deadly consequences. Here, to free up as many beds as possible in New York's near-capacity hospitals, the Cuomo administration would try to move as many patients infected with the SARS-CoV-2 coronavirus as they could out of these facilities into others, even though they could still be contagious and present the risk of spreading infections within the facilities to which they would be transferred.

25 March 2020: The facilities in which they chose to place them were predominantly privately run nursing homes, where a directive issued by the state's Department of Health on 25 March 2020 mandated they must admit them into their facilities, where refusals could mean the loss of their New York state-issued licenses to operate.

New York Department Of Health Directive to Nursing Homes Mandating Admission of Coronavirus-Infected Patients, 25 March 2020

Flashing forward to the end of March 2020, the coronavirus epidemic forecast models Governor Cuomo was using in making his decisions were pointing to the peak still being ahead:

Cuomo said various predictive models being used by New York indicate the apex of the surge for hospitals will come anywhere from 7 to 21 days from now.

“The virus is more powerful, more dangerous than we expected,” Cuomo said. “We’re still going up the mountain. The main battle is on top of the mountain.”

Four days later, the coronavirus models were predicting the peak was almost upon New York:

While giving an update Saturday on the frantic work to ready New York hospitals for the most intense period of the coronavirus (COVID-19) crisis, Gov. Andrew Cuomo said that the state’s models put the so-called apex about four-to-eight days out.

“By the numbers, we’re not yet at the apex. We’re getting closer,” he said at his daily press briefing. “Depending on whose model you look at, they’ll say four, five, six, seven, days, some people go out 14 days. But our reading of the projections is that we’re somewhere in the seven-day range. Four, five, six, seven, eight-day range.”

“Part of me would like to be at the apex, and just, let’s do it,” Cuomo continued. “But there’s part of me that says it’s good that we’re not at the apex because we’re not yet ready for the apex, either. We’re not yet ready for the high point...the more time we have to improve the capacity, the better.”

But on 6 April 2020, the IHME model revised its estimates for New York and the U.S. downward, indicating the peak Governor Cuomo feared would overwhelm New York's hospitals was not going to come anywhere close to what it had previously projected. On 8 April 2020, it indicated New York had already passed its peak in number of daily new cases.

Ordinarily, that would be a good thing. Except, Governor Cuomo had taken an action by which he intended to avoid the spectacle of having pictures of sick New Yorkers not able to get medical treatment in the media, but instead ensured the state's death toll from its coronavirus epidemic would no longer be small. That part of the story has its own special timeline, which we've moved here from the bottom of the article where we had previously been piecing together this part of the story of COVID-19 in New York....

Image credit: unsplash-logoMartin Sanchez


The explosion of Cuomo scandal news has prompted us to launch a new blog to host the timeline we had been updating regularly in this space! We officially launched the new site a week ago. If you haven't yet seen it, may we introduce A Timeline of New York Governor Andrew Cuomo's Nursing Home Scandals.

The Governor Who Kills Grandmas?

Now serving all your Cuomo nursing home scandal news needs!

The Dark Side of Success for U.S. Soybean Exports

In 2017, U.S. soybean producers sent an estimated 1.32 billion bushels of their crop to China, the second-most on record. The record for U.S-to-China soybean exports came a year earlier, when U.S. soybean producers exported an estimated 1.53 billion bushels of their crop that year to China, which was a dramatic increase over the 1.15 billion bushels they sent to China in the year before.

Estimated Bushels of Soybeans Exported by U.S. to China, 2012-2017

2016 would appear to be have been the most successful year to date for U.S. soybean exporters, but there's a lot more to that story.

Although the year saw optimal growing conditions for soybeans in the U.S., which resulted in a bumper crop, one of the main contributors to the success of U.S. soybean producers that year came about as a result of a severe drought in Brazil, the world's top soybean exporting nation.

Brazil's drought created a unique opportunity for U.S. soybean producers seeking to claim a larger share of the world market in 2016. Since Brazil's annual harvest peaks in the second quarter of each year, thanks to its Southern hemisphere geography that puts its growing seasons six months ahead of the U.S., the news that Brazil's 2016 soybean crop and exports would be reduced because of drought conditions provided U.S. growers with the advance warning they would need to respond to what, for them, would be an opportunity.

So they took it. U.S. soybean producers planted seed varieties that would optimize the yield for their crops, which helped contribute to 2016's bumper crop in the United States. They then aggressively harvested the crop to satisfy China's domestic demand for soybeans, where China was buying up as many bushels of soybeans from the U.S. as they could that year.

But there was a dark side to that success, which is now becoming increasing apparent. In choosing seeds that would maximize crop yields, U.S. soybean producers sacrificed the protein content of their crop, effectively reducing the quality of their product. In 2017, that meant having to compete with higher quality soybeans grown in Brazil as that nation's crops have rebounded from 2016's drought conditions.

U.S. soybean growers are losing market share in the all-important China market because the race to grow higher-yielding crops has robbed their most prized nutrient: protein.

Declining protein levels make soybeans less valuable to the $400 billion industry that produces feed for cattle, pigs, chickens and fish. And the problem is a key factor driving soybean buyers from the U.S. to Brazil, where warmer weather helps offset the impact of higher crop yields on protein levels....

Soybeans are by far the most valuable U.S. agricultural export, with $22.8 billion in shipments in 2016. Declining protein levels and market share pose another vexing problem for soy farmers already reeling from a global grains glut and years of depressed prices.

The quality problems of U.S. soybean producers go beyond that however. In their race to export as many soybeans as they could to China in 2016, they also got sloppy in their harvesting and processing practices, where an excessive amount of foreign material was being included within the industry's soybean shipments.

China's response to that problem was to impose stricter import specifications on U.S. soybean exports at the end of 2017, which is expected to negatively impact up to 50% of the nation's soybean exports in 2018. That impact will come in the form of higher costs for U.S. soybean producers, who will have to take steps to reduce the amount of non-soybean material that will be shipped to China.

Half of U.S. soybeans exported to China this year would not meet Chinese rules for routine delivery in 2018, according to shipping data reviewed by Reuters, signaling new hurdles in the $14-billion-a-year business.

More stringent quality rules, which take effect on Jan. 1, could require additional processing of the U.S. oilseeds at Chinese ports to remove impurities. This could raise costs and reduce sales to the world’s largest soybean importer, according to U.S. farmers and traders.

Half of the 473 vessel shipments in 2017 and half the total 27.5 million tonnes of U.S. soybeans exported to China this year contained more than 1 percent of foreign material, exceeding a new standard for speedy delivery, according to U.S. Department of Agriculture (USDA) data compiled by grain broker McDonald Pelz Global Commodities LLC.

In the short run, the choice to sacrifice quality to pursue additional revenue and higher profits made a lot of sense to U.S. soybean producers. In the long run, that choice could very well leave them worse off than if they hadn't taken that path. What choice would you have made in 2016 if you were playing the soybean export game?

Cut from the Same Psychological Cloth

"Scientific misconduct and sexual assault have more in common than you might think."

That's UCLA's Michael Chwe's provocative introduction to an April 2016 article at Retraction Watch, in which he explored a number of predatory behaviors that appear to be disturbingly common among both alleged junk scientists and individuals engaged in sexual harrassment.

For starters, in both scientific misconduct cases and sexual assault or sexual harassment cases, typically a weak person accuses a powerful person. The accused is usually much closer to administrators and the investigative system: the first administrator to confront Diederik Stapel with charges that he had faked his data played tennis with Stapel every Wednesday, and told him that he would “like nothing better” than to believe in Stapel’s innocence. After an investigation found that Sujit Choudhry, dean of the UC Berkeley Law School, sexually harassed executive assistant Tyann Sorrell, UC Berkeley Provost Claude Steele told Sorrell that he would not fire Choudhry because it might “destroy his future chances for higher appointment.”

In contrast, people who report scientific fraud and sexual assault and harassment typically do not have powerful friends, and decide to report at great personal cost. The students of Elizabeth Goodwin abandoned many years of graduate school study in order to report that Goodwin had faked data. As Sarah LaMartina told Science in 2006:

We kept thinking, ‘Are we just stupid [to turn Goodwin in]?’ . . . Sure, it’s the right thing to do, but right for who? . . . Who is going to benefit from this? Nobody.

LaMartina lost her appetite and fifteen pounds, while faculty members in the department all supported Goodwin. Similarly, sexual assault is one of the least reported crimes: In a 2015 survey of 23,000 college students, only 12.5 percent of rape incidents and 4.3 percent of sexual battery incidents experienced by women were reported to authorities. People reporting sexual assault face the possibility of violent reprisals, not being believed by authorities, and even being blamed for the assault.

A particularly insidious dynamic in both scientific fraud and sexual assault and harassment is that people who report it are made to feel that they themselves are implicated in the offense. In a 2006 survey published in the Journal of Interpersonal Violence, the vast majority of women who were raped did not report to authorities; the most common reason they provided (63 percent) was that they themselves would be blamed for the assault. Similarly, as pointed out in a 2010 editorial by the journal Nature:

A young scientist’s reputation is tethered to the successes and failures of his or her adviser, and when that adviser is accused of misconduct, trainees can also be viewed with suspicion.

Even for an established scientist, accusing another of fraud can be very costly. In her book about Jan Hendrik Schön, Eugenie Samuel Reich writes:

A whistleblower of scientific fraud once told me that he felt he needed the right to remain anonymous for the rest of his life. “Like a rape victim,” he said. . . . Thinking of a fraud allegation as if it were an allegation of sexual abuse, I could start to understand on an instinctive level why scientists might feel strongly and yet be very fearful about coming forward.

One of the things that stands out immediately is the extent to which the individuals who engaged in scientific misconduct exploited their personal connections and positions of authority to relentlessly attempt to denigrate the reputations and well-being of the whistleblowers who came forward to challenge their reigns of personal abuse.

Beyond that, it is very interesting to consider the behavioral similarities and parallels between those called out for having engaged in junk science prior to those being called out in today's scandal-ridden headlines involving the power-elite of both Hollywood and Washington D.C. Especially when those stories involve the unethical and systematic actions taken by the abusive personalities against the people who were willing to blow the whistle against their misconduct.

Consider the multiple stories that have come to light involving the recently convicted USA Gymnastics doctor Larry Nassar or of Hollywood's Harvey Weinstein, the latter of whom reports indicate had his own personal "enemies list" of people he targeted for special and ongoing abuse.

The Observer has gained access to a secret hitlist of almost 100 prominent individuals targeted by Harvey Weinstein in an extraordinary attempt to discover what they knew about sexual misconduct claims against him and whether they were intending to go public.

The previously undisclosed list contains a total of 91 actors, publicists, producers, financiers and others working in the film industry, all of whom Weinstein allegedly identified as part of a strategy to prevent accusers from going public with sexual misconduct claims against him.

The names, apparently drawn up by Weinstein himself, were distributed to a team hired by the film producer to suppress claims that he had sexually harassed or assaulted numerous women.

The document was compiled in early 2017, around nine months before the storm that blew up on 5 October when the New York Times published a series of sexual harassment allegations against Weinstein.

Weinstein's enemies list was used to support the gathering of damaging information on his alleged victims and potential whistleblowers, which in turn, was planned to be used to both distract attention away from and to discredit any statements they might make about his personal conduct, to wreck their professional and personal reputations for the purpose of damaging their career prospects as a means to punish them for standing up to him, and to send a message to others about what might happen to them if they ever went public with allegations of misconduct on his part.

What kind of person is like that?

What kind of person engages in serial episodes of misconduct, whether it be cooking data to obtain predetermined results or engaging in acts of sexual harrassment or assault, then puts together an enemies list to facilitate their ability to further demean and diminish or to stalk and terrorize the targets of their personal abuse?

In our Examples of Junk Science series, we paid special attention to the kind of personality traits that characterized the unethical and ultimately antisocial and toxic behaviors that were common among confirmed pseudoscientists. As a hypothesis, we think that many of these are the same traits and characteristics associated with having a narcissistic personality disorder, which is indicated by their having five or more of the following symptoms of the spectrum condition:

  • Exaggerates own importance
  • Is preoccupied with fantasies of success, power, beauty, intelligence or ideal romance
  • Believes he or she is special and can only be understood by other special people or institutions
  • Requires constant attention and admiration from others
  • Has unreasonable expectations of favorable treatment
  • Takes advantage of others to reach his or her own goals
  • Disregards the feelings of others, lacks empathy
  • Is often envious of others or believes other people are envious of him or her
  • Shows arrogant behaviors and attitudes
Psychology Today drills down deeper into each of these symptoms to provide more insight into how each might manifest itself (highly recommended reading, particularly if you ever have to deal with such a person and their abnormal behavior with any regularity).

Dealing with such a personality however can be an especially difficult challenge, because often, their go-to strategy to get away with their misconduct involves launching an unending smear campaign or other forms of social menacing against those who either have or who might expose their misconduct.

Most smear campaigners are highly narcissistic, and narcissists cannot ever be expected to apologize, come clean or admit any wrongdoing, even if caught red-handed in their lies. They truly believe, in their own way, that a smear campaign is the right thing to do to you, because you have opposed them, and you should have known better than to do such an unthinkable thing, so it’s simply all your fault they’re smearing you anyhow. They’re teaching you a lesson — agree with whatever they want, or else. You “asked for it”, and they’re teaching you better.

Smear campaigners are like spoiled playground bullies who kick another child when the teacher’s back is turned, just because the child doesn’t give them whatever they want. They cannot be made to empathize, and they are well-practiced in their abusive games, because they have been playing them all their lives.

In the quoted passage above, we've emphasized the first sentence with red boldface font because it largely agrees with the kind of behavior that we've observed on the part of several of the pseudo-scientists whose egregious academic misdeeds were referenced during our Examples of Junk Science series back in 2016, where they have not acknowledged the serious deficiencies that led to their work being dismissed as little more than junk science in the first place.

In place of that, we've often seen really unprofessional behaviors involving anything from simple namecalling on through to prolonged smear campaigns directed at their perceived enemies with the apparent intent of damaging their credibility, where new frenzies of smears often seem prompted by little more than the most minor of offenses that only they perceive.

How do you deal with that if you're on the receiving end of that kind of personal abuse?

Throughout this article, we've used the term "enemies list" rather than "hit list" because it harkens back to the days of Richard Nixon, whose paranoia drove the biggest political corruption scandal in the U.S. during the twentieth century, or more importantly, of Joseph McCarthy, whose enemies list had greater impact and whose name has become synonymous with unethically-inspired smear campaigns, thanks to what has been described as his "driven, sanctimonious, dogmatic behaviors that are hallmarks of narcissism with an authority attachment". Sadly, in our experience, the twenty-first century's pseudoscientists and sexual harassers would very much appear to be cut from the same psychological cloth, so if you ever come across someone who has a similar enemies list that they're so worked up about that they're acting out on it by engaging in a smear campaign, you'll have a pretty good idea of what to expect from that kind of personality.

Amy Tuteur, a critic and target of the pseudoscience anti-vax movement, has a unique perspective of what it means to make the enemies list of such people, which we've excerpted the following two points below (she makes a third point that's more specific to what she's encountered with the anti-vax "movement", but the following two points are applicable much more generally):

  • An enemies list is an implicit acknowledgement that the facts are not on their side.
  • The purpose of the list is to preemptively exclude list members from the echo chambers that are so vital to the propagation of pseudoscience.

We would suggest following a strategy that we hope would be an improvement on how Dwight Eisenhower dealt with Joe McCarthy's similarly unethical and unprofessional behavior, where ultimately, the narcissistic and paranoid McCarthy destroyed his own credibility with his obsessive conduct, which he either could not or would not constrain. Given sufficient time, the narcissistic pseudo-scientist or sexual harasser will publicly hang themselves with the rope from what is most often their own one-way campaign of abuse, where all you need to do as a target is to hang tough and act behind the scenes to limit the damage they might do as much as possible until that happens (Eisenhower's approach to the politically-powerful McCarthy), while making their ongoing unethical conduct as visible as possible to as many people as possible (the improvement), which makes it happen faster.

Whether they be pseudo-scientists or sexual harrassers, when the narcissistic misconduct and targeted abuse in which they've engaged becomes widely known - when everybody knows - is when the end is near for them. When all can see what they're doing and what they've done, and when no one sees them or their conduct as anything other than contemptible, is when they lose whatever power they had to intimidate others to get away with their misconduct without consequences.

Just follow the stories of the falls of Harvey Weinstein or of Joseph McCarthy to see how that works.

Harvey Weinstein / Joseph McCarthy

Image credits: New York City Media and Library of Congress.

Postscript

Today (9 February 2018) is the 68th anniversary of the date that Senator Joseph McCarthy launched his "Red Scare" campaign. Coincidentally, 9 February 2018 marks the date that the Los Angeles Police Department referred three cases of sexual abuse allegedly involving Harvey Weinstein to the Los Angeles District Attorney. We had originally planned to present this post as our only Friday feature, but bumped it since we've been focusing on covering the turmoil in the U.S. stock market this past week.

Honesty as a Path for Avoiding Failure

When a scientist realizes that they've made a fundamental error in their research that has the potential to invalidate their findings, they are often confronted with an ethical dilemma in determining what course of action that they might take to address the situation. Richard Mann, a young researcher from Uppsala University, lived through that scenario back in 2012, when a colleague contacted him right before he presented a lecture based on the results of his research that he had a problem that called his results into question.

When he gave his seminar, Mann marked the slides displaying his questionable results with the words "caution, possibly invalid". But he was still not convinced that a full retraction of his paper, published in Plos Computational Biology, was necessary, and he spent the next few weeks debating whether he could simply correct his mistake with a new analysis rather than retract the paper.

But after about a month, he came to see that a full retraction was the better option as it was going to take him at least six months to wade through the mess that the faulty analysis had created. However, it had occurred to him that there was a third option: to keep quiet about his mistake and hope that no one noticed it.

After numerous sleepless nights grappling with the ethics of such silence, he eventually plumped for retraction. And looking back, it is easy to say that he made the right choice, he remarks. "But I would be amazed if people in that situation genuinely do not have thoughts about [keeping quiet]. I had first, second and third thoughts." It was his longing to be able to sleep properly again that convinced him to stay on the ethical path, he adds.

Mann's case represents a success story for ethics in science, where his choices to demonstrate personal integrity and to provide transparency regarding the errors he had made through the retraction of his work proved to have no impact on his professional career, though he may have feared it. Such are the rewards of integrity and transparency in science, where the honest pursuit of truth outweighs both personal reputation and professional standing.

Still, an 2017 anonymous straw poll of 220 scientists indicated that 5% would choose to do nothing if they detected an error in their own work after it had been published in a high-impact journal, where they would hope that none of their peers would ever notice, while another 9% would only retract a paper if another researcher had specifically identified their error.

According to Nature, only a tiny fraction of published papers are ever retracted, even though a considerably higher percentage of scientists have admitted to knowing of issues that would potentially invalidate their published results in confidential surveys.

The reasons behind the rise in retractions are still unclear. "I don't think that there is suddenly a boom in the production of fraudulent or erroneous work," says John Ioannidis, a professor of health policy at Stanford University School of Medicine in California, who has spent much of his career tracking how medical science produces flawed results.

In surveys, around 1–2% of scientists admit to having fabricated, falsified or modified data or results at least once (D. Fanelli PLoS ONE 4, e5738; 2009). But over the past decade, retraction notices for published papers have increased from 0.001% of the total to only about 0.02%. And, Ioannidis says, that subset of papers is "the tip of the iceberg" — too small and fragmentary for any useful conclusions to be drawn about the overall rates of sloppiness or misconduct.

There is, of course, a difference between errors resulting from what Ioannidis calles "sloppiness", which can run the gamut from data measurement errors to the use of less-than-optimal analytical methods, which can all happen to honest researchers, and those that get baked into research findings through knowing misconduct.

The good news is that for honest scientists who act to disclose errors in their work, there is no career penalty. And why should there be? They are making science work the way that it should, where they are contributing to the advancement of their field where the communication of what works and what doesn't work has value. As serial entrepreneur James Altucher has said, "honesty is the fastest way to prevent a mistake from turning into a failure."

The bigger problem is posed by those individuals who put other goals ahead of honesty. The ones who choose to remain silent when they know their findings will fail to stand up to serious scrutiny. Or worse, the ones who choose to engage in irrational, hateful attacks against the individuals who detect and report their scientific misconduct as a means to distract attention away from it, which is another form of refusing to acknowledge the errors in their work.

The latter population are known as pseudoscientists. Fortunately, they're a very small minority, but unfortunately, they create outsized problems within their fields of study, where they can continue to do damage until they're exposed and isolated.

Previously on Political Calculations