Why Scientists Should Stop Misusing Science To Influence The Election


Earlier this month, the editors of Scientific American, published an all-out, endorsement of Joe Biden for President—something unprecedented in the journal’s 175 year history. Then, last week, all of the New England Journal of Medicine’s editors signed a scathing review of the Trump administration’s handling of the COVID-19 emergency, calling for Trump to be voted out of office.

In truth, both editorials offer several valid criticisms of the administration on scientific grounds. And to be clear: The present article is not making any counter-endorsement of Donald Trump—far from it.

Rather, we pose an important question: Are high-profile scientists crossing a dangerous line by using their trusted platforms to influence the election? Based on behavioral science, we believe they are and their actions come at the risk of diminishing the public’s trust in scientific objectivity.

Indeed, their political suasion efforts might even backfire.

A long literature in behavioral research suggests people place more credence on arguments or statements said to be supported by science. In that connection, scientists are exalted by the public and even given extra validity when their listeners are under stress or in a state of fear.

To make matters more complicated, a pervasive cognitive bias known as the halo effect suggests people often assume highly regarded figures (such as scientists) possess expertise in areas where they don’t.

The net effect of such biases and perceptions is that scientists are often given undo public trust; yet, in places where a scientists’s assertions are preliminary, inconclusive or outright wrong, the public follows their lead, nonetheless.

The problem is that scientists are often wrong.

In fact, a long-term study indicates that over 70% of scientists are unable to replicate the results of

Johnson has ignored the science and blown our chance to stop a second wave


We shouldn’t be here. Back in June, England had the opportunity to suppress the virus. With a functional test and trace system, support to help people self-isolate, a robust set of regulations to keep work and leisure spaces safe and a clear public communications campaign, we could have suppressed coronavirus into the winter.

Boris Johnson in a suit and tie: Photograph: Toby Melville/AFP/Getty Images

© Provided by The Guardian
Photograph: Toby Melville/AFP/Getty Images

But the opportunity was squandered. Worse, as restrictions were lifted on 4 July – what became known colloquially as “Freedom Saturday” – we were encouraged to relax, to travel back to work, to go to the pub, to mix and mingle. Meanwhile, the country’s dysfunctional, centralised and privately-run test and trace system lurched from one calamity to the next. World class? At failing to contact people and succeeding in losing data, perhaps.

The virus never went away. In some deprived communities, such as Bolton and Rochdale, infections remained endemic. As the summer faded we moved indoors, and schools and then universities returned. Infections began to rise again, slowly at first, but then faster and faster. The signs were unmistakable. If the government did nothing, England would be back to a similar number of cases that we saw in March, and the death rate would begin to climb again. The NHS would be overwhelmed.

On 21 September the scientific advisory body Sage produced a paper with a simple message: do something now or else lose control over the virus. That “something” would have to be sufficient to reduce infections to a level where the virus could be controlled without shutting businesses and curtailing livelihoods. At a minimum, that would mean restricting social mixing, closing pubs, offering university classes online and working from home.

On the day that advice was given, there were 4,696 infections across the UK. The government

Science Says Stop Infecting Other People With the ‘Better-Than-Average’ Effect


You’re probably familiar with the famous survey where more than 80 percent of respondents said they were above-average drivers, even though that’s mathematically impossible. And even though all of the respondents had, at some point in their lives, been injured in car accidents. (In fact, another study found that less than 1 percent of respondents considered themselves “worse than average.”)

Findings like that are easy to laugh at… until you realize that most people think they’re above-average at almost everything. A meta-analysis of a number of studies shows that people rate themselves as above average in creativity, intelligence, dependability, athleticism, honesty, friendless… provide people with a survey about almost any trait and teh vast majority will rate themselves as above average.

Social psychologists call it the “better-than-average effect.” Ask me to rate myself — in anything — in terms of basically anything, and I’ll be convinced I’m above average. (Even though I’m clearly not.)

Granted, a little confidence is a good thing, as long as that self-belief is based on actual achievements, actual experiences, and actual results. Belief based on evidence is confidence.

Belief based on nothing but belief is arrogance — and unfortunately, arrogance is infectious.

In a study published earlier this year in the Journal of Experimental Psychology, researchers conducted two experiments. In the first, participants were asked to look at photos of faces and guess the individual’s personalities based on their facial expressions. Then they were asked to rate how well they did compared to the rest of the participants. (Basically, the “better-than-average” question.)

Then participants were placed in pairs and asked to perform the same task. 

Here’s the interesting part: When a relatively humble participant — someone who had rated themselves relatively poorly compared to the other participants after the first experiment — was paired

Virginia Tech helpless to stop North Carolina in first loss of the 2020 season |


Virginia Tech vs. UNC Chapel Hill, N.C.


Virginia Tech 0 14 23 8 — 45

North Carolina 21 14 7 14 — 56

First Quarter

NC—Williams 1 run (Atkins kick), 10:22.

NC—D.Brown 37 pass from Howell (Atkins kick), 7:52.

NC—Williams 19 run (Atkins kick), 4:09.

Second Quarter

VT—Mitchell 1 run (B.Johnson kick), 14:13.

VT—Herbert 8 run (B.Johnson kick), 6:28.

NC—Newsome 6 run (Atkins kick), 4:17.

NC—D.Brown 43 pass from Howell (Atkins kick), :16.

Third Quarter

VT—FG B.Johnson 55, 9:55.

NC—Carter 16 run (Atkins kick), 7:14.

VT—Hooker 5 run (B.Johnson kick), 5:58.

VT—Herbert 52 run (B.Johnson kick), 5:04.

VT—T.Robinson 33 pass from Hooker (run failed), :15.

Fourth Quarter

NC—Newsome 12 pass from Howell (Atkins kick), 12:37.

NC—Carter 62 run (Atkins kick), 8:49.

VT—Mitchell 26 pass from Hooker (Hooker run), 5:20.





First downs 25 31

Rushes-yards 48-260 43-399

Passing 235 257

Comp-Att-Int 15-29-0 18-23-0

Return Yards 53 22

Punts-Avg. 4-47.2 3-45.0

Fumbles-Lost 0-0 0-0

Penalties-Yards 4-26 10-87

Time of Possession 32:06 27:54



RUSHING—Virginia Tech, Herbert 18-138, Burmeister 11-51, Blackshear 8-33, Hooker 8-29, Holston 1-12, Mitchell 1-1, (Team) 1-(minus 4). North Carolina, Carter 17-214, Williams 20-169, Howell 3-19, Newsome 1-6, (Team) 2-(minus 9).

PASSING—Virginia Tech, Burmeister 7-15-0-79, T.Robinson 1-1-0-20, Hooker 7-13-0-136. North Carolina, Howell 18-23-0-257.

RECEIVING—Virginia Tech, Mitchell 4-103, T.Robinson 4-45, Blackshear 3-1, Turner 2-51, Hooker 1-20, Gallo 1-15. North Carolina, Newsome 7-69, D.Brown 3-86, Williams 3-55, Corrales 2-15, Carter 1-15, K.Brown 1-10, Walston 1-7.



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Virginia Tech helpless to stop North Carolina in first loss of the 2020 season | Virginia Tech


Running back Khalil Herbert made his presence felt in the quarter as well with a 52-yard touchdown run. Herbert converted the third and eight by weaving his way through the secondary to go over 100-yards for the third straight game.

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The Hokies held onto the ball for nearly 11 minutes in the third quarter, but still couldn’t overcome the 21 points they spotted UNC in the first quarter. 

North Carolina went straight down the field on their first three possessions to take a 21-0 lead while averaging 9.7 yards per play.

Howell was near perfect in the quarter going 10 of 12 for 123 yards with a 37-yard touchdown pass to Brown. Brown, who beat Tech cornerback Armani Chatman down the field, was able to get one foot down at the back of the end zone for the score.

Williams ran for two scores in the quarter.

Tech’s defense forced a pair of three-and-outs in the second quarter — Dorian Strong broke up a third down pass to force UNC’s first punt of the game and Amare Barno came up with a third down sack — but the Tar Heels weren’t done.

Howell connected again with Brown right before the end of the first half on a 43-yard throw to push North Carolina’s lead back up to 21 points.

Tech’s already short-handed secondary suffered a blow in the first quarter when nickel Chamarri Conner was ejected for targeting. The Hokies’ starting safeties Divine Deablo and Keonta Jenkins were among the 15 players that didn’t travel to the game. Nadir Thompson, who started last week at cornerback, came in for Conner.

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