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**True, sadly. Probably more or less catastrophic depending on context - situation, supports, “resiliency”, etc.
But we’ve seen this coming for months, in major U.S. cities, definitely.
Stay safe. Listen to science & health experts. Hang in there… sanity and vaccines are on the horizon.***

*One or both
Newsweek: Students May Not Survive COVID Lockdown Without Urgent Mental Health Support

#copingwithCovid #coronavirus #college #COVID19 #stress #education #StaySafe #MentalHealth #psychology
 
**True, sadly. Probably more or less catastrophic depending on context - situation, supports, “resiliency”, etc.
But we’ve seen this coming for months, in major U.S. cities, definitely.
Stay safe. Listen to science & health experts. Hang in there… sanity and vaccines are on the horizon.***

*One or both
Newsweek: Students May Not Survive COVID Lockdown Without Urgent Mental Health Support

#copingwithCovid #coronavirus #college #COVID19 #stress #education #StaySafe #MentalHealth #psychology
 
This is awesome research and worth reading the entire summary (in my opinion.)
reshare from @Wayne Radinsky

“When adults and 4- to 5-year-old children played a game where certain choices earned them rewards, both adults and children quickly learned what choices would give them the biggest returns. But while adults then used that knowledge to maximize their prizes, children continued exploring the other options, just to see if their value may have changed.”

Ah, this is known as the “explore-exploit” problem in computer science. I’ve read that mathematicians have analyzed simple models of it and found that the optimal solution depends on the time remaining. To use a “restaurant” analogy, suppose you are visiting a city and are going out to eat every night. Should you go to a new restaurant or go to the best you have visited so far? The answer is, if it’s your last night, you should go to the best you’ve been to so far – exploit the knowledge that you have for maximum reward. (We are assuming maximum reward, defined as the best tasting food, is the goal here.). But if you have weeks or months ahead of you, you should go to a new restaurant. At some point, the balance will tip and you will reap the best rewards by going to the best restaurant over and over before your time runs out. I don’t recall the math for working out the exact optimal solution but I remember it’s really complicated. Nowadays people make AI agents, in particular reinforcement learning agents, that learn the optimal explore-exploit strategy for a given environment, without it being directly solved mathematically.

Anyway, what’s interesting is that children seem oriented towards exploration, while adults seem oriented towards exploitation, as if humans have some innate sense of “time left” and “knowledge gained so far” and what is the optimal strategy.

“And despite what adults may think, kids’ search for new discoveries is anything but random. Results showed children approached exploration systematically, to make sure they didn’t miss anything.”

“The researchers conducted two studies. One study involved 32 4-year-olds and 34 adults. On a computer screen, participants were shown four alien creatures. When participants clicked on each creature, they were given a set number of virtual candies. One creature was clearly the best, giving 10 candies, while the others gave 1, 2 and 3 candies, respectively. Those amounts never changed for each creature over the course of the experiment.”

In the computer science models I’ve read about, they simulated armed bandits. This is the same thing except replace bandits with “aliens” and money with “virtual candies.”

“The goal was to earn as much candy as possible over 100 trials. (The children could turn their virtual candies into real stickers at the end of the experiment.)”

“As expected, the adults learned quickly which creature gave the most candies and selected that creature 86 percent of the time. But children selected the highest-reward creature only 43 percent of the time.”

“And it wasn’t because the children didn’t realize which choice would reap them the largest reward. In a memory test after the study, 20 of 22 children correctly identified which creature delivered the most candy.”

“When they didn’t click on the option with the highest reward, they were most likely to go through the other choices systematically, to ensure they never went too long without testing each individual choice.”

“In a second study, the game was similar but the value of three of the four choices was visible – only one was hidden. The option that was hidden was randomly determined in each trial, so it changed nearly every time. But the values of all four choices never changed, even when it was the hidden one.”

“Like in the first experiment, the 37 adults chose the best option on almost every trial, 94 percent of the time. That was much more than the 36 4- and 5-year-old children, who selected the highest-value option only 40 percent of the time.”

“When the hidden option was the highest-value option, adults chose it 84 percent of the time, but otherwise they almost never selected it (2 percent of the time).”

“Children chose the hidden option about 40 percent of the time – and it didn’t matter if it was the highest value one or not.”

Young children would rather explore than get rewards

#discoveries #psychology #exploreexploit
 
This is awesome research and worth reading the entire summary (in my opinion.)
reshare from @Wayne Radinsky

“When adults and 4- to 5-year-old children played a game where certain choices earned them rewards, both adults and children quickly learned what choices would give them the biggest returns. But while adults then used that knowledge to maximize their prizes, children continued exploring the other options, just to see if their value may have changed.”

Ah, this is known as the “explore-exploit” problem in computer science. I’ve read that mathematicians have analyzed simple models of it and found that the optimal solution depends on the time remaining. To use a “restaurant” analogy, suppose you are visiting a city and are going out to eat every night. Should you go to a new restaurant or go to the best you have visited so far? The answer is, if it’s your last night, you should go to the best you’ve been to so far – exploit the knowledge that you have for maximum reward. (We are assuming maximum reward, defined as the best tasting food, is the goal here.). But if you have weeks or months ahead of you, you should go to a new restaurant. At some point, the balance will tip and you will reap the best rewards by going to the best restaurant over and over before your time runs out. I don’t recall the math for working out the exact optimal solution but I remember it’s really complicated. Nowadays people make AI agents, in particular reinforcement learning agents, that learn the optimal explore-exploit strategy for a given environment, without it being directly solved mathematically.

Anyway, what’s interesting is that children seem oriented towards exploration, while adults seem oriented towards exploitation, as if humans have some innate sense of “time left” and “knowledge gained so far” and what is the optimal strategy.

“And despite what adults may think, kids’ search for new discoveries is anything but random. Results showed children approached exploration systematically, to make sure they didn’t miss anything.”

“The researchers conducted two studies. One study involved 32 4-year-olds and 34 adults. On a computer screen, participants were shown four alien creatures. When participants clicked on each creature, they were given a set number of virtual candies. One creature was clearly the best, giving 10 candies, while the others gave 1, 2 and 3 candies, respectively. Those amounts never changed for each creature over the course of the experiment.”

In the computer science models I’ve read about, they simulated armed bandits. This is the same thing except replace bandits with “aliens” and money with “virtual candies.”

“The goal was to earn as much candy as possible over 100 trials. (The children could turn their virtual candies into real stickers at the end of the experiment.)”

“As expected, the adults learned quickly which creature gave the most candies and selected that creature 86 percent of the time. But children selected the highest-reward creature only 43 percent of the time.”

“And it wasn’t because the children didn’t realize which choice would reap them the largest reward. In a memory test after the study, 20 of 22 children correctly identified which creature delivered the most candy.”

“When they didn’t click on the option with the highest reward, they were most likely to go through the other choices systematically, to ensure they never went too long without testing each individual choice.”

“In a second study, the game was similar but the value of three of the four choices was visible – only one was hidden. The option that was hidden was randomly determined in each trial, so it changed nearly every time. But the values of all four choices never changed, even when it was the hidden one.”

“Like in the first experiment, the 37 adults chose the best option on almost every trial, 94 percent of the time. That was much more than the 36 4- and 5-year-old children, who selected the highest-value option only 40 percent of the time.”

“When the hidden option was the highest-value option, adults chose it 84 percent of the time, but otherwise they almost never selected it (2 percent of the time).”

“Children chose the hidden option about 40 percent of the time – and it didn’t matter if it was the highest value one or not.”

Young children would rather explore than get rewards

#discoveries #psychology #exploreexploit
 
"When adults and 4- to 5-year-old children played a game where certain choices earned them rewards, both adults and children quickly learned what choices would give them the biggest returns. But while adults then used that knowledge to maximize their prizes, children continued exploring the other options, just to see if their value may have changed."

Ah, this is known as the "explore-exploit" problem in computer science. I've read that mathematicians have analyzed simple models of it and found that the optimal solution depends on the time remaining. To use a "restaurant" analogy, suppose you are visiting a city and are going out to eat every night. Should you go to a new restaurant or go to the best you have visited so far? The answer is, if it's your last night, you should go to the best you've been to so far -- exploit the knowledge that you have for maximum reward. (We are assuming maximum reward, defined as the best tasting food, is the goal here.). But if you have weeks or months ahead of you, you should go to a new restaurant. At some point, the balance will tip and you will reap the best rewards by going to the best restaurant over and over before your time runs out. I don't recall the math for working out the exact optimal solution but I remember it's really complicated. Nowadays people make AI agents, in particular reinforcement learning agents, that learn the optimal explore-exploit strategy for a given environment, without it being directly solved mathematically.

Anyway, what's interesting is that children seem oriented towards exploration, while adults seem oriented towards exploitation, as if humans have some innate sense of "time left" and "knowledge gained so far" and what is the optimal strategy.

"And despite what adults may think, kids' search for new discoveries is anything but random. Results showed children approached exploration systematically, to make sure they didn't miss anything."

"The researchers conducted two studies. One study involved 32 4-year-olds and 34 adults. On a computer screen, participants were shown four alien creatures. When participants clicked on each creature, they were given a set number of virtual candies. One creature was clearly the best, giving 10 candies, while the others gave 1, 2 and 3 candies, respectively. Those amounts never changed for each creature over the course of the experiment."

In the computer science models I've read about, they simulated armed bandits. This is the same thing except replace bandits with "aliens" and money with "virtual candies."

"The goal was to earn as much candy as possible over 100 trials. (The children could turn their virtual candies into real stickers at the end of the experiment.)"

"As expected, the adults learned quickly which creature gave the most candies and selected that creature 86 percent of the time. But children selected the highest-reward creature only 43 percent of the time."

"And it wasn't because the children didn't realize which choice would reap them the largest reward. In a memory test after the study, 20 of 22 children correctly identified which creature delivered the most candy."

"When they didn't click on the option with the highest reward, they were most likely to go through the other choices systematically, to ensure they never went too long without testing each individual choice."

"In a second study, the game was similar but the value of three of the four choices was visible -- only one was hidden. The option that was hidden was randomly determined in each trial, so it changed nearly every time. But the values of all four choices never changed, even when it was the hidden one."

"Like in the first experiment, the 37 adults chose the best option on almost every trial, 94 percent of the time. That was much more than the 36 4- and 5-year-old children, who selected the highest-value option only 40 percent of the time."

"When the hidden option was the highest-value option, adults chose it 84 percent of the time, but otherwise they almost never selected it (2 percent of the time)."

"Children chose the hidden option about 40 percent of the time -- and it didn't matter if it was the highest value one or not."

Young children would rather explore than get rewards

#discoveries #psychology #exploreexploit
 
#Newhere all the way from a smokey town called Arbroath.

Once I learn how to drive this thing I will be posting about #philosophy #Science #history #psychology #Logic . I'm no expert on any these subjects, still very much a beginner, although, I like to think of myself as an advanced beginner.

My main interest is #philosophy. Over the past few years I've been reading the history and evolution of #GreekPhilosophy - #ModernPhilosophy - especially #ImmanuelKant and #DavidHume - #ScottishPhilosophy and #TheScottishEnlightenment.

So these are the kind of subjects I will be posting about, along with some #Art #Music and a shit sense of #humour.

Thanks for having me 😀
 
#Newhere all the way from a smokey town called Arbroath.

Once I learn how to drive this thing I will be posting about #philosophy #Science #history #psychology #Logic . I'm no expert on any these subjects, still very much a beginner, although, I like to think of myself as an advanced beginner.

My main interest is #philosophy. Over the past few years I've been reading the history and evolution of #GreekPhilosophy - #ModernPhilosophy - especially #ImmanuelKant and #DavidHume - #ScottishPhilosophy and #TheScottishEnlightenment.

So these are the kind of subjects I will be posting about, along with some #Art #Music and a shit sense of #humour.

Thanks for having me 😀
 
Introverts like mountains while extroverts like the flatlands, according to this research that graphs out flatness and extroversion by state and shows a relationship. Also they say extroverts like beaches while introverts like mountains.

I'm half-n-half -- neither introvert nor extrovert. (Apparently there's a word for this: "ambivert".) I land in the middle on the "introvert-extrovert" scale on Big 5 and Myers-Briggs personality tests, and it seem to fit as I can be by myself for hours and I don't mind and I can be with other people for hours and that's fine, too.

Having said that, the flatlands vs mountains theory is new to me and makes no sense. It seems like, some people, like my mom, like the "big sky" feeling that you get in a place that's very flat. Others like the scenic feeling from mountains. When you get very high up the scenery becomes quite dramatic.

My mom grew up in west Texas and I've been there many times to visit my grandparents and it is the flattest place I've ever been. The graph shows North Dakota as the flattest state, and I guess the problem here is they're using whole states and some like Texas are pretty big. Texas has some hills on it's eastern side where it borders Louisiana. But on the western side, well, I've been to both North Dakota and west Texas and I can tell you west Texas is flatter.

I live in Denver and maybe Denver is the perfect place for the half-n-half ambiverts who are neither introvert nor extrovert, but something in the middle. Look east, and you're on the flatlands. Look west and you're in the mountains.

Extroverts Prefer Plains, Introverts Like Mountains

#discoveries #psychology #personality
 
Introverts like mountains while extroverts like the flatlands, according to this research that graphs out flatness and extroversion by state and shows a relationship. Also they say extroverts like beaches while introverts like mountains.

I'm half-n-half -- neither introvert nor extrovert. (Apparently there's a word for this: "ambivert".) I land in the middle on the "introvert-extrovert" scale on Big 5 and Myers-Briggs personality tests, and it seem to fit as I can be by myself for hours and I don't mind and I can be with other people for hours and that's fine, too.

Having said that, the flatlands vs mountains theory is new to me and makes no sense. It seems like, some people, like my mom, like the "big sky" feeling that you get in a place that's very flat. Others like the scenic feeling from mountains. When you get very high up the scenery becomes quite dramatic.

My mom grew up in west Texas and I've been there many times to visit my grandparents and it is the flattest place I've ever been. The graph shows North Dakota as the flattest state, and I guess the problem here is they're using whole states and some like Texas are pretty big. Texas has some hills on it's eastern side where it borders Louisiana. But on the western side, well, I've been to both North Dakota and west Texas and I can tell you west Texas is flatter.

I live in Denver and maybe Denver is the perfect place for the half-n-half ambiverts who are neither introvert nor extrovert, but something in the middle. Look east, and you're on the flatlands. Look west and you're in the mountains.

Extroverts Prefer Plains, Introverts Like Mountains

#discoveries #psychology #personality
 

What’s next for psychology’s embattled field of social priming


TL;DR: It's still faking statistics and searching for ridiculous correlations.

#statistics #psychology
 
#psychology #bystander #debunk

How Often Will Bystanders Help Strangers in Need? - CityLab



It’s one of the most enduring urban myths of all: If you get in trouble, don’t count on anyone nearby to help. Research dating back to the late 1960s documents how the great majority of people who witness crimes or violent behavior refuse to intervene.

Psychologists dubbed this non-response as the “bystander effect”—a phenomenon which has been replicated in scores of subsequent psychological studies. The “bystander effect” holds that the reason people don’t intervene is because we look to one another. The presence of many bystanders diffuses our own sense of personal responsibility, leading people to essentially do nothing and wait for someone else to jump in.
[…]
The study finds that in nine out of 10 incidents, at least one bystander intervened, with an average of 3.8 interveners. There was also no significant difference across the three countries and cities, even though they differ greatly in levels of crime and violence.

Instead of more bystanders creating an immobilizing “bystander effect,” the study actually found the more bystanders there were, the more likely it was that at least someone would intervene to help.
 
#psychology #bystander #debunk

How Often Will Bystanders Help Strangers in Need? - CityLab



It’s one of the most enduring urban myths of all: If you get in trouble, don’t count on anyone nearby to help. Research dating back to the late 1960s documents how the great majority of people who witness crimes or violent behavior refuse to intervene.

Psychologists dubbed this non-response as the “bystander effect”—a phenomenon which has been replicated in scores of subsequent psychological studies. The “bystander effect” holds that the reason people don’t intervene is because we look to one another. The presence of many bystanders diffuses our own sense of personal responsibility, leading people to essentially do nothing and wait for someone else to jump in.
[…]
The study finds that in nine out of 10 incidents, at least one bystander intervened, with an average of 3.8 interveners. There was also no significant difference across the three countries and cities, even though they differ greatly in levels of crime and violence.

Instead of more bystanders creating an immobilizing “bystander effect,” the study actually found the more bystanders there were, the more likely it was that at least someone would intervene to help.
 

How I Almost Destroyed a £50 million War Plane and The Normalisation of Deviance. - Fast Jet Performance


#sociology #psychology #science #engineering
 

How I Almost Destroyed a £50 million War Plane and The Normalisation of Deviance. - Fast Jet Performance


#sociology #psychology #science #engineering
 
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