The latest viral debate taking over the internet is the man or bear question, so of course there’s lots of memes now. It all started on TikTok with asking women whether they’d rather be in the woods with a man or a bear. Most women are choosing the bear, stating that a man may pose more potential danger than the wild animal. This trend is sparking conversations about violence against women. However, many men have been bizarrely triggered by the trend. Anyway, we collected all the best man or bear memes and comments and here they are:
And here is the original video that started the man or bear debate by @screenshothq!
The fundamental flaws with the odds of being attacked by bear vs a man is it compares the odds of being attacked in a year with the odds of being attacked over the course of your whole life and ignores that on average people spend very little time in areas where there are bears (and when they do are likely to take precautions such as apply bear repellent spray) where as people spend a lot of time on average in areas where there other people, most of the time half of whom will be men.
This latter one is probably an exercise in Bayesian statistics, given that one thing is true what is the probability that another thing is also true. Normally examples given are around if a disease has a certain prevalence in the population and you test positive for that disease with a test that has a known false positive rate what are the odds that you do actually have it. Here, the probability of being attacked by a bear vs a man given doesn’t take account of the different probabilities of being near a bear (without taking precautions) vs being near a man. If people spent as much time close to bears as they do other people then the rate of bear attacks would be much higher. It’s like the oft quoted statistic that you’re more likely to be bitten by a New Yorker than by a shark. If you avoid New York and the ocean then you can reduce both probabilities greatly, if you go to New York then the probability of being bitten by a New Yorker increases and if you swim or surf where there are known to be sharks then the probability of being bitten by a shark is increased.
Also, in the videos I’ve seen (I went on Tik-Tok and looked for them to try to understand what it was about) the question is whether you would prefer to be trapped or stuck with a man or bear, which connotes a different situation from just being near or seeing on the trail. The makers of the videos, based on the T-shirt slogans and other messages their interviewees display, seem to be quite selective about who they talk to, or at least feature. If someone wears a “Smash the Patriarchy” shirt and drinks from a “Male Tears” mug then you can probably draw reasonable conclusions on their views on certain social questions.
Congrats on the Gish gallop.. You totally missed the point.
The nice thing about written arguments is you have all the time in the world to respond to them, unlike a live debate. So go ahead and crush this gish gallop with logic and reason sweetheart.
But I know, ‘the point’ isn’t reasonable. Your point of view HAS been ‘heard’ and been found wanting.
Hmm.
I don’t understand the point you are trying to make here. How exactly are you factoring Bayesian statistics into this particular discussion?
“If someone wears a “Smash the Patriarchy” shirt and drinks from a “Male Tears” mug then you can probably draw reasonable conclusions on their views on certain social questions.”
I don’t understand what you mean here. What conclusions might one draw from their choice of clothing and drinkware?
If someone expresses a particular political view, like say wearing a MAGA hat, then you can reasonably draw the conclusion that they will also hold most if not all of the political views and beliefs typical of MAGA hat wearers. If they are wearing clothing and drinking from vessels displaying certain messages then you can similarly and reasonably draw the conclusion that they will hold and espouse the beliefs and views typical of wearers and users of similarly marked items.
Bayesian statistics is based around given one fact is known, what is the probability of another thing also being true. A common example is given that someone has tested positive for a disease what is the probability that they have it, as I stated above. At any given time there is a probability that you are in the vicinity of a bear and in the vicinity of a man. There is also a probability that you will be attacked by the bear or a man if you are in the vicinity of them. Most people have a very low probability of being in the vicinity of a bear so the stated probability of being attacked by a bear is very low, not because bears are unlikely to attack those in their vicinity but because it’s so rare for anyone to be close enough to a bear to be attacked. Conversely, most people spend most of their time in the vicinity of men so the stated probability of being attacked by a man is higher not because a man is very likely to attack someone but because it’s so common for people to be in the vicinity of men. You could just multiply the probability of being in the vicinity and the probability of being attacked given you’re in the vicinity, for each, but you need the Bayes formula to get a good estimate of the latter.
“If someone expresses a particular political view, like say wearing a MAGA hat, then you can reasonably draw the conclusion that they will also hold most if not all of the political views and beliefs typical of MAGA hat wearers. If they are wearing clothing and drinking from vessels displaying certain messages then you can similarly and reasonably draw the conclusion that they will hold and espouse the beliefs and views typical of wearers and users of similarly marked items.”
How are you defining “reasonably”? Most of the time? 50% of the time? 70%?
“Bayesian statistics is based around given one fact is known, what is the probability of another thing also being true. A common example is given that someone has tested positive for a disease what is the probability that they have it, as I stated above. At any given time there is a probability that you are in the vicinity of a bear and in the vicinity of a man. There is also a probability that you will be attacked by the bear or a man if you are in the vicinity of them. Most people have a very low probability of being in the vicinity of a bear so the stated probability of being attacked by a bear is very low, not because bears are unlikely to attack those in their vicinity but because it’s so rare for anyone to be close enough to a bear to be attacked. Conversely, most people spend most of their time in the vicinity of men so the stated probability of being attacked by a man is higher not because a man is very likely to attack someone but because it’s so common for people to be in the vicinity of men.”
So first you’re saying that there is a probability that you will be attacked by men….but then you’re saying that this is a DEFENSE of why it’s better to be in the woods with men than with a bear? I don’t understand.
And what IS the probability for each likelihood, do you know? What is the exact probability that a given man or a given bear would attack me, whereever I encounter them?
Thank you Stephen for reinforcing the point of the exercise.
See the meme “But bears are dangerous. How do you not get that?”
I live in an area with lots of bears. I’ve met both men and bears in the woods. I’d much rather meet the bear.
the beauty of this is that if all the women who say they would chose a bear would actually go out into the wilderness and hanged out with bears, instead of men, everybody would statistically win: the women, the m,en and the bears.
“if all the women who say they would chose a bear would actually go out into the wilderness and hanged out with bears, instead of men, everybody would statistically win: the women, the m,en and the bears.”
I don’t understand what you’re getting at here. Can you explain?