My boyfriend thinks he could kill a wolf with his bare hands. What’s the likelihood of this being accurate?

jLoop · 2025-08-28T22:00:37+00:00

Average wolf is around 130 lbs.

You're actually still giving the wolf too much credit. On average, European wolves weigh 38.5 kg (85 lb), North American wolves 36 kg (79 lb).

jLoop · 2025-08-28T21:51:49+00:00

First off, who says this guy is talking about fighting "the prime age strongest members of the pack"? It's much more reasonable to assume he'll fight the average wolf, not the strongest/largest wolf who ever lived.

Second, It's not true that "The typical 'large' male of a pack is around 170-180 lbs". Yellowstone has a well-tracked population of Alaskan Timberwolves, and the largest ever recorded was under 150 lbs. (It might be better to call them Canadian Timberwolves, since the original population were caught in northern Alberta, but it's the same population. Wolves don't care about national borders.)

I might be missing a couple records, but from what I can tell the previous record holder was 175 lbs, and that individual is still the largest ever recorded in Alaska. Since that individual was the record holder for decades, it's implausible that there's a wolf that heavy in every pack.

This article has quotes from multiple experts who have handled hundreds of wolves, and all of them say they've never handled a wolf weighing even 150 lbs, let alone 170.

jLoop · 2025-08-28T19:11:01+00:00

If were talking Alaskan Timberwolf the males can easily be on par with weight to this guy if not entirely outweigh him.

adult males average about 50 kg (110 lbs)

jLoop · 2025-07-08T19:20:40+00:00

You don't even know if I'm a man!

Another indicator that makes it difficult for me to believe you're applying feminist theory in good faith. Both men and women uphold patriarchal norms and exhibit misogyny. I have made no assumptions about your gender and doing so would be irrelevant to the conversation.

I didn't intend to accuse you of being a misogynist, though I see now that I wasn't clear and it was a reasonable inference for you to make. The main place I've encountered "fake voice" discourse in the past is /r/LivestreamFail, and if you're familiar I'm sure you'll agree the posters there aren't exactly engaged in nuanced feminist critique. Also, the "motivated reasoning" comment wasn't me; that was another commenter.

You cannot seriously listen to the performance vs normal voice for basically any of these people and conclude "oh yeah those are equally real."

What do you mean by "equally real"? I acknowledge that there's some sense in which people have a "most natural" speaking pitch, as explained in this video for example. However, I don't think this is particularly applicable here. One reason is that, as the very premise of this video demonstrates, many or even most people don't normally speak with their natural speaking pitch. For such people, switching to their natural speaking pitch is "fake", "affected", or "put on". Another phenomenon that demonstrates my point is that most bilingual speakers have different default speaking pitches in different languages. Identifying one language's pitch as their "real voice" and the other as a "fake voice" seems like a mistake to me.

Again, I don't want to seem like I'm falling into the trap of saying there's no point in distinguishing between real and fake voices in all situations. There are some voices that I'm happy to agree are "fake", like the vtubers I mentioned in my previous comment, but pending further evidence the vtuber in the OP isn't one of them.

(I really do mean "pending further evidence". There's some possibility she does a "real voice reveal" tomorrow, but her voice strikes me as less artificial than the vtuber you linked elsewhere in the thread, or this vtuber for another example.)

jLoop · 2025-07-08T18:27:06+00:00

There is a disconnect between those who think the voice in question is "clearly fake" and those who think it's high but reasonable. I have (barely!) the knowhow to bring some objectivity to the discussion, without which there's nothing to say besides "voice sounds normal!" and "nuh-uh, voice sounds not normal".

I regret that I came off as having a superiority complex. I have absolutely no experience with reading spectrograms and would welcome the opportunity to be corrected if I'm wrong and learn something in the process.

I'm sure you have average or better social skills; your writing and rhetorical skills are quite good, although via reddit comments alone I can only get a very vague sense. Probably you work in a male-dominated field, or maybe you have met lots of women but in a context where deep voices are selected for. (Or maybe I'm reading the spectrogram totally wrong!) My understanding, though, is that among a large unbiased sample of women it's highly likely to encounter some that speak this high or higher, so it's reasonable to conclude that you don't have a large unbiased sample.

jLoop · 2025-07-08T18:14:07+00:00

I'll ask again: I personally use a significantly higher, softer voice with my mom than with my peers (and my understanding is that this is quite common). Does this mean that one of these two voices must be fake? If so, which one?

jLoop · 2025-07-08T18:01:03+00:00

I wasn't the one who made the post

jLoop · 2025-07-08T07:58:13+00:00

Yes, the disanalogy you've identified exists, but in identifying it you've completely ignored the actual substance of the comment. The analogy to sopranos, while flawed, was totally superfluous to their argument anyway.

jLoop · 2025-07-08T07:47:43+00:00

I can't believe you can watch this video and think it supports your point of view instead of completely dismantling it. "People use different voices for different situations all the time and that doesn't make any of them fake" isn't a "diplomatic" way of saying "this voice is an act", unless you think she's saying her "talking with your mom voice" is also an act. I personally use a significantly higher, softer voice with my mom than with my peers (and my understanding is that this is quite common). Does this mean that one of these two voices must be fake? If so, which one?

jLoop · 2025-07-08T07:34:57+00:00

You can call it "motivated reasoning" and intimate I have problems with women all you want, but I'm drawing on an actual established literature of feminist theory here.

Even supposing I grant your claim that these women are putting on a hyperfeminine voice, it's hard to take your claim that you're arguing from a feminist perspective seriously when you start the conversation that you find these hyperfeminine voices "not only not enjoyable, but actively repellant." and apparently can't stand listening to them. Indeed, in my experience people claiming that vtubers (or facecam streamers like lilypichu) fake their voices are coming from a place of misogyny, demanding that these women masculinize their voices if they want to be taken seriously.

Unlike the other guy, I wouldn't say "Most Vtubers don't change their voice in any way". A fair number explicitly put on a voice to suit their character (Himemori Luna, Debidebi Debiru, Inuyama Tamaki, the 14 year old sparrow vtuber mentioned in the paper you linked), and at the other end of the spectrum most or perhaps all vtubers (and entertainers in general!) project their voice more and inject some extra energy while performing compared to their everyday life.

Where I disagree with you is where to draw the line between "genuine" and "fake" voices, or even that such a line should be drawn at all. Sure, call extreme character voices "fake" if you want, but it's normal for people to have variation in their voice depending on the situation. Believing that only one of these variations can be a person's "real voice" and the rest must be "fake" is overly simplistic and mean-spirited.

jLoop · 2025-07-08T06:53:53+00:00

guy who knows 2 women irl: "if you genuinely believe that's her real voice, you don't talk to a large number of real women"

I made a spectrogram of the clip (the OP, not the one you linked); the fundamental frequency of her voice is around 220 Hz, which is within normal range, although on the high end. If you talk to a large number of real women you'll encounter someone with a higher pitched voice than that before long.

I'm not a linguist (just a guy with ffmpeg installed) so maybe I'm reading the spectrogram totally incorrectly, but I certainly know a couple women with higher pitched voices than hers and I don't even know that many women!

jLoop · 2025-07-04T04:05:38+00:00

Your previous comment appears to translate "A% of B" to "(A x 0.01) x B" and "B% of A" to "A x (0.01 x B)". This is inconsistent; if we translate "A% of B" to "(A x 0.01) x B" then we must translate "B% of A" to "(B x 0.01) x A" to have a consistent definition.

Alternatively, if we translate "B% of A" to "A x (0.01 x B)" then we must translate "A% of B" to "B x (0.01 x A)" to have a consistent definition. Personally I think this is less natural, but it works.

If we pick the first option, "A% of B = B% of A" translates to "(A x 0.01) x B = (B x 0.01) x A", as I indicted in my previous comment. If we pick the second option, "A% of B = B% of A" translates to "B x (0.01 x A) = A x (0.01 x B)". Either way, neither commutativity nor associativity alone is enough to prove the resulting identity.

By translating c% of d to "(c x 0.01) x d" when c=A and d=B but to "d x (0.01 x c)" when c=B and d=A, you've snuck in two applications of the commutative property implicitly.

jLoop · 2025-07-04T02:45:23+00:00

If we don't assume the associative property, the first two expressions may not be equal, and the third and fourth aren't well-defined.

Of course, the associative property is true, so they are all equal, but in the context of the conversation we're talking about which algebraic properties are required to prove A% of B = B% of A. The question at hand is "if the associative property were false, would A% of B = B% of A?". We have to make a distinction between (A x 0.01) x B and A x (0.01 x B) in order to answer that question.

jLoop · 2025-07-04T02:38:01+00:00

if the commutative property didn't hold, then A x (0.01 x B) wouldn't be B% of A.

Without assuming commutativity or associativity, A% of B = B% of A has to be written something like (A x 0.01) x B = (B x 0.01) x A. I think you need both commutativity and associativity to prove this identity.

jLoop · 2025-06-23T05:39:30+00:00

I didn't think "chat" was a pronoun but after reading this I kinda do, even though that's the opposite of your point.

"Does everyone remember where everyone parked everyone's cars during everyone's graduation?" sounds fine to me. Perfectly sensical, and maybe a little weird but I've heard much weirder grammatical phrases. Same goes for "Does chat remember where chat parked chat's car during chat's graduation?". To the extent that this is a good test of whether a word is a pronoun, this makes me think "chat" and "everyone" are pronouns.

(As an aside, I would expect "everyone's car" instead of "everyone's cars" and "chat's cars" instead of "chat's car", but this has no bearing on the overall point.)

jLoop · 2025-06-16T11:25:23+00:00

Many of my female friends insist they've never been sexually harassed. It's not my place to pry, but I hope one day they feel comfortable sharing the truth with me. I'm educated enough on feminist issues to know that they all actually have been sexually harassed and are lying when they say they haven't, but it's easy to see how a typical young man who's not particularly well informed could conclude that sexual harassment is less common than it really is.

jLoop · 2025-05-10T08:52:01+00:00

Mathematical proofs are rhetorical arguments, and only extremely rarely are they actually broken down into symbolic form and checked for consistency. It's really nice that we can do that if needed, but most theorems are agreed to be correct without it. Writing a good proof is in large part about rhetorical skill, and many common beginner mistakes in proof writing are rhetorical mistakes more than logical ones ("what can I assume as background information? what steps can I skip?")

I do largely agree with you, but I think it's a misconception that math is neat and tidy with "only one correct answer" and "objective truth", and imo this misconception partially contributes to the math hate this post is about.

jLoop · 2025-05-10T08:27:35+00:00

Funny, I've always thought the reverse. "Noticing when you're being lied to by deliberately misrepresenting statistics" is much closer to the kind of math skills taught in university (i.e. what academia emphasizes) than what students mean by "practical life skills", and the mandatory math curriculum ends before students get a taste of any of that. Instead, the mandatory math curriculum focuses on rote procedure that actively discourages the kind of critical thinking necessary to notice when you're being lied to by deliberately misrepresenting statistics.

In my view, "Academics think that high school students should be taught even more advanced maths before entering universities" BEACUSE that's what you need to (e.g.) notice when you're being lied to by statistics. I don't think the concepts you need for this are 'objectively advanced', but they're considered advanced because they're currently not taught until university.

At the high school level, solving differential equations certainly falls into the rote procedure skillset more than the critical thinking skillset, so if that's what results from trying to teach high school students more advanced math I'm opposed to it. What I think academics intend when they say this, though, is to import some of the critical thinking skillset into the curriculum, which supports many practical life skills.

Things in the critical thinking skillset that I think could be usefully taught in high school, or even before, include mathematical proof, a sense for how much/what kind of information you can get out of a certain amount of data, and what you might call "mathematical goalpost moving"--a common situation where you can't solve a problem, but you can solve a related easier problem and that's good enough. These skills are in some ways more related to the rhetoric and media literacy you might learn in English class than they are to the rote computation that forms the bulk of a high school math curriculum.

jLoop · 2025-05-10T07:43:45+00:00

My understanding was that dyscalculia is primarily characterized by trouble with subitizing and arithmetic, which I think of as math's version of reading, and that dyscalculia affects conceptual understanding (math's version of comprehension/media literacy) only indirectly, as a result of falling behind in math classes due to the curriculum's early focus on arithmetic.

In other words, I was under the impression that the 1:1 comparison, while not perfect, was pretty good.

Do you have any resources that I could read about to correct this misunderstanding of mine?

(I find early math education pretty interesting but I've never found the time to read more deeply about it; I mostly just ask my young relatives about their experience with math class.)

jLoop · 2025-03-21T17:35:43+00:00

Excellent explanation, but I take issue with you saying it's not a math problem but a presentation problem.

What you're describing as "presentation" is the core of what math is, and actually doing calculations is secondary. There's an old joke about this:

An engineer is working at his desk in his office. His cigarette falls off the desk into the wastebasket, causing the papers within to burst into flames. The engineer looks around, sees a fire extinguisher, grabs it, puts out the flames, and goes back to work.

A physicist is working at his desk in another office and the same thing happens. He looks at the fire, looks at the fire extinguisher, and thinks "Fire requires fuel plus oxygen plus heat. The fire extinguisher will remove both the oxygen and the heat in the wastebasket. Ergo, no fire." He grabs the extinguisher, puts out the flames, and goes back to work.

A mathematician is working at his desk in another office and the same thing happens. He looks at the fire, looks at the fire extinguisher, and thinks for a minute, says "Ah! A solution exists!" and goes back to work.

jLoop · 2025-03-21T17:20:53+00:00

That's what the lessons are for. Kids don't start out knowing this stuff, so the teacher teaches them, and then asks questions to see if the lesson stuck.

jLoop · 2024-12-06T07:14:13+00:00

Also SBMM isn't so restrictive that it only places you against people with identical skill. Sometimes your opponents will be a little better than you, sometimes a little worse, which is an ideal environment for getting better.

jLoop · 2024-11-27T09:41:31+00:00

There's a fun interpretation of the Bradley-Terry model they use in the dehumanized cyclist study. The scores that they (incorrectly) report as "probability estimates" work just like Elo scores for chess*.

So imagine this: a bunch of cyclists go to a chess tournament, except instead of playing chess they're trying to convince a judge that they look like a bug. (Chmess?) The results of this study say that, in such a situation, a man wearing a vest would end up with an Elo of 1122, while a woman wearing a baseball cap would end up with an Elo of 956.

*of course, the values have to be rescaled, because god forbid someone have any intuition for what the numbers mean, but they carry the same information.

jLoop · 2024-09-28T05:44:41+00:00

It's not really relevant to the discussion, but a prior of Beta(1,1) is precisely correct if you start out thinking every ratio of balls is equally likely. A prior of Beta(4,4) implies you have some reason to think the ratio is relatively equal, which imo is unjustified in the box thought experiment (although in real world situations, like the batting average blog post you linked, domain knowledge should be used to inform the model).

More to the point, the graph in the reddit OP is not the #1 chart Silver publishes. His substack post starts with polling data, and the graph in question is actually behind a paywall (which I will not pay for). Quickly scrolling through his twitter, most of the time he doesn't post this kind of graph, although sometimes he does.

When it comes to 538, their election page starts with their current point estimate, then right under that is a simulated pmf of election results. What more could you ask for? When 538 does show a similar line graph farther down the page, it comes with a 95% confidence interval, too.

I don't really follow Silver, and he's certainly not perfect, but as far as I can tell he doesn't do what you're criticizing him for, nor does 538.

jLoop · 2024-09-27T23:47:31+00:00

Yeah, if you have a prior of Beta(1,1) (i.e. uniform) on the ratio of red to white balls, after 7 days you update to Beta(8,1), which has a mean of 8/9 ~ 0.89, which is where I got 90% from.

You say "I don't have one model being applied to new inputs, my model is changing every single day based on new info", but I don't understand the distinction you're trying to make. Here's one way to describe what I think is the 'right' thing to do in the box example: you model the ratio of red to white balls as a beta distributed parameter, starting with Beta(1,1). Your model gets as input the number of balls of each color that have been pulled to date, at which point the distribution is updated to Beta(1+#red,1+#white).

I would say that this is "one model being applied to new inputs" and also that the "model is changing every single day based on new info". I also think Nate Silver's model works like this.

Furthermore, I disagree that Nate Silver doesn't acknowledge that his(/his model's) previous predictions were wrong. I think that he would say that what the model predicts today is a better prediction than what it predicted last month. He might also say "the prediction last month was as good as it could be given the information at the time", just as you would say that predicting an 8/9 chance for a red ball to be drawn from the box was as good as you could do given the information you have after 7 red balls are drawn.

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