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Brand X Pictures

Terms for the Penis Among American College Students

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Brand X Pictures

In 1990, linguist Deborah Cameron was teaching a class on language and gender when a male student mentioned that he and his roommates had once had a contest to see how many terms they could name for the "male member." Then a female student mentioned that she and her friends had done the same thing. In the paper Cameron subsequently published ("Naming of Parts: Gender, culture, and terms for the penis among American college students"), she said her "interest was piqued by this exchange. I wondered why college students apparently consider the activity of listing penis terms interesting and enjoyable. I also wondered what an analysis of the terms themselves might tell us about American English and…American culture." And so, she and her students did a study. As one does.

They had two groups of students, one male, one female, come up with as many terms as they could. What they learned was that while there are many, many (oh so many) penis terms in American English, they can be categorized according to a very few basic metaphors. But, unsurprisingly, men and women have different takes on those metaphors.

Because it's National Thesaurus Day (it exists!), let's take a look at some of the terms.

It's a person

Dick, Peter, Johnson, Mr. Happy. Some of these names suggested an intimate friendliness, but for the male group, most of those in the personification category carried a sense of authority (his Excellency, your Majesty, the commissioner) or referenced powerful characters in myths, legends, and comics (Ghengis Khan, Cyclops, The Hulk, The Purple Avenger). The personal names from the female list were all of the intimate friendliness type but for one: Eisenhower.

It's an animal

For the males, basically a dangerous beast like King Kong, The Dragon, Cujo, snake, cobra or anaconda, but sometimes just fun like hairy hound of hedonism. The only animal terms on the women's list were animal length and visions of horses.

It's a tool

For the males there were references to shape (pipe, hose), but mostly to action (screwdriver, jackhammer, drill). The females only had tool.

It's a weapon

Love pistol, passion rifle, pink torpedo, stealth bomber, and other references to the instruments of war were only on the male list, but the female list did overlap with the male list in terms which were variations on a helmet-wearing soldier.

It's food

There was meat spear, which could fit in either the food or weapon category, but also Wiener, Vienna sausage, tube steak, and noodle. Only the female list had biscuit. The male group found this category "the most demeaning and disgusting."

"Romancing the bone"

Only the female list had terms in this category associated with romance novels: throbbing manhood, swelling passion, growing desire.

There were other miscellaneous terms that couldn't be so easily categorized, from sweaty cigar to tallywacker to special purpose. But the majority of terms recapitulated typical cultural associations of masculinity: dominance, violence, dangerousness, and occasionally ridiculousness. Cameron didn't interpret this as necessarily bad news. She sees that the male group is not "simply reproducing myths and stereotypes" but "also recognizing them as myths and stereotypes; and to a significant extent, they are laughing at them." What she does find disheartening, though, is that the metaphors available to young people when they play this naming game "are so limited" and "predictable." The women reject a lot of the offensive metaphors, but "their list offers no real alternatives."

Has this changed since 1990? Do we have better metaphors today? Is it a good idea to invite comments on this? Or will I be sorry I ever brought this up?

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]