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18 Academic Papers About '90s TV Shows

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Culture is culture, high or low. If we can learn something interesting about the ancient Romans by studying their drinking songs, surely we can learn something interesting about ourselves by studying our TV shows. The following list of academic papers about the shows of the '90s now belongs to the lofty subject of history.

1. "I'll be there for you" if you are just like me: An analysis of hegemonic social structures in Friends.

Lisa Marie Marshall. Dissertation. Bowling Green State University, 2007.

Gender, race, class and how those friends kept everyone else out of their clique.

2. Solidarity and the Scoobies: an analysis of the -y suffix in the television series Buffy the Vampire Slayer.

Susan Mandala. Language and Literature 16.1, 2007.

When they say stuff like "Heart-of-Darkness-y" on Buffy, they are marking shifting group alliances.

3. Subtitling Rap: Appropriating The Fresh Prince of Bel-Air for Youthful Identity Formation in Kuwait.

Timothy Havens. International Communication Gazette 63.1, 2001.

A group of kids in Kuwait got into the Fresh Prince. What do they identify with?

4. Smoking and The Simpsons.

Guy D. Eslick, and Marielle G. Eslick. Med Journal of Australia 190.11, 2009.

The characters on The Simpsons smoke a lot more than you might think. And it's only portrayed as a negative thing about a third of the time.

5. The use of music on Barney & Friends: Implications for music therapy practice and research.

Kenneth M. McGuire. Journal of Music Therapy 38.2, 2001.

In the name of science, the authors studied the use of music in all 88 episodes of the show.

6. From the Simpsons to the Bundys: A critical analysis of disrespectful discourse in television narratives.

Tony Russell DeMars. Dissertation, The University of Southern Mississippi, 1996.

TV captures a lot about how we view rudeness, but it didn't make your kids rude.

7. Ancient archetypes in modern media: A comparative analysis of Golden Girls, Living Single, and Sex and the City.

Deborah Ann Macey. Dissertation. University of Oregon, 2008.

The Iron Maiden, the Sex Object, the Child, and the Mother, these ancient archetypes find their place on all our shows.

8. Mighty Morphin Power Rangers: the aesthetics of phallo-militaristic justice.

Peter McLaren and Janet Morris. In Kinderculture: The Corporate Construction of Childhood. Shirley R. Steinberg and Joe L. Kincheloe, eds., 1997.

Do you really need anything more than that magnificent title?

9. Revealing the universal through the specific in A Different World: An interpretive approach to a television depiction of African-American culture and communication patterns.

Venita Ann Kelley. Dissertation. University of Kansas, 1995.

A look at how the media looks at African-American culture, with A Different World as a non-sensationalized example.

10. Children's television: A content analysis of communication intent in Arthur and Rugrats.

William Wayne Anderson. Dissertation. Northern Illinois University, 2001.

There's better communication on Arthur than Rugrats.

11. Jung and Picard: Archetypes and the modern myth of Star Trek: The Next Generation.

Kenneth Alan Hutchins. Dissertation. Pacifica Graduate Institute, 1996.

In this interpretation of the myth of the Hero's Journey, the whole crew is the hero.

12. The Schlemiel and the Schlimazl in Seinfeld.

Carla Johnson. Journal of Popular Film and Television 22.3, 1994.

In Yiddish folklore the schlemiel is the klutz who spills the soup while the schlimazl is the sap who gets the soup spilled on him. Jerry is the schlimazl to George's schlemiel.

13. Powerpuff Girls: Fighting evil gender messages or postmodern paradox?

Carole Baroody Corcoran and Judith A. Parker. The psychology of prejudice and discrimination 3, 2004.

More of the latter, actually.

14. Images of prime time justice: A content analysis of NYPD Blue and Law & Order.

Sarah Eschholz, Matthew Mallard, and Stacey Flynn. Journal of Criminal Justice and Popular Culture 10.3, 2004.

How does what happens on these shows match up with the real world stats?

15. The Fallacy of Falsity Un-“Dresch”-ing Masquerade, Fashion, and Postfeminist Jewish Princesses in The Nanny.

Vincent Brook. Television & New Media 1.3, 2000.

Yeah, there's something very bizarre about the social roles on this show.

16. Television and the Teenage Literate: Discourses of Felicity.


Margaret Mackey. College English, 2003.

Literacy and "literacies," Felicity's got 'em all.

17. Living on Dawson’s Creek: Teen viewers, cultural convergence, and television overflow.


Will Brooker. International Journal of Cultural Studies 4.4, 2001.

Did Dawson's Creek fans in the real world create a culture of their own?

18. The role of the television drama ER in medical student life: Entertainment or socialization?


Michael M O'Connor. JAMA: The Journal of the American Medical Association 280.9, 1998.

Your doctor had to be socialized into doctorhood. Maybe ER helped.

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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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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May 23, 2017
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