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The Strange Tale of Texas’ All-Female Supreme Court

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The lawyer approached the bench to be certified. A member of the state bar? Check. A practicing attorney for more than seven years? Check. Never participated in a duel? Check. Hortense Sparks Ward climbed the podium, sat in the center chair, and took her place as chief justice of the Supreme Court of Texas.

The year was 1925, and it would be 66 years before another group of women managed to eke out a majority in any state court. So how did three women take over the highest court in Texas a mere four and a half years after women won the right to vote? The story of Texas’ “Petticoat Court” is one of old boys’ clubs political vendettas, and a group of women bold enough to serve a court that actively undermined their interests at every turn.

In 1924, Texas’ outgoing governor, Pat Neff, was a sitting duck. He had been elected twice, and though the state didn’t expressly forbid a governor from sitting for three terms, it had never been done before. But Neff was less than thrilled about his elected successor—Miriam “Ma” Ferguson, the wife of a former governor who had been barred from future office after being impeached for a retaliatory veto. Ma Ferguson wasn’t just a shrewd wheeler and dealer—she was the first woman winner of a gubernatorial election in the United States. And that didn’t sit well with Neff.

In March 1924, Neff had been informed of a conflict of interest at the state supreme court. It involved a land dispute case that had originally been heard in El Paso. The case involved the Woodmen of the World (WOW), a fraternal organization that did double duty as the insurance carrier and old boys’ network of nearly every male lawyer in the state of Texas. When attorney after attorney recused himself from the case, the state turned to Neff and told him he must appoint a special court instead. Neff hemmed and hawed—but ten months later, he landed on a solution. The WOW only admitted men, so why not assemble a special state supreme court with only women? 

The scheme wouldn’t just solve the conflict of interest—it would give Neff the opportunity to one-up Ma Ferguson before she had even taken office. It was hard to find qualified women to fill the three seats of the special court, but after a few misses, Hortense Sparks Ward, Hattie Lee Henenberg, and Ruth Virginia Brazzil were certified as the state supreme court in the case of Johnson v. Darr

Hortense Ward was used to controversy—she had fought hard to be admitted to the state bar and was the state’s first female lawyer. But she was also experienced, and even practiced before the United States Supreme Court in 1915, though she tended to minimize her court appearances for fear of the reaction of all-male juries. When she took her seat as temporary chief justice, she was already well known for her support of women’s rights, including lobbying for and winning a law that protected the property rights of married women.

To understand how revolutionary the appointment of three women to a state supreme court was at the time, it helps to realize that women weren’t even allowed to serve on juries (and wouldn’t for another 30 years). And though the Texas Bar grumbled in private, they knew there was no other alternative to the court’s conflict of interest problem.

Four months after their appointment, the “Petticoat Court” ruled in favor of WOW and the special court was dissolved. It would be 57 years before another woman, Ruby Kless Sondock, served on the Supreme Court of Texas—and today, only two of nine justices are women. 

Additional Sources: The Southern Judicial Tradition: State Judges and Sectional Distinctiveness, 1790-1890 Texas Obscurities: Stories of the Peculiar, Exceptional and NefariousThe Texas Supreme Court: A Narrative History, 1836–1986; Texas State Historical SocietyTexas Bar Association

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iStock // Ekaterina Minaeva
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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Scientists Think They Know How Whales Got So Big
May 24, 2017
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It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]