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Pandemic Parenting, Green Steel, and Subtracting Sexism: Five Things That Made Us Smarter This Week

From refabricating materials to recalibrating priorities, we learned a lot over the last seven days

We’re living in a world awash with content—from must-read articles and binge-worthy shows to epic tweetstorms and viral TikToks and all sorts of clickbait in between. The Elective is here to help cut through the noise. Each week, members of the Elective team share the books, articles, documentaries, podcasts, and experiences that not only made them smarter but also changed how they see the world around them and, often, how they see themselves.

Group of people holding signs protesting gerrymandering

Tasos Katopodis/Getty Images

Protesters attends a rally for "Fair Maps" on March 26, 2019 in Washington, DC. The rally was part of the Supreme Court hearings in landmark redistricting cases out of North Carolina and Maryland.

Review, Redraw, Redistrict
 

I was a wide-eyed 20-something legislative aide for the Texas Speaker of the House in 1990 when I first heard the term “redistricting.” There was a dedicated committee in the House whose job was to draw the districts for congressional seats and state lawmakers based on decennial Census data. The buzz then was that there was a fancy new computer program that could help draw the lines, a major innovation over the meticulous, hand-calculated process that existed for the better part of two centuries. As I remember it, legislators would go into the anteroom behind the main hearing room and work with a computer-nerd-mapping-savant and test different models for their districts. There was chatter that lawmakers were “picking their voters” rather than the voters picking their representatives, meaning they were drawing district lines to get a specific mix of citizens who would return a specific slate of legislators—primarily incumbents. It was a bipartisan exercise.

In the 30 years since, technology and redistricting have gotten much more sophisticated and controversial. The software that lets lawmakers draw precise lines to achieve precise demographic results has gotten a lot more powerful, fed by bigger and better streams of data, and the politics of gerrymandering have become more intense. If you want an inside look at what all the fuss is about, there are now some nifty DIY mapping tools that let you try your hand at building your own legislative maps. What characteristics would you favor if you were in charge of drawing legislative borders? Would you optimize for "community of interest,” meaning people who see themselves as civically or economically related? Would you aim for proportional representation by race? By party affiliation? Compactness or geographic neatness? Diversity within the district? Opinion writers make it sound easy to draw fair districts, and there are definitely some examples of gerrymandering so egregious that it's hard to find any logic in them. But fairness isn't as simple as it sounds. An old colleague of mine drew a joke congressional map where every district in Texas had a tiny toehold in Austin, so everyone could keep their "district office" in the capital and save on commuting costs. The whole state looked like a strange pizza, with Austin in the middle. He made his point—there are a lot of ways to draw maps depending on what you prioritize. So what's your definition of fair and reasonable? —Stefanie Sanford

Woman gestures while speaking on a stage in front of a large screen with mathematical concepts projected onto it

Pablo Costa/ICM 2018/flickr

Ingrid Daubechies speaks at the 2018 International Conference of Mathematicians in Rio de Janiero on August 3, 2018.

01101100 01100101 01100111 01100101 01101110 01100100
 

Everything you see on a screen is math. Ones and zeroes, alternating in fantastically complex patterns to produce a TikTok video, a video game, or a brilliant collection of reading recommendations from your favorite education website. The calculations required to get a live, high-definition feed of a football game onto your giant television screen are mind-bogglingly intricate. That’s where mathematicians like Ingrid Daubechies come in, creating advances in the ever-growing field of “signal processing.” I am not going to do justice to the complexities of wavelet theory and how it relates to artificial intelligence, but I love reading articles that stretch my understanding of science to the breaking point. And this one, from Siobhan Roberts and the New York Times Magazine, absolutely did.

It also provided some vivid examples of just how stubbornly sexist academic fields like physics and mathematics have been for a very long time. Daubechies is clearly a genius, and has a wonderful sense of humor—she threw a big bash for her 64th birthday instead of her 65th, because 64 is a cooler number in binary (1000000). But she has also had to push against a field so oblivious to its own biases that a Playboy picture served as a standard test image at signal processing conferences for decades. When she was almost hired away from Duke University a few years ago, Daubechies conditioned her retention offer on a commitment to recruit and hire female mathematicians until they make up 30% of the school’s faculty. “This is a data-driven target,” Roberts writes. “Surveys by the American Mathematical Society indicate that at universities with R1 status, the highest research classification, women constitute about 30 percent of math Ph.D. students, but only about 17 percent of the tenured or tenure-track faculty.” Daubechies is used to untangling wickedly complex problems. Glad to know academic gender bias is on her list. —Eric Johnson

Red-hot block of steel rolling off a mill machine

SSAB

A slab of the "first fossil-free steel in the world. #infrastructureweek

Ironing Out Steel’s Future
 

You don’t have to be a sports fan to know the Pittsburgh Steelers logo: three star-like shapes with the team name against a white background. But what’s less familiar is that it’s actually the steel industry’s mark, and those shapes are hypocycloids representing the steelmaking process: the yellow for coal, red for iron ore, and blue for steel scrap. The success of the Steelers (and rabid black-and-gold die-hards of the Pittsburgh diaspora, created by the cratering steel industry in) has made that symbol iconic. But it’s also a monument to dirty fossil fuels. Steel—Pittsburgh steel—built America and the modern world. But it’s absolutely abysmal for the environment. Steel production ruins air quality, pollutes rivers, and generates tons of byproduct. (One of my favorite malls growing up in Pittsburgh (RIP Century III) was built atop fields of slag.) Cleaning up fossil-fuel-heavy building materials is huge business. Steel seems ungreenable, but what do you use instead? How about, um, steel? In August, Swedish company SSAB delivered the world’s first load of steel manufactured without fossil fuels. “[This] is not only a breakthrough for SSAB, it represents proof that it’s possible to make the transition and significantly reduce the global carbon footprint of the steel industry,” Martin Lindqvist, president and CEO of SSAB, said in a statement. “We hope that this will inspire others to also want to speed up the green transition.” Indeed, SSAB has already found some big-league allies: Volvo took that first load of green steel, and in September Mercedes-Benz received an order of its own.

There’s a whole technical conversation about the process, which is itself fascinating. But basically, as Forbes explains it, SSAB’s “Hydrogen Breakthrough Ironmaking Technology replaces fossil fuels both in the production of the iron pellets that are the key ingredient of steel, and in the removal of oxygen from the iron by replacing carbon and coke with green hydrogen.” The climate change conversation often breaks down over economic issues, especially when it comes to how we get around and how we build. The rapid expansion of electric car ownership and infrastructure (not to mention a move toward hydrogen fuel) is exciting, but SSAB’s green steel could be game changing—for the climate, for the built environment, for the economy, and for workers. Let’s swap out that yellow hypocycloid for a green one! —Dante A. Ciampaglia

Tall blonde woman wearing a business suit and face mask walks behind two people, also masked, into a courtroom

Ethan Swope/Getty Images

Theranos founder Elizabeth Holmes arrives at the Robert F. Peckham Federal Building with her defense team on August 31, 2021. Holmes is on trial after being indicted on multiple counts of fraud for misrepresenting her company's blood-testing technology.

There Will Be Rapid Testing
 

I first learned about Theranos several years ago when someone compared me to CEO Elizabeth Holmes dressing like Steve Jobs. (I was wearing a black turtleneck; I hope that's where the resemblance ended.) This was in 2016, and at the time Holmes' company—which developed rapid blood testing technology it claimed would revolutionize medical diagnosis and care—was under investigation for its tech failing to comply with federal standards and accuracy requirements. I was immediately intrigued by both her persona and the seeming short-comings of her business, which we now know was a long con. Theranos dissolved in 2018, months after Holmes and former company president Ramesh Balwani were charged with fraud by the SEC.

As Holmes’ criminal trial begins (two counts of conspiracy to commit wire fraud, 10 counts of wire fraud, all federal charges), The Atlantic’s Benjamin Mazer draws interesting parallels between Theranos and covid-19 rapid testing. The company thrived, at least at first, thanks to lax federal oversight that allowed the organization to generate 890,000 test results a year—tens of thousands of which were inaccurate. Theranos took advantage of a loophole for laboratory-developed tests (LDTs) that allowed it to skirt FDA approval in using what were fraudulent tests. At the onset of the pandemic, the FDA attempted to address this gap by requiring that labs receive approval to evaluate covid-19 test results. This process proved too slow to support the moment’s public health and was discontinued in August 2020. As Mazer points out, though, "The same emergency protections that slowed test availability in early 2020 had also blocked Theranos from deploying potentially inaccurate Ebola and Zika tests half a decade earlier." In the wake of Theranos and the testing challenges America faced in the first months of the pandemic, the FDA must adjust and balance the need for speed—ensuring patients receive covid-19 test results quickly—and reliability—the results need to be accurate. Threading that needle is up to Congress, which is evaluating one bill that eliminates FDA oversight for LDTs and another that tightens it. Hopefully it won't take another Elizabeth Holmes to find the right balance.  —Hannah Van Drie

Father Putting Home Made Face Mask on Little Daughter

Morsa Images/Getty Images

The only certainty when it comes to parenting is uncertainty. But we can mitigate some of it through data. And a shelf full of Emily Oster's books. Or so say Emily Oster stans.

Oster’s Pearls of Parenting Wisdom (Pandemic Edition)
 

Parenting means accepting a constant stream of worries out of your control. You can take precautions, calculate, do your best to make good decisions and shield your kids from harm, but there’s no eliminating risk. That’s always a little hard to accept, and it has been maddening for many parents over the last 18 months of the pandemic. After the initial lockdown last spring, we had to make all kinds of fraught decisions with deeply imperfect information. Back to daycare or no? Can we visit with the family down the street? Take off our masks at the playground? Let our kids join us on grocery trips again, which they absolutely love? Through all of it, the Brown University economist and parenting-data evangelist Emily Oster has tried making sense of the science to help parents think clearly about risk. The latest entry of her ParentData newsletter, “COVID: When will it be over?,” gives a smart if unsatisfying answer to the question we’ve all been asking for the last year and a half.

“In the end, the message here is that there is no world of ‘no COVID,’ and if you are waiting for some external sign that the pandemic is over, you will be waiting forever,” Oster writes. “Eventually it will move to our everyday risks; our behavior will adapt to its existence, but it will not be top-of-mind all the time.” In other words, the risk of getting ill from covid-19 won’t disappear, but we’ll eventually register it as so small that it’ll become part of the background noise we accept as the price of having a full and meaningful life. “There may be some broad adaptations of our behavior to the existence of the risk, but there will also be a point at which COVID is not a part of our everyday calculations about playdates and weddings and birthday parties,” Oster predicts. “And when we get to this point, it will feel more like the ‘before times,’ even if it looks a little different.” Oster is a little polarizing within the parenting world; there are people who swear by her data-centric approach and others who find it insensitive. What I like about her writing and thinking is that she’s honest about tradeoffs, about the fact that anything worth doing—going to the park, taking a trip, having kids in the first place — requires accepting some level of uncertainty. A reasonable dose of caution is great, but too much can be crippling. And everyone has to figure out where that line gets drawn in the not-quite-post-pandemic world. —Eric Johnson