David Epstein
Range
strategy. Human/Computer combo teams—known as “centaurs”—were playing the highest level of chess ever seen.
When we know the rules and answers, and they don’t change over time—chess, golf, playing classical music—an argument can be made for savant-like hyperspecialized practice from day one. But those are poor models of most things humans want to learn.
with an unkind domain, the human tendency to rely on experience of familiar patterns can backfire horribly—like the expert firefighters who suddenly make poor choices when faced with a fire in an unfamiliar structure. Chris Argyris, who helped create the Yale School of Management, noted the danger of treating the wicked world as if it is kind.
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The world is not golf, and most of it isn’t even tennis. As Robin Hogarth put it, much of the world is “Martian tennis.” You can see the players on a court with balls and rackets, but nobody has shared the rules. It is up to you to derive them, and they are subject to change without notice.
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Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer.
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“rather than obsessively focus[ing] on a narrow topic,” creative achievers tend to have broad interests. “This breadth often supports insights that cannot be attributed to domain-specific expertise alone.”
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engineer Claude Shannon, who launched the Information Age thanks to a philosophy course he took to fulfill a requirement at the University of Michigan. In it, he was exposed to the work of self-taught nineteenth-century English logician George Boole, who assigned a value of 1 to true statements and 0 to false statements and showed that logic problems could be solved like math equations. It resulted in absolutely nothing of practical importance until seventy years after Boole passed away, when Shannon did a summer internship at AT&T’s Bell Labs research facility. There he recognized that he could combine telephone call-routing technology with Boole’s logic system to encode and transmit any type of information electronically. It was the fundamental insight on which computers rely. “It just happened that no one else was familiar with both those fields at the same time,” Shannon said.
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The successful adapters were excellent at taking knowledge from one pursuit and applying it creatively to another, and at avoiding cognitive entrenchment. They employed what Hogarth called a “circuit breaker.”
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Their skill was in avoiding the same old patterns. In the wicked world, with ill-defined challenges and few rigid rules, range can be a life hack.
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Ospedale della Pietà. The name literally means “Hospital of Pity,” but figuratively it was the House of Mercy, where the girls grew up and learned music. It was the largest of four ospedali, charitable institutions in Venice founded to ameliorate particular social ills.
Most of them would never know their mothers. They were dropped off in the scaffetta, a drawer built into the outer wall of the Pietà.
The ospedali were public-private partnerships, each overseen by a volunteer board of upper-class Venetians. The institutions were officially secular, but they were adjoined to churches, and life inside ran according to quasi-monastic rules.
Once the indoor space was full, listeners crowded outside windows, or paused their gondolas in the basin outside. Foundlings became an economic engine not just sustaining the social welfare system in Venice, but drawing tourists from abroad. Entertainment and penitence mixed in amusing ways. Audience members were not allowed to applaud in church, so after the final note they coughed and hemmed and scraped their feet and blew their noses in admiration. The ospedali commissioned composers for original works. Over one six-year period, Vivaldi wrote 140 concertos exclusively for the Pietà musicians. A teaching system evolved, where the older figlie taught the younger, and the younger the beginners. They held multiple jobs—Anna Maria was a teacher and copyist—and yet they produced star after virtuoso star. After Anna Maria, her soloist successor, Chiara della Pietà, was hailed as the greatest violinist in all of Europe.
It all raises the question: Just what magical training mechanism was deployed to transform the orphan foundlings of the Venetian sex industry, who but for the grace of charity would have died in the city’s canals, into the world’s original international rock stars?
The Pietà’s music program was not unique for its rigor. According to a list of Pietà directives, formal lessons were Tuesdays, Thursdays, and Saturdays, and figlie were free to practice on their own. Early in the rise of the figlie del coro, work and chores took most of their time, so they were only allowed an hour a day of music study. The most surprising feature was how
They lifted composers to unexplored heights. They were part of the bridge that carried music from Baroque composers to the classical masters: Bach (who transcribed Vivaldi’s concertos); Haydn (who composed specifically for one of the figlie, Bianchetta, a singer, harpist, and organist); and perhaps Mozart, who visited an ospedale with his father as a boy, and returned as a teen. The figlie’s skills on a vast array of instruments enabled musical experimentation so profound that it laid a foundation for the modern orchestra. According to musicologist Denis Arnold, the modernization of church music that occurred through the figlie was so influential that one of Mozart’s iconic sacred pieces, without the girls of the Venetian orphanages, “might never have been composed at all.”
The more confident a learner is of their wrong answer, the better the information sticks when they subsequently learn the right answer. Tolerating big mistakes can create the best learning opportunities.*
It is what it sounds like—leaving time between practice sessions for the same material. You might call it deliberate not-practicing between bouts of deliberate practice.
The economists suggested that the professors who caused short-term struggle but long-term gains were facilitating “deep learning” by making connections. They “broaden the curriculum and produce students with a deeper understanding of the material.” It also made their courses more difficult and frustrating, as evidenced by both the students’ lower Calculus I exam scores and their harsher evaluations of their instructors.
For example, say you plan to visit a museum and want to be able to identify the artist (Cézanne, Picasso, or Renoir) of paintings there that you have never seen. Before you go, instead of studying a stack of Cézanne flash cards, and then a stack of Picasso flash cards, and then a stack of Renoir, you should put the cards together and shuffle, so they will be interleaved. You will struggle more (and probably feel less confident) during practice, but be better equipped
The “desirable difficulty” coiner himself, Robert Bjork, once commented on Shaquille O’Neal’s perpetual free-throw woes to say that instead of continuing to practice from the free-throw line, O’Neal should practice from a foot in front of and behind it to learn the motor modulation he needed.
Desirable difficulties like testing and spacing make knowledge stick. It becomes durable. Desirable difficulties like making connections and interleaving make knowledge flexible, useful for problems that never appeared in training.
When a knowledge structure is so flexible that it can be applied effectively even in new domains or extremely novel situations, it is called “far transfer.” There is a particular type of thinking that facilitates far transfer—a type that Alexander Luria’s Uzbek villagers could not employ—and that can seem far-fetched precisely because of how far it transfers. And it’s a mode of broad thinking that none of us employ enough.
Each time he got stuck, Kepler unleashed a fusillade of analogies. Not just light, heat, odor, currents and boatmen, but optics of lenses, balance scales, a broom, magnets, a magnetic broom, orators gazing at a crowd, and more. He interrogated each one ruthlessly, every time alighting on new questions.
Most problems, of course, are not new, so we can rely on what Gentner calls “surface” analogies from our own experience.
“In the life we lead today,” Gentner told me, “we need to be reminded of things that are only abstractly or relationally similar. And the more creative you want to be, the more important that is.”
Those results are from a series of 1980s analogical thinking studies. Really, don’t feel bad if you didn’t get it.
In 2001, the Boston Consulting Group, one of the most successful in the world, created an intranet site to provide consultants with collections of material to facilitate wide-ranging analogical thinking.
The interactive “exhibits” were sorted by discipline (anthropology, psychology, history, and others), concept (change, logistics, productivity, and so on), and strategic theme (competition,
Dedre Gentner wanted to find out if everyone can be a bit more like Kepler, capable of wielding distant analogies to understand problems. So she helped create the “Ambiguous Sorting Task.”
Psychologist Kevin Dunbar began documenting how productive labs work in the 1990s, and stumbled upon a modern version of Keplerian thinking. Faced with an unexpected finding, rather than assuming the current theory is correct and that an observation must be off, the unexpected became an opportunity to venture somewhere new—and analogies served as the wilderness guide.
The labs in which scientists had more diverse professional backgrounds were the ones where more and more varied analogies were offered, and where breakthroughs were more reliably produced when the unexpected arose. Those labs were Keplers by committee. They included members with a wide variety of experiences and interests.
The more unusual the challenge, the more distant the analogies, moving away from surface similarities and toward deep structural similarities. In some lab meetings a new analogy entered the conversation every four minutes on average, some of them from outside of biology entirely.
Rather than expecting an ironclad a priori answer to “Who do I really want to become?,” their work indicated that it is better to be a scientist of yourself, asking smaller questions that can actually be tested—“Which among my various possible selves should I start to explore now?
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It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it’s hard to get an accurate picture of most jobs. . . . Most of the work I’ve done in the last ten years didn’t exist when I was in high school. . . . In such a world it’s not a good idea to have fixed plans.
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I propose instead that you don’t commit to anything in the future, but just look at the options available now, and choose those that will give you the most promising range of options afterward.
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He worked according to Ibarra’s new aphorism: “I know who I am when I see what I do.”
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Virtually every good thing in my life I can trace back to a misfortune, so my feeling is you don’t know what’s good and what’s bad when things happen. You do not know. You have to wait to find out.”
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“Outsider artists” are the self-taught jazz masters of visual art, and the originality of their work can be stunning.
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Katherine Jentleson, who in 2015 was appointed as a full-time curator of self-taught art at the High Museum of Art in Atlanta, told me that these artists typically started just by experimenting and doing things they liked, while working other jobs.
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Trying things is the answer to find your talent.”
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Meanwhile, his invitation to outsiders worked so well that it was spun off as an entirely separate company. Named InnoCentive, it facilitates entities in any field acting as “seekers,” paying to post “challenges” and rewards for outside “solvers.” A little more than one-third of challenges were completely solved, a remarkable portion given that InnoCentive selected for problems that had stumped the specialists who posted them.
the Einstellung effect, a psychology term for the tendency of problem solvers to employ only familiar methods even if better ones are available.
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Karim Lakhani, codirector of the Laboratory for Innovation Science at Harvard, had InnoCentive solvers rate problems on how relevant they were to their own field of specialization, and found that “the further the problem was from the solver’s expertise, the more likely they were to solve it.”
For the most intractable problems, “our research shows that a domain-based solution is often inferior,” according to Lakhani. “Big innovation most often happens when an outsider who may be far away from the surface of the problem reframes the problem in a way that unlocks the solution.”
Kaggle is like InnoCentive but specifically for posting challenges in the area of machine learning—artificial
As Karim Lakhani put it after his InnoCentive research, a key to creative problem solving is tapping outsiders who use different approaches “so that the ‘home field’ for the problem does not end up constraining the solution.” Sometimes, the home field can be so constrained that a curious outsider is truly the only one who can see the solution.
Yokoi was well aware of his engineering limitations. As one aficionado of game history put it, “He studied electronics at a time where the technology was evolving faster than the snow melts in sunlight.” Yokoi had no desire (or capability) to compete with electronics companies that were racing one another to invent some entirely new sliver of dazzling technology. Nor could Nintendo compete with Japan’s titans of traditional toys—Bandai, Epoch, and Takara—on their familiar turf.
Yokoi meant tech that was old enough to be extremely well understood and easily available, so it didn’t require a specialist’s knowledge. The heart of his philosophy was putting cheap, simple technology to use in ways no one else considered. If he could not think more deeply about new technologies, he decided, he would think more broadly about old ones. He intentionally retreated from the cutting edge, and set to monozukuri.
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possible. What if, Yokoi wondered, there was a game small enough that an adult could play it discreetly while commuting? He sat on the idea for a while, until one day when he was drafted to be the company president’s chauffeur.
What its withered technology lacked, the Game Boy made up in user experience. It was cheap. It could fit in a large pocket. It was all but indestructible. If a drop cracked the screen—and it had to be a horrific drop—it kept on ticking. If it were left in a backpack that went in the washing machine, once it dried out it was ready to roll a few days later. Unlike its power-guzzling color competitors, it played for days (or weeks) on AA batteries.
The Game Boy became the Sony Walkman of video gaming, forgoing top-of-the-line tech for portability and affordability. It sold 118.7 million units, far and away the bestselling console of the twentieth century.
In the Unusual (or Alternative) Uses Task, test takers have to come up with original uses for an object. Given the prompt “brick,” a test taker will generate familiar uses first (part of a wall, a doorstop, a weapon). To score higher, they have to generate uses that are conceptually distant and rarely given by other test takers, but still feasible. For the brick: a paperweight; a nutcracker; a theatrical coffin at a doll’s funeral; a water displacement device dropped in a toilet tank to use less per flush.
There is, to be sure, no comprehensive theory of creativity. But there is a well-documented tendency people have to consider only familiar uses for objects, an instinct known as functional fixedness. The most famous example is the “candle problem,” in which participants are given a candle, a box of tacks, and a book of matches and told to attach the candle to the wall such that wax doesn’t drip on the table below. Solvers try to melt the candle to the wall or tack it up somehow, neither of which work. When the problem is presented with the tacks outside of their box, solvers are more likely to view the empty box as a potential candle holder, and to solve the problem by tacking it to the wall
Unquestionably, Yokoi needed narrow specialists. The first true electrical engineer Nintendo hired was Satoru Okada, who said bluntly, “Electronics was not Yokoi’s strong point.” Okada was Yokoi’s codesigner on the Game & Watch and Game Boy. “I handled more of the internal systems of the machine,” he recalled, “with Yokoi handling more of the design and interface aspects.” Okada was the Steve Wozniak to Yokoi’s Steve Jobs.
Yokoi was the first to admit it. “I don’t have any particular specialist skills,” he once said. “I have a sort of vague knowledge of everything.” He advised young employees not just to play with technology for its own sake, but to play with ideas. Do not be an engineer, he said, be a producer. “The producer knows that there’s such a thing as a semiconductor, but doesn’t need to know its inner workings. . . . That can be left to the experts.” He argued, “Everyone takes the approach of learning detailed, complex skills. If no one did this then there wouldn’t be people who shine as engineers. . . . Looking at me, from the engineer’s perspective, it’s like, ‘Look at this idiot,’ but once you’ve got a couple hit products under your belt, this word ‘idiot’ seems to slip away somewhere.”
As the company grew, he worried that young engineers would be too concerned about looking stupid to share ideas for novel uses of old technology, so he began intentionally blurting out crazy ideas at meetings to set the tone.
In 2006, Nintendo’s president said that the Nintendo Wii was a direct outgrowth of Yokoi’s doctrine.
Given its basic hardware, the Wii was criticized as not innovative. Harvard Business School professor Clayton Christensen argued that it was actually the most important kind of innovation, an “empowering innovation”—one that creates both new customers and new jobs, like the rise of personal computers before it—because it brought video games to an entirely new (often older) audience.
“It understood that the barrier to new consumers using video game systems was the complexity of game play, not the quality of existing graphics.”
Eminent physicist and mathematician Freeman Dyson styled it this way: we need both focused frogs and visionary birds. “Birds fly high in the air and survey broad vistas of mathematics out to the far horizon,” Dyson wrote in 2009. “They delight in concepts that unify our thinking and bring together diverse problems from different parts of the landscape. Frogs live in the mud below and see only the flowers that grow nearby. They delight in the details of particular objects, and they solve problems one at a time.”
“If they say, ‘It’s a great idea, go for it, makes sense,’ what is the chance you’re the first person to come up
The specialists were adept at working for a long time on difficult technical problems, and for anticipating development obstacles. The generalists tended to get bored working in one area for too long. They added value by integrating domains, taking technology from one area and applying it in others.
the Carlton Award—the “Nobel Prize of 3M.”
polymaths had depth in a core area—so they had numerous patents in that area—but they were not as deep as the specialists. They also had breadth, even more than the generalists, having worked across dozens of technology classes.
Repeatedly, they took expertise accrued in one domain and applied it in a completely new one, which meant they were constantly learning new technologies. Over the course of their careers, the polymaths’ breadth increased markedly as they learned about “the adjacent stuff,” while they actually lost a modicum of depth.
“T-people like myself can happily go to the I-people with questions to create the trunk for the T,” she told me. “My inclination is to attack a problem by building a narrative. I figure out the fundamental questions to ask, and if you ask those questions of the people who actually do know their stuff, you are still exactly where you would be if you had all this other knowledge inherently. It’s mosaic building. I just keep putting those tiles together.
In high-uncertainty domains—where the fruitful questions themselves were less obvious—teams that included individuals who had worked on a wide variety of technologies were more likely to make a splash.
Darwin always juggled multiple projects, what Gruber called his “network of enterprise.” He had at least 231 scientific pen pals who can be grouped roughly into thirteen broad themes based on his interests, from worms to human sexual selection. He peppered them with questions. He cut up their letters to paste pieces of information in his own notebooks, in which “ideas tumble over each other in a seemingly chaotic fashion.” When his chaotic notebooks became too unwieldy, he tore pages out and filed them by themes of inquiry.
They are “π-shaped people” who dive in and out of multiple specialties. “Look for wide-ranging interests,” they advised. “Look for multiple hobbies and avocations.
Hamilton creator Lin-Manuel Miranda painted the same idea elegantly: “I have a lot of apps open in my brain right now.”
the Intelligence Advanced Research Projects Activity (IARPA), a government organization that supports research on the U.S. intelligence community’s most difficult challenges.
Eastman described the core trait of the best forecasters to me as: “genuinely curious about, well, really everything.”
The best forecasters view their own ideas as hypotheses in need of testing. Their aim is not to convince their teammates of their own expertise, but to encourage their teammates to help them falsify their own notions.
The most science-curious folk always chose to look at new evidence, whether or not it agreed with their current beliefs.
The best forecasters are high in active open-mindedness. They are also extremely curious, and don’t merely consider contrary ideas, they proactively cross disciplines looking for them.
He relentlessly attacked his own ideas, dispensing with one model after another, until he arrived at a theory that fit the totality of the evidence.
In wicked domains that lack automatic feedback, experience alone does not improve performance. Effective habits of mind are more important, and they can be developed.
involved ferociously dissecting prediction results in search of lessons, especially for predictions that turned out bad. They made a wicked learning environment, one with no automatic feedback, a little more kind by creating rigorous feedback at every opportunity.
exist. Reason without numbers was not accepted. In the face of an unfamiliar challenge, NASA managers failed to drop their familiar tools.
But with Challenger they were outside their usual bounds, where “can do” should have been swapped for what Weick calls a “make do” culture.
Roger Boisjoly’s unquantifiable argument that the cold weather was “away from goodness” was considered an emotional argument in NASA culture. It was based on interpretation of a photograph. It did not conform to the usual quantitative standards, so it was deemed inadmissible evidence and disregarded.
When Weick spoke with hotshot Paul Gleason, one of the best wildland firefighters in the world, Gleason told him that he preferred to view his crew leadership not as decision making, but as sensemaking. “If I make a decision, it is a possession, I take pride in it, I tend to defend it and not listen to those who question it,” Gleason explained. “If I make sense, then this is more dynamic and I listen and I can change it.” He employed what Weick called “hunches held lightly.”
the plan was ripe for revision as the team collectively made sense of a fire.
A team or organization that is both reliable and flexible, according to Weick, is like a jazz group.
There are fundamentals—scales and chords—that every member must overlearn, but those are just tools for sensemaking in a dynamic environment.
The strategy, strange as it sounds, is to send a mixed message. “Congruence” is
She found that the most effective leaders and organizations had range; they were, in effect, paradoxical.
be demanding and nurturing, orderly and entrepreneurial, even hierarchical and individualistic all at once. A level of ambiguity, it seemed, was not harmful. In decision making, it can broaden an organization’s toolbox in a way that is uniquely valuable.
In that case, the cure was fake Harvard Business Review research indicating that successful groups prioritize cohesion, loyalty, and finding common ground. Again, the HR managers became learning machines; they suddenly hewed closer to the traditional process when it had value, but continued to deviate readily when it didn’t, as NASA should have.
If he heard the same hunch twice, it didn’t take data for him to interrupt the usual process and investigate.
Von Braun started “Monday Notes”: every week engineers submitted a single page of notes on their salient issues. Von Braun handwrote comments in the margins, and then circulated the entire compilation.
Like Kranz, von Braun went looking for problems, hunches, and bad news. He even rewarded those who exposed problems.
“The chain of communication has to be informal,” he told me, “completely different from the chain of command.” He wanted a culture where everyone had the responsibility to protest if something didn’t feel right. He decided to go prospecting for doubts.
there is a difference between the chain of command and the chain of communication, and that the difference represents a healthy cross-pressure. “I warned them, I’m going to communicate with all levels of the organization down to the shop floor, and you can’t feel suspicious or paranoid about that,” he said.
it seemed a lot like the kind of incongruence Geveden worked to engender, and the kind that Captain Lesmes wielded: a differentiated chain of command and chain of communication that produced incongruence, and thus a healthy tension. An occasionally confusing but effective mix of strong formal and informal culture.
“On Saturday,” as Smithies put it, “you don’t have to be completely rational.”
What struck me as Smithies spoke was his joy in experimentation. Not just in his lab, but in his life.
“I try to teach people, ‘Don’t end up a clone of your thesis adviser,’” he told me. “Take your skills to a place that’s not doing the same sort of thing. Take your skills and apply them to a new problem, or take your problem and try completely new skills.”
An enthusiastic, even childish, playful streak is a recurring theme in research on creative thinkers. University of Manchester physicist Andre Geim employs (with no relation to Smithies) “Friday night experiments” (FNEs). It was a Friday night when he began the work that led to his 2000 Ig Nobel Prize.
When Geim was asked (two years before the Nobel) to describe his research style for a science newsletter, he offered this: “It is rather unusual, I have to say. I do not dig deep—I graze shallow. So ever since I was a postdoc, I would go into a different subject every five years or so.
Sometimes I joke that I am not interested in doing re-search, only search.”
there are pioneers who are working to balance the cult of the head start. They want to have it all—the mental meandering along with the wisdom of deep experience;
The reason Casadevall came to Hopkins, from a comfy post at New York City’s Albert Einstein College of Medicine, is that the new gig offered him the chance to create a prototype of what he thinks graduate science education, and eventually all education, should be.
The program, known as the R3 Initiative (Rigor, Responsibility, Reproducibility), starts with interdisciplinary classes that include philosophy, history, logic, ethics, statistics, communication, and leadership. A course titled “How Do We Know What Is True?” examines types of evidence through history and across disciplines. In “Anatomy of Scientific Error,” students are detectives, hunting for signs of misconduct or poor methods in real research, while also learning how errors and serendipity have led to momentous discoveries.
“But the provision of credit goes across all those markets. So we specialized products, we specialized regulation, and the question is, ‘Who looks across those markets?’ The specialized approach to regulation missed systemic issues.”
“Everyone acknowledges that great progress is made at the interface, but who is there to defend the interface?”
Luís A. Nunes Amaral, a Northwestern physicist who studies networks.
To recap: work that builds bridges between disparate pieces of knowledge is less likely to be funded, less likely to appear in famous journals, more likely to be ignored upon publication, and then more likely in the long run to be a smash hit in the library of human knowledge.
The further basic science moves from meandering exploration toward efficiency, he believes, the less chance it will have of solving humanity’s greatest challenges.
Casadevall’s overarching point is that the innovation ecosystem should intentionally preserve range and inefficiency. He is fighting an uphill battle. In
When engineer Bill Gore left DuPont to form the company that invented Gore-Tex, he fashioned it after his observation that companies do their most impactful creative work in a crisis, because the disciplinary boundaries fly out the window. “Communication really happens in the carpool,” he once said. He made sure that “dabble time” was a cultural staple.
shown that the more work eminent creators produced, the more duds they churned out, and the higher their chances of a supernova success. Thomas Edison held more than a thousand patents, most completely unimportant, and was rejected for many more. His failures were legion, but his successes—the mass-market light bulb, the phonograph, a precursor to the film projector—were earthshaking.
There is no well-defined formula or perfect system of feedback to follow. It’s like the stock market that way; if you want the sky highs, you have to tolerate a lot of lows. As InnoCentive founder Alph Bingham told me, “breakthrough and fallacy look a lot alike initially.” The question I set out to explore was how to capture and cultivate the power of breadth, diverse experience, and interdisciplinary exploration, within systems that increasingly demand hyperspecialization, and would have you decide what you should be before first figuring out who you are.
So, about that one sentence of advice: Don’t feel behind.
Compare yourself to yourself yesterday, not to younger people who aren’t you.
start planning experiments. Your personal version of Friday night or Saturday morning experiments, perhaps.
Approach your own personal voyage and projects like Michelangelo approached a block of marble, willing to learn and adjust as you go, and even to abandon a previous goal and change directions entirely should the need arise.
Even when you move on from an area of work or an entire domain, that experience is not wasted.
Finally, remember that there is nothing inherently wrong with specialization. We all specialize to one degree or another, at some point or other.
(France, which won the 2018 World Cup, overhauled its youth development decades ago to emphasize unstructured play at the expense of formal competitions, and to make room for late bloomers. A top youth footballer in France might play half as many formal games as an American peer.
Robin Hogarth’s fantastic book on learning environments is Educating Intuition (Chicago: University of Chicago Press, 2001).
For more depth on Shannon, see J. Soni and R. Goodman, A Mind at Play (New York: Simon & Schuster, 2017).
Her book, My Life in Leadership (San Francisco: Jossey-Bass, 2011), was a particularly useful source and contains the “a doctor, a lawyer, an aviatrix” quote.
The History of Nintendo, vol. 2, 1980–1991