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The Most Distinctive Baby Names for Each of the Past 7 Generations

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Some names seem to have been around forever, and yet seem perfectly contemporary to name your child even today. Think James for boys or Mary for girls, which have seen high levels of use since the beginning of record-keeping. Other names, however, are just evocative of a specific era and can sometimes give strong clues to the person’s year of birth. Girls named Linda were most likely born in 1947, while odds are good that the average kindergarten boy you run into these days will have a name that ends in n.

Calculating the names that are most popular in a year or years is fairly straightforward, and can be done by looking at the Social Security Administration’s baby name database. However, if you want to find out the girls and boys names that are most distinctive to an era, looking at the absolute most popular names will not be enough to reveal those really generation-specific names like Maude or Elmer. To do this, I developed a measure of generational distinctiveness. This is calculated by dividing how often a name appears per sex within a generation (as defined within the Strauss-Howe generational theory) and dividing how often it appears per sex throughout the entire period from 1883 to 2015. The higher the score, the more generationally distinctive a name is. Below are the top three most distinctive girls and boys names of every generation based on this measure.

1. LOST GENERATION // 1883-1900

Girls: Maude, Effie, Minnie
Boys: Will, Harry, Charlie

Members of this generation were defined by coming of age during World War I and the 1920s. Gertrude Stein used the term in a conversation with Ernest Hemingway (“you are all a lost generation”). It was originally used to describe Hemingway and other writers of that era including F. Scott Fitzgerald and ee cummings.

The popularity of Maude is usually attributed to the 1855 poem "Maud" by Alfred Lord Tennyson. Effie, a diminutive for Euphemia, was likely inspired by Effie Gray, who was at the center of a publicized Victorian love triangle. Minnie (short for Wilhelmina) was more popular still in the 1880s, but stayed in use for longer, making it less distinctive to the Lost Generation. The most Shakespearean of names—William—was the #2 name for boys until 1909. However, its shortened form of Will was most unique to the Lost Generation. Harry peaked in 1889 at #8 for boys and had a steady but not rapid decline in subsequent decades. Charlie similarly piggy-backed off Charles, which was the #5 name for boys but stuck around for longer than the diminutive form.

2. G.I. GENERATION // 1901-1924

Girls: Gertrude, Mildred, Viola
Boys: Elmer, Chester, Clarence

Members of this generation came of age during the Great Depression and World War II.

Gertrude is the quintessential late 1800s/early 1900s girls name, used both in popular fiction and by well-known socialites. Mildred was the more popular overall, staying at #6 from 1912 to 1920, but remained in use for longer after the end of the generation than Gertrude did. Also from literature (specifically Shakespeare’s Twelfth Night), Viola was big in the early 1900s before sharply retreating. Looney Tunes character Elmer Fudd premiered in 1940, and odds are he’d be in his 40s by then if he was real, as the name peaked in the late 1800s but kept being given to boys into the early 1900s. Chester stayed in the top 50 most popular boys names throughout the 20th century’s first two decades, likely buoyed by the presidency of Chester A. Arthur. Clarence peaked in 1901 at #17 for boys and stayed in the top 30 for the whole generation, so was more popular than Elmer or Chester but didn’t decline as rapidly in subsequent decades.

3. SILENT GENERATION // 1925-1942

Girls: Dolores, Betty, Joan
Boys: Gene, Billy, Norman

Members of this generation are defined by the post World War II McCarthyist period. "Silent" is a reference to “working within the system” and not wanting to disturb the social order. The term was coined in a TIME magazine essay in 1951.

Few American-born girls are named Dolores today, but in the 1920s, the name became synonymous with beauty and glamor, first with model Kathleen Rose (stage name Dolores) and then with Mexican actress Dolores del Río. Like Dolores, Betty also peaked in 1930 but was much more popular overall that year at #2. However, Betty stuck around longer, making it less distinctive to the era. Joan peaked in 1932, likely driven by the success of actress Joan Crawford. Gene (short for Eugene) never truly broke out but was consistently around #70 for boys names for the entire generation. Billy did break out in 1930 likely due to the release of film Billy the Kid. Child actor Norman Chaney’s short movie career peaked around the time that the name Norman reached the height of its popularity.

4. BABY BOOMERS // 1943-1960

Girls: Linda, Judy, Gail
Boys: Gary, Larry, Dennis

Members of this generation were born in the “baby boom” years when the U.S. birth rate grew rapidly after World War II.

Inspired by a Buddy Clark song of the same name, Linda may well be the trendiest baby name of all time, and it was an immensely popular girls name for Baby Boomers. Judy—a diminutive of Judith—peaked and dipped around the same time as Linda, but was not as popular overall. Gail, short for Abigail, peaked in 1951. For boys, Gary peaked at #9 in 1954 after a decade or so of Oscar wins by actor Gary Cooper. Larry and Dennis attained their maximum popularity a few years prior to that.

5. GENERATION X // 1961-1981

Girls: Tammy, Tracy, Tonya
Boys: Todd, Scott, Chad

Members of this generation get their name from the 1991 novel Generation X: Tales for an Accelerated Culture by Douglas Coupland. A Pew Research report refers to Generation X as "America’s neglected 'middle child'" due to its position between the much larger Baby Boomer and Millennial generations.

Todd and Scott are two of the earliest popular examples of the use of what were once exclusively last names as first names. Chad peaked in 1972 as the #25 most popular boy name, and the vast majority of Chads were born during Generation X. Likewise with girls named Tammy, Tracy, and Tonya.


Girls: Brittany, Kelsea, Chelsea
Boys: Cody, Zachary, Kyle

Members of this generation are often the children of Baby Boomers, and have overtaken them as the largest population group. The name was popularized by the book Millennials Rising: The Next Great Generation by Neil Howe.

Babynamewizard’s Laura Wattenberg has pointed out that we have seen an increase in alternate spellings of names, but not necessarily an increase in names in recent years. Kelsea and Chelsea are examples of this. Brittany peaked as the third most popular girl’s name in 1989, and just about all the Brittanys are Millennials. Cody and Kyle are also first names that were originally last names. Zachary peaked as 12th most popular boy’s name in 1994 and probably owes its increased popularity to celebrities Robin Williams and John Denver, who picked this name for their kids starting in the early 1980s.


Girls: Addison, Nevaeh, Zoey
Boys: Ayden, Aiden, Jayden

Babies being born today would be counted as members of this generation. “Homeland” was picked as the name for the post-Millennial generation in a website contest hosted by Neil Howe. The term is in reference to the post-9/11 American political climate.

Robbie Gonzalez at io9 called the habit of ending boys names in n “one of the weirdest naming trends in American history," and names that rhyme with Aidan are a popular subset of these. This is evidenced by the top three boys names. Nevaeh is the word heaven spelled backwards and was popularized by musician Sonny Sandoval naming his daughter that in 2000. Zoey is a phonetic variant of the Greek name Zoe, which was popularized through use in several TV shows. Addison’s popularity stems from its rhyming with Madison, which became popular as a girl’s name after the movie Splash featured a mermaid that picked it as her own. It also continues the trend of last names becoming first names. In a nod to the Lost Generation, Madison’s original male meaning is “son of Maud.”

Source and Methodology: The source is the Social Security Administration’s baby names database and includes births through 2015 (most recent available). For this analysis, no births before 1883 were included. Name totals were grouped by sex for all names (two groups), as well as by sex within each of the seven most recent Strauss-Howe generations (14 sub-groups). These totals were then used to calculate the total incidence within each sex as well as the incidence within each sex by generation. Generational distinctiveness was calculated by dividing incidence by sex and generation by total incidence by sex. To ensure a level of relative popularity, the minimum threshold for a name’s inclusion in a sub-group is that it has to comprise at least .25 percent of total births within that sub-group.

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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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Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]