This 19 min is some the best storytelling I have seen in a while. This made me feel things the same way Firewatch and Untitled Goose Game did; also published by Cabel.
you're going about your normal day when, suddenly, surprise! you've been pokémon mystery dungeon'd!
unfortunately, due to budget cuts, the pokémon assigning quiz has been canceled. instead, you must spin THE WHEEL, assigning you a random, unevolved, non-legendary and non-mythical pokémon. you must now go on some sort of world-saving adventure as this pokémon. good luck!
tell me in the tags what you rolled, and how you feel about it - for bonus points, you can spin the wheel again for (or just take your pick of) a pokémon to be your partner.
bonus rules:
you're not shiny unless the wheel tells you you're shiny
take your pick of regional forms and evolutions (for example, if you roll vulpix, it's up to you whether that means normal or alolan vulpix)
apply whatever logic you like with regards to gender
going to spend 2024 focusing on my fundamentals. i have some ideas for big pieces but i need to learn a few things before i can pull it off. thanks for everyone who followed me through the years! :-))
A Guide to Historically Accurate Regency-Era Names
I recently received a message from a historical romance writer asking if I knew any good resources for finding historically accurate Regency-era names for their characters.
Not knowing any off the top of my head, I dug around online a bit and found there really isn’t much out there. The vast majority of search results were Buzzfeed-style listicles which range from accurate-adjacent to really, really, really bad.
I did find a few blog posts with fairly decent name lists, but noticed that even these have very little indication as to each name’s relative popularity as those statistical breakdowns really don't exist.
I began writing up a response with this information, but then I (being a research addict who was currently snowed in after a blizzard) thought hey - if there aren’t any good resources out there why not make one myself?
As I lacked any compiled data to work from, I had to do my own data wrangling on this project. Due to this fact, I limited the scope to what I thought would be the most useful for writers who focus on this era, namely - people of a marriageable age living in the wealthiest areas of London.
So with this in mind - I went through period records and compiled the names of 25,000 couples who were married in the City of Westminster (which includes Mayfair, St. James and Hyde Park) between 1804 to 1821.
So let’s see what all that data tells us…
To begin - I think it’s hard for us in the modern world with our wide and varied abundance of first names to conceive of just how POPULAR popular names of the past were.
If you were to take a modern sample of 25-year-old (born in 1998) American women, the most common name would be Emily with 1.35% of the total population. If you were to add the next four most popular names (Hannah, Samantha, Sarah and Ashley) these top five names would bring you to 5.5% of the total population. (source: Social Security Administration)
If you were to do the same survey in Regency London - the most common name would be Mary with 19.2% of the population. Add the next four most popular names (Elizabeth, Ann, Sarah and Jane) and with just 5 names you would have covered 62% of all women.
To hit 62% of the population in the modern survey it would take the top 400 names.
The top five Regency men’s names (John, William, Thomas, James and George) have nearly identical statistics as the women’s names.
I struggled for the better part of a week with how to present my findings, as a big list in alphabetical order really fails to get across the popularity factor and also isn’t the most tumblr-compatible format. And then my YouTube homepage recommended a random video of someone ranking all the books they’d read last year - and so I present…
The Regency Name Popularity Tier List
The Tiers
S+ - 10% of the population or greater. There is no modern equivalent to this level of popularity. 52% of the population had one of these 7 names.
S - 2-10%. There is still no modern equivalent to this level of popularity. Names in this percentage range in the past have included Mary and William in the 1880s and Jennifer in the late 1970s (topped out at 4%).
A - 1-2%. The top five modern names usually fall in this range. Kids with these names would probably include their last initial in class to avoid confusion. (1998 examples: Emily, Sarah, Ashley, Michael, Christopher, Brandon.)
B - .3-1%. Very common names. Would fall in the top 50 modern names. You would most likely know at least 1 person with these names. (1998 examples: Jessica, Megan, Allison, Justin, Ryan, Eric)
C - .17-.3%. Common names. Would fall in the modern top 100. You would probably know someone with these names, or at least know of them. (1998 examples: Chloe, Grace, Vanessa, Sean, Spencer, Seth)
D - .06-.17%. Less common names. In the modern top 250. You may not personally know someone with these names, but you’re aware of them. (1998 examples: Faith, Cassidy, Summer, Griffin, Dustin, Colby)
E - .02-.06%. Uncommon names. You’re aware these are names, but they are not common. Unusual enough they may be remarked upon. (1998 examples: Calista, Skye, Precious, Fabian, Justice, Lorenzo)
F - .01-.02%. Rare names. You may have heard of these names, but you probably don’t know anyone with one. Extremely unusual, and would likely be remarked upon. (1998 examples: Emerald, Lourdes, Serenity, Dario, Tavian, Adonis)
G - Very rare names. There are only a handful of people with these names in the entire country. You’ve never met anyone with this name.
H - Virtually non-existent. Names that theoretically could have existed in the Regency period (their original source pre-dates the early 19th century) but I found fewer than five (and often no) period examples of them being used in Regency England. (Example names taken from romance novels and online Regency name lists.)
Just to once again reinforce how POPULAR popular names were before we get to the tier lists - statistically, in a ballroom of 100 people in Regency London: 80 would have names from tiers S+/S. An additional 15 people would have names from tiers A/B and C. 4 of the remaining 5 would have names from D/E. Only one would have a name from below tier E.
Women's Names
S+ Mary, Elizabeth, Ann, Sarah
S - Jane, Mary Ann+, Hannah, Susannah, Margaret, Catherine, Martha, Charlotte, Maria
A - Frances, Harriet, Sophia, Eleanor, Rebecca
B - Alice, Amelia, Bridget~, Caroline, Eliza, Esther, Isabella, Louisa, Lucy, Lydia, Phoebe, Rachel, Susan
C - Ellen, Fanny*, Grace, Henrietta, Hester, Jemima, Matilda, Priscilla
& Men were sometimes given a family surname (most often their mother's or grandmother's maiden name) as their first name - the most famous example of this being Fitzwilliam Darcy. If you were to combine all surname-based first names as a single 'name' this is where the practice would rank.
*Rank as a given name, not a nickname
+If you count Mary Ann as a separate name from Mary - Mary would remain in S+ even without the Mary Anns included
~Primarily used by people of Irish descent
^Primarily used by people of Scottish descent
>Primarily used by people of Welsh descent
I was going to continue on and write about why Regency-era first names were so uniform, discuss historically accurate surnames, nicknames, and include a little guide to finding 'unique' names that are still historically accurate - but this post is already very, very long, so that will have to wait for a later date.
If anyone has any questions/comments/clarifications in the meantime feel free to message me.
Methodology notes: All data is from marriage records covering six parishes in the City of Westminster between 1804 and 1821. The total sample size was 50,950 individuals.
I chose marriage records rather than births/baptisms as I wanted to focus on individuals who were adults during the Regency era rather than newborns. I think many people make the mistake when researching historical names by using baby name data for the year their story takes place rather than 20 to 30 years prior, and I wanted to avoid that. If you are writing a story that takes place in 1930 you don’t want to research the top names for 1930, you need to be looking at 1910 or earlier if you are naming adult characters.
I combined (for my own sanity) names that are pronounced identically but have minor spelling differences: i.e. the data for Catherine also includes Catharines and Katherines, Susannah includes Susannas, Phoebe includes Phebes, etc.
The compound 'Mother's/Grandmother's maiden name used as first name' designation is an educated guesstimate based on what I recognized as known surnames, as I do not hate myself enough to go through 25,000+ individuals and confirm their mother's maiden names. So if the tally includes any individuals who just happened to be named Fitzroy/Hastings/Townsend/etc. because their parents liked the sound of it and not due to any familial relations - my bad.
I did a small comparative survey of 5,000 individuals in several rural communities in Rutland and Staffordshire (chosen because they had the cleanest data I could find and I was lazy) to see if there were any significant differences between urban and rural naming practices and found the results to be very similar. The most noticeable difference I observed was that the S+ tier names were even MORE popular in rural areas than in London. In Rutland between 1810 and 1820 Elizabeths comprised 21.4% of all brides vs. 15.3% in the London survey. All other S+ names also saw increases of between 1% and 6%. I also observed that the rural communities I surveyed saw a small, but noticeable and fairly consistent, increase in the use of names with Biblical origins.
Sources of the records I used for my survey:
Ancestry.com. England & Wales Marriages, 1538-1988 [database on-line].
Ancestry.com. Westminster, London, England, Church of England Marriages and Banns, 1754-1935 [database on-line].
for those who don't speak academia: "according to our MRI machine, dead fish can recognise human emotions. this suggests we probably should look at the results of our MRI machine a bit more carefully"
So basically, in the psych and social science fields, researchers would (I don't know if they still do this, I've been out of science for awhile) sling around MRIs like microbiolosts sling around metagenomic analyses. MRIs can measure a lot but people would use them to measure 'activity' in the brain which is like... it's basically the machine doing a fuckload of statistics on brain images of your blood vessels while you do or think about stuff. So you throw a dude in the machine and take a scan, then give him a piece of chocolate cake and throw him back in and the pleasure centres light up. Bam! Eating chocolate makes you happy, proven with MRI! Simple!
These tests get used for all kinds of stuff, and they get used by a lot of people who don't actually know what they're doing, how to interpret the data, or whether there's any real link between what they're measuring and what they're claiming. It's why you see shit going around like "men think of women as objects because when they look at a woman, the same part of their brain is active as when they look at a tool!" and "if you play Mozart for your baby for twenty minutes then their imagination improves, we imaged the brain to prove it!" and "we found where God is in the brain! Christians have more brain activity in this region than atheists!"
There are numerous problems with this kind of science, but the most pressing issue is the validity of the scans themselves. As I said, there's a fair bit of stats to turn an MRI image into 'brain activity', and then you do even more stats on that to get your results. Bennett et. al.'s work ran one of these sorts of experiments, with one difference -- they used a dead salmon instead of living human subjects. And they got positive results. The same sort of experiment, the same methodology, the same results that people were bandying about as positive results. According to the methodology in common use, dead salmon can distinguish human facial expressions. Meaning one of two things:
Dead salmon can recognise human facial expressions. OR
Everyone else's results are garbage also, none of you have data for any of this junk.
I cannot overstate just how many papers were completely fucking destroyed by this experiment. Entire careers of particularly lazy scientists were built on these sorts of experiments. A decent chunk of modern experimental neuropsychology was resting on it. Which shows that science is like everything else -- the best advances are motivated by spite.
So, basically, for much of Tetris's history, people believed level 29 was the "last" level of Tetris, as the speed of the blocks would get so high that no human could do anything but lose; the blocks would go so fast that human hands physically could not control them. However, Tetris does not get any faster beyond that point, so if you're capable of playing level 29, you're capable of playing hypothetically infinitely.
Except Tetris, the original version for the NES, is not a hypothetical. It's a physical object, an item you can touch and hold, and it has limits. Many classic arcade-style video games have honest-to-god killscreens, where the game breaks so badly that it becomes completely unplayable. Pac-Man, famously, has a killscreen that garbles half of the playing field and doesn't spawn enough dots for the level to ever end. Tetris was assumed to be no exception, but because of the presumed-impossible difficulty of level 29, the community considered that to be Tetris's killscreen, and all high-leveled Tetris play centered around level 29 being the absolute end of your run, no matter what.
But, and if you've heard literally anything about people getting insanely good at retro games, you'll know what comes next. Of course, someone figures out how to control the game past level 29. In 2011, Thor Aackerlund discovered a technique now known as "hypertapping" (which is exactly what it sounds like, tapping very very fast) - and became the first person to play level 30.
But hypertapping wasn't enough. It was still stupidly difficult to get to, let alone past, level 30. Then this guy named Cheez shows up and finds that using an even more absurd technique, called "Rolling", which was even faster than hypertapping. People weren't just hitting level 30, but then 40, then 50, and then all the way into the 90s. Since all post-29 levels have the exact same speed, once they mastered rolling, they were pretty much good to play forever.
With levels 29+ conquered, now players could face the real killscreen of Tetris. A Tetris-playing AI got the first crash, but since it was playing a very slightly modified version (to show a larger score number, because the vanilla score counter didn't have enough digits), it only kinda-sorted counted. So the community picked apart the game's code to find where the game could hypothetically crash while completely unmodified - and found the current human record was not that far off.
So the entire community fucking scrambles to be the first person to crash Tetris, but then were confounded by another technically-not-game-ending-but-still-pretty-much-impossible-for-a-human bug; after level 138, the game stops choosing the colors for the blocks from where it's supposed to, leading it to display some truly heinously color palettes. Most of them are just ugly, but a few make the blocks you're placing next to invisible. (This was actually known about before the AI even crashed the game, and part of the reason the AI could get so much further than humans; it didn't need to visually see the blocks.)
Just next to invisible, though. You could still sorta see most of the blocks, and when you pass the level, the game pulls a new color palette, so if you can tough it out long enough to get 10 lines, you're probably gonna be able to continue your game for a while after that. It's annoying as hell, but not impossible. So, of course, the runners start getting past them and brushing up against the crashable levels.
And by runners, I mostly mean a 13 year old boy who goes by the online handle Blue Scuti. He'd skyrocketed into fame in the Tetris community relatively recently by achieving scores and levels that most adults couldn't even dream of, so of course he was among the first people to get past both impossible-palette levels, and he was able to keep going.
The game doesn't always crash in one specific spot, though. It just starts having a chance to crash after a certain point. You might have to perform some specific actions in specific windows of time to get it to crash on purpose, and it's much more likely that you'll lose control and lose your run before you achieve that goal.
Blue Scuti missed the first crash opportunity in his run. He was the first person to get that far at all, so it'd be a record regardless, but he was determined to win. He somehow keeps his cool, despite being a literal child with thousands of eyes on him (this was streamed on Twitch, of course), and never loses control of his stack, all the way until he reaches the next crash opportunity all the way on level 157.
And he fucking does it. He gets a single line clear in the middle of level 157 and the game just stops. It completely crashed. A 13 year old boy nicknamed Blue Scuti is the first human being in history to crash Tetris in this way. He is the first person ever to see Tetris's real killscreen. This game is over twice his age, and he is the first to kill it dead.
This kid fucking rules.
(if you want more detail, I learned basically all of the above from this video by aGameScout, please watch it!!)
[Video description: A compilation of clips from Star Trek: The Next Generation showing the instances in which Picard pulled his shirt. It is edited so that every time he pulls his shirt, his badge flies off of his uniform with a 'pop' sound. End description]
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