#What is Graph Database?

[dhirajmarketresearch]

[crystal-to-bloom]

Chapter 3.5

Grayson family x child dragon reader

𝟙, 𝟚, 𝟛, 𝟛.𝟝, 𝟜, 𝟝

Global Defense Agency — Deep Monitoring Sector

Rows of monitors flickered in dim blue light, casting pale reflections on Cecil Stedman’s face. He stood still, arms crossed, staring at the central screen — a live-updating diagram pulsing with energy readings.

— “Run it again,” he said.

A young analyst nervously tapped keys on his console. The graph reloaded, spreading like a heartbeat wave across the map.

— “Same irregularity, sir,” the tech said. “Localized around the Grayson residence. It’s not radioactive or magical. It’s... something else. The signature doesn’t match anything in the GDA database.”

— “But it’s alive,” Cecil muttered.

The tech hesitated. Then nodded.

— “Yes, sir. It’s moving. Breathing, even. Like a pulse. The weird part is, it started right after that energy drop Nolan brought back from his last mission”

Cecil didn’t respond immediately. He lit a cigarette, the ember burning softly in the low light. He didn’t like being wrong — and this time, he had the sinking feeling he was very right.

The screen flickered again. New data.

A spike.

— “There,” he said. “What the hell is that?”

The analyst’s voice was tight: “Temperature in the surrounding atmosphere dropped by nearly six degrees. In the middle of spring. It’s not just energy now — it’s affecting the environment”

Another pulse on the screen. Another chill.

Cecil narrowed his eyes.

— “And Nolan hasn’t said a damn word about it”

He turned away from the monitors, slowly walking toward a back console where a different feed was displayed — this one more secure. Experimental. Monitoring vitrumite-related anomalies within range of Earth.

Normally, it tracked Nolan.

Today, there were two dots. One small. One still unstable.

— “Well, well... Looks like someone brought home a souvenir” he murmured.

He took a slow drag from the cigarette, eyes narrowing as he watched the readings shift again. The smaller signal pulsed in bursts — unpredictable, but growing stronger.

Alive. Evolving.

Cecil exhaled smoke through his nose and muttered to himself:

— “Let’s see what you’re hiding, Grayson”

Underground GDA HQ — a few hours before Nolan returns home

Sleek, dim corridors. A low mechanical hum. Nolan’s cape stirred behind him as he entered the briefing room.

Cecil stood at the far end, arms crossed, flanked by holographic monitors. He gave Nolan a nod, expression unreadable behind that ever-present stubble and the surgical scars.

— “Appreciate you coming by so quickly”

— “You said it was urgent”

— “Mm. Let’s call it... timely” Cecil gestured toward one of the displays. “We picked up a signal. Low energy. Not Viltrumite, but... strange. Organic”

Nolan didn’t flinch, but his eyes narrowed slightly.

— “Where?”

Cecil zoomed the map with two fingers. A blip appeared — subtly placed over the general area of his home.

— “Near here. Kinda odd, right? No major incidents. No registered tech spikes. But definitely... something”

A pause.

Nolan said nothing.

Cecil gave a slow, casual shrug.

— “Could be nothing. Could be some new alien plant taking root in the backyard”

His tone was light, but his eyes were sharp, watching every muscle on Nolan’s face.

— “And you brought this to me because...?”

— “Because I trust your instincts more than most. And hey—since you just got back from that scorched ice-planet graveyard, I figured you’d be interested”

Nolan didn’t respond immediately. His voice, when it came, was neutral.

— “There was nothing there”

Cecil nodded.

— “Right. Empty. Frozen. Dead”

Another pause.

He smiled — small, but precise.

— “Still, funny thing. Radiation on your suit didn't match the known profile of that system. Some low-level bio-signatures we can’t quite match to anything. Guess space has its secrets”

Nolan’s eyes locked with his.

Cecil held his gaze.

Then he turned toward the screen again, tone deceptively casual.

— “Anyway. Just keeping you in the loop”

The message was clear:

"I’m watching. I don’t know yet what you did — but I will."

previous part 》 Chapter 3

Chapter 4

[kawaoneechan]

Project Special K, my "maybe this will be an Animal Crossing some day" thing that I mainly use to learn C++ has a Starbound-inspired asset system, much like many other things I made. As such, it works in much the same way:

On startup it takes a list of asset sources, sorts them by priority (I haven't added dependency graphs yet) and enumerates all the files in these assets. It then spends more time populating various databases from these files, like which items, species, and villagers there are.

That's it lol it's single-player only for now.

Even though I've written a function to forget certain files' existence in the asset system, there's a catch. Imagine two asset sources contain a file with the same relative path, let's say "foo.json", and they're different in content. During enumeration, the first file is put on the list, marked as coming from the first asset source. Some entries later, the second file is found and takes the first one's spot in the list, marking it as coming from the later source.

If I were to call ForgetVFS("foo.json"), I would not magically get the first version back. It was replaced, after all. That entry in the file list is removed, but it's the only entry listing "foo.json".

And that brings me back to the first PSK mockup screenshot that I made, the Content Filter screen.

Since PSK is beholden to the same limitations as SB that I literally just rambled about, clearly the content filter can't disable specific asset sources. It's all already loaded and processed after all.

But as the text in the mockup notes: "Unchecked species will never appear in your town as villagers. Any villager already there will remain." So if you uncheck the cranky personality and the hippopotamus species before first starting a game, no villagers of that personality and/or species will try to move in. But any cranky hippos already there will remain there until they're put in boxes.

This can be dynamic, in the middle of a running game. You could have a single cranky villager, disable that personality in the content filter, and no other cranky villagers will appear.

Or you could disable sea bass. Any bass already caught, stored in your inventory, in an aquarium on display in your house or the museum, or in storage, will still be there, but no more sea bass will spawn in the waters until you re-enable them.

That of course raises the question...

What happens when you remove an asset source whose contents are already used in your saved game?

My take? Since the saved game would refer to all of this by ID names that have to resolve to the actual things, it could fail gently. Items turn into fallback stuff (perfectly generic items as it were), and villagers whose IDs don't appear in the database, or whose species don't exist anymore, spontaneously move out, their houses replaced by cordoned-off "this space for sale" placeholders.

That was my take. But what's yours?

[patroxlos]

home base . ch8

"friends who are for the people" - 6.7k words

ultraman: rising (2024). kenji sato x reader

master post. ao3 link.

previous: ch7. "friends who use their phones in bed"

next: [SOON]

When you said you were busy with your own things, you meant it.

You have your own fun when Kenji is not around.

---

Dr. Onda has a special ability to be the most imposing person in the room.

Even in front of a long panel of the most important figures in Tokyo, he intimidates with the glare from his shades and his permanent frown. His second-in-command is much more approachable with his youthful face and calm but reliable demeanor, but Captain Aoshima can only do so much with his digestible powerpoint slides and well-crafted charts to lessen the heavy air of the room.

“...and you can see in this graph, that with your help, the KDF has managed to expand our fleet to tackle airborne kaiju. Our aviators have suffered less injuries due to the fortification of our aircrafts, and we are able to more efficiently terminate kaiju with our updated munitions. Any questions?” Captain Aoshima glances around the room to check whether the board was following.

They only nod, some casting glances towards Dr. Onda as he stood at the side to monitor his assistant’s presentation. The KDF’s board is composed of some of the most decorated war veterans, politicians, and arms dealers in the country, yet all are wary towards the senior researcher.

All except you.

“Captain, I have a question,” You say. You look up from the comprehensive board report they had passed around earlier, neat inside a plain black folio. “You discussed that the updated munitions arming the refurbished planes are necessary for more efficient ejection of projectiles, correct?”

“Yes, Director.”

You swallow.

You don’t think you earned the title compared to the others seated at the long table–this being your first board meeting, after all–but you let it go. They will sense weakness if you do not appear more confident. You continue your line of inquiry. “The report states that we have not introduced new projectiles in the armory within the quarter, yet based on the most recent kaiju attack, I have noticed that your fleets utilized non-lethal tranquilizers on the target. I reviewed the previous reports from the past five years and there has not been any mention about the research and development of such. May I ask why there was this omission?”

Murmurs broke out amongst your fellow board members. You keep your eyes trained at the commanding captain. He does not seem fazed at all by your question; he merely turns to look at Dr. Onda, who nods back, for permission to answer.

“Yes, Director. The tranquilizers were not mentioned in the quarterly review because they were not a recent development nor acquisition. They have been archived in our inventory for a better part of two decades. However, I can assure that our aviation ordnancemen checked prior to its use whether they are still effective as they were when they were first developed.”

You cross-check the provided digital database, manipulating the holographic screen. The inventory displays the potent tranquilizers. You skim over the document, pausing momentarily when you catch a line of text stating ‘Developer: Dr. Emiko Sato.’ You swipe away from the tab.

“Why take out old tranquilizers from storage for this specific kaiju?” You inquire.

“It was imperative for us to take this Kaiju alive.”

At the corner of your eye, you notice the Chairman of the Board stand up from his seat. Of course, as he is also Japan’s Minister of Defense, he has the most interest in increasing the KDF’s productivity. “And for what reason did you feel it was necessary to keep that kaiju alive?! I thought we agreed that the infrastructural costs outweigh the necessity to study these monsters?”

With a flick of his wrist, the Minister pushes one of the holographic screens to the center of the room. It plays the footage of that abnormally small, pink kaiju that ran through the streets a week prior. You see yourself on the screen get picked up, and you get phantom pains on your body as you remember how constricting the hold of that kaiju was. The stares of the other directors stab into your skin as they also recognize you from the footage.

Before anyone else can make a comment, Dr. Onda steps forward. The Minister falls back down on his chair, startled that the man has decided to finally speak after two hours in the boardroom.

“Captain Aoshima, thank you. I will take over the presentation for now.” He commands attention despite not raising his voice. Even if his eyes are covered, even you can feel the wuthering stare he sends towards the Minister. “Minister, while I respect your position as Chairman of the Board, I don’t think it is part of your responsibilities to scold my subordinates. Let your grievances out towards me.”

While the panel is silenced due to fear, you instead are stricken with respect for the older man. You appreciate how he takes care of his workers. Although, you still have your own job to do.

“Very well, Dr. Onda,” you speak up and everyone’s focus is now back on you. “Does this kaiju have anything to do with your current updates on Project Surrogate?”

He actually looks impressed, and you try not to look too pleased about his nod of approval. “Yes. I will move the presentation along towards it.”

The screen in front of you now presents a concise, bulleted summary of action points that Project Surrogate aims to achieve. This isn’t new to the panel, and the project needs no introduction. After all, it has been in development for the past five years, and most of taxpayer money being invested in the KDF has went towards it.

Project Surrogate��s main objective echoes that of the KDF’s original purpose: to locate Kaiju Island. It is hinged on the long-standing theory that Kaijus exhibit homing behavior towards their island of origin. Since it has been notoriously difficult to track adult Kaiju to the island, Project Surrogate hypothesizes that infant Kaiju might make it easier. The KDF has spent nearly half a decade trying to find proof of juvenile kaiju, until they finally stumbled onto a nest.

You have studied all of the declassified information on the project, yet even with your clearance level, you and the Board are kept out of the loop from Dr. Onda’s plans.

“We have seen this slide before,” you say, a bit frustrated as you stare at the screen. “Can we skip towards the project’s developments?”

Bowing slightly to your direction, he acquiesces to your request and switches to the photo of Gigantron, Queen of the Kaiju. Stepping forward, he begins his presentation. “Project Surrogate has made large progress since we have discovered the nest of Gigantron at the town of Oshima, by its coast. It has confirmed for us that kaiju, or in particular Gigantron, do not necessarily lay eggs nor reproduce exclusively in their island. The evidence in the surrounding area suggests that this is not the first time Gigantron has laid her eggs there.”

“Is it possible that Gigantron has natal homing?” You ignore the murmurs of confusion around you, but you do spot a few board members rolling their eyes at your display of proficiency.

You’re trying too hard to impress others, they think. Everything you do is performative. At your core, you’re just as dumb and vapid as everyone says you are.

“Indeed,” Dr. Onda nods your way. “This display of migratory behavior brings us closer towards finding Kaiju Island, as the infant would soon be instinctively motivated to fly away from our territory.”

The slide changes to the baby kaiju, and the pieces begin falling in place for the Board. The egg had hatched, and the kaiju has been alive for a few months at the moment. You raise another question. “Has the child been in KDF custody this entire time? Can you explain why it was allowed to roam the streets of Tokyo?”

“Unfortunately, the egg was stolen from us by Ultraman, and it had hatched under his control.”

Loud, outraged murmurs broke out amongst the board. Ultraman? Isn’t he supposed to be on our side?

 “Wait, Dr. Onda,” the Minister says. “So, even after the Tokyo fiasco, Ultraman still has custody over the kaiju?”

“Yes.”

A gruff-looking general shouts “Then doesn’t that mean Project Surrogate is a bust?”

“Hardly.” Even at the face of angry investors, Dr. Onda keeps his cool. He simply changes the slide to show an image of Ultraman cradling the kaiju against his chest while he hangs from the side of Tokyo Tower. Chills run down your spine. It is as if Ultraman was in the room himself, staring down everyone with a righteous fury.

Like a mother holding her child close, baring her teeth at the dangers that creep near.

“Due to Ultraman letting the kaiju loose on the streets, we have learned that the baby is capable of echolocation. It is possible that adult kaiju use echolocation at a frequency our sensors fail to pick up, but this child uses it as clear as day. Once we recapture the kaiju from Ultraman, we can set it free to the ocean and follow it towards Kaiju Island.”

As Dr. Onda finishes relaying the plan to the room, murmurs of approval soon broke the silence. The plan is reasonable, but you still remained unconvinced that he is telling you everything. You open the quarter report again, this time towards the expenditures for Project Surrogate.

“The plan does not seem clear to me yet, Dr. Onda. How sure are we that the KDF will be able to track the kaiju as it navigates through open waters?” You probe.

“I’m afraid I cannot disclose that for now,” He dodges your question.

“And what about the amount of lithium and uranium in the itemized budget? If you wanted to make bombs I would prefer it if you declare it.”

“We are making bombs, that is nothing new at the KDF. That is as much declaration I can make,” he dismisses your concern.

“So you do have a more thorough plan that you are not telling us about?”

“For two decades, the KDF and its Board of Directors have operated together with a strong sense of trust. You might not be familiar with it now, since this is your first meeting with us as a board member, but soon you will be.”

“But—” Shit. You are getting a little frazzled as he points out your inexperience. “Okay, that’s beside the point. What about Ultraman? The continuation of this project hinges on the KDF tracking his location, but he remains an elusive figure to the Japanese people.”

Dr. Onda gestures towards the Minister of Defense. “We will double down our efforts into tracking him, and we are encouraging the people to send to our tip line any sightings of the vigilante. Our chairman has been most helpful in declaring Ultraman persona non grata.”

“With much public backlash,” the Minister comments.

Another board member pipes in. “Ultraman is seen as a Japanese icon. The favorability of KDF has been declining steadily in the past several months, but it has been crashing to the gutter ever since the announcement that Ultraman is wanted.”

The meeting is getting derailed as the Board grows restless with the lack of direction in the KDF, exposed by you. You are starting to wonder whether you should have just sat there and listened like the others were.

Soon it ends, and everyone begins to shuffle out of the board room. You personally bow to each of the board members before they leave, half of them sizing you up but the rest giving you their blessings for being part of the team. Either way, your stomach turns.

You approach Captain Aoshima, and do the same bow towards him. “Thank you for that presentation, Captain. I look forward to seeing more of you in the future.”

“Likewise,” he returns the courtesy, though after he rises from his bow he fiddles with his pockets. “Actually, before you leave, ah– sorry, this is a bit unprofessional.”

You already have a feeling on what he is going to ask, but it still humors you slightly that he is breaking a bit of his respectful decorum that you know him for. You glance around the room, and the only people left are you, the captain and Dr. Onda. At least no one else is there to make fun of what you’re about to do. “Sure, we can take a photo.”

Aoshima brightens significantly. “Thank you, my daughter would be thrilled. Is it okay if you record a greeting as well? It’s her birthday soon.”

“She knows who I am?” Your eyes widen.

He thinks you’re being too modest. “She used to follow you before you deleted your accounts.”

“Then, it’s no problem! Sorry if I might seem a bit awkward. I haven’t done this in a while so I’m a bit rusty,” you laugh nervously.

You take his phone from his hands, angling the camera for a self-photo with him at your side. The recording goes just as smoothly, with you giving a small pep talk on how his daughter should focus on her studies. Captain Aoshima bows in gratitude, glowing with the excitement of a father who will do anything in the world for his kids.

Dr. Onda watches as his assistant leaves the room, leaving you and him alone. Swallowing your nervousness, you turn to the man and give a respectful bow. “Thank you for the meeting, Dr. Onda. The KDF remains safe in your hands.”

His silence makes you a bit more nervous. It is one thing for you to conduct a thorough interrogation during a quarterly board meeting, it is another making small-talk.

“I’ll…be going?” You try to have a smooth exit, but he raises his hand to signal you to stay.

“I was never fond of businessmen meddling with the organization,” he says, matter-of-fact.

“Well…Motsubishi prides itself in our social involvement—”

“Spare me the sales pitch, your father has done a lot of that when he served on the board,” he interrupts you. “I doubt you believe weapons development equates to welfare.”

“We only make it to the KDF,” you immediately rebut.

“Not fond of the dirtier sides of the business? Isn’t this what you’ve studied?” He raises an eyebrow at you.

You pocket your hands into your slacks. “I’m not entirely fond of profiting from war.”

“Would you call our fight against kaiju a war?”

“...You’re testing me.” You click your tongue. “Please, Dr. Onda.”

“You used to call me ‘Uncle’, when you played with Akiko.”

The room grows a little colder.

“Have you seen Hayao lately?” He changes topic, turning away from you.

“Can’t say I have, but I’ve seen him a couple of times since the incident,” you admit.

He gives a hum of acknowledgement.

“His knee is getting better, not that you asked,” you inform him, stepping forward to stand by his side. You look ahead as you speak. “I think…I think Kenji is taking care of him? Not sure, I didn’t get to confirm, but Emiko…before she disappeared…she told me that he flew all the way here just to take care of the Professor. It took a bit but I think they’re finally talking.”

It’s quiet again, for a moment. “And…Ultraman?”

“I…I don’t know who it is now, I’m sorry,” you don’t know why you are apologizing.

Dr. Onda merely sighs.

You turn to face him properly. “He doesn’t blame you, you know. For his knee.”

“I never asked for his forgiveness.” His face is steel, not betraying a hint of emotion. You see your worried face in the reflection of his shades. “Nor do I feel any sort of guilt.”

“You didn’t know he was Ultraman—”

“And even if I did, I still would have ordered the shot.”

You suck in a breath through your teeth.

“And I don’t make it a habit to shoot at superheroes. Ultraman was interfering with an official KDF extraction. It was necessary.” He remains stone-faced.

“You let him go.”

He walks away from you to another side of the room as he dismissively waves you off. “A mistake.”

“Admit it. You saw his crumpled body on the ground and you just let him go.” You follow, hot on his heels.

You nearly ram into him when he briskly stops in his tracks to turn to you. “I saw the crumpled body of my daughter’s killer and decided I wouldn’t stoop down to his level.”

“He is only one man.” You run a hand through your hair.

“Ultraman is not my enemy, but if he proves to be a nuisance that hinders us from achieving some peace in our shores, then I am not against making him one,” he booms. The conviction of his words might have shaken you, but you notice his shoulders sag slightly, defeated.

You cross your arms, tucking them close to your torso. “That’s…that’s one thing I agree on.”

“...Thank you.” You can tell he means it.

“The new Ultraman…he still needs to grow on me,” you divulge. “He kind of acts like some young hotshot. Seems pretty immature.”

“It’ll be easy to track him down then. But Hayao…he must have taught his new protégé all he knows about how to hide himself.”

“Doctor, you know that I am dedicated to help the KDF in anyway I can,” you affirm.

He raises an eyebrow at you. “Even if it means going against your tutor?”

“I think we and Ultraman have the same goal,” you answer. “We all want to be able to keep the people of this city safe. I don’t know how useful I can be to Ultraman’s cause but I know that I can affect real change here in the KDF. Like how Emiko used to.”

He’s a bit unsatisfied with your reply, but his lips almost twitch into a smile at your, as he calls it, misguided idealism. “You should also go by Doctor, then.”

You wince at the title.

“I’ll pass.” Even if you did recently graduate, it feels like a brag. It does not help that most of the internet thinks you’re lying when you discuss your educational background.

“Receiving a doctorate at 26 is no easy feat. You deserve to be acknowledged for it,” he coolly praises you. The flattery is getting to you a bit, but you still avoid letting it seep in.

“Doesn’t seem to matter much to others,” you dismiss his words. “I’ve tried so hard to distance myself from my old image. I deleted all my social media. I have placed full attention into preparing myself for what I’m about to inherit and I’m still…It still isn’t enough.”

Dr. Onda pushes his shoulders back. “The media play against you has been rampant since you were younger. It is hard to push back against such schemes.”

At eighteen, you formally entered society.

At eighteen, you had the world at your fingertips.

At eighteen, your father officially named you as his successor. He did not have much of a choice, given that you were his only one.

At eighteen, you made enemies who to this day are intent that you stay far away from the title Chief Executive Officer.

“My dad’s officially retiring within the month.”

“I’ve received the invitation to your welcoming gala,” he states. “Congratulations. While I’m not fond of public outings, since your father personally requested my appearance, I cannot say no.”

“I need a win.” Your arms fall to your sides, hands balling into fists. “I refuse to be driven out of the company my family built.”

His shades reflect a small flash of light. “Is this the purpose of our chat?”

“Project Surrogate. I need this to work. If the KDF can get stronger public approval I can solidify my position.”

“I can’t guarantee anything,” he warns you. “And I’m not doing this to satisfy anyone’s greed for power. This is for the people.”

“Because of the kaiju, I got separated from my best friend.” You place a hand over your heart. “And he grew up without a father. Believe me. My ambitions are here but I am fully committed to making this work.”

His hands clasp behind his back. “All I ask is for trust— an understanding, that I am using your investments for the greater good.”

You grin. “Where do I sign?”

A/N: hello … I’m not dead :D

And yes you are pro-KDF for now :D I think Dr. Onda is such a cool and well-written antagonist. DYK in early Ultraman he actually does just straight up kill the kaiju. From a utilitarian standpoint, kaiju are an invasive species. They’re not inherently bad but they don’t belong in the environment they are in. (I watch a lot of those lion fish exterminator tiktoks…)

If you saw on my Tumblr I posted a WIP snippet of what was supposed to go into this chapter, but ultimately I decided that maybe having a portion that focused solely on adding more context to who the reader is would help push the story forward. You go by a lot of different names around these parts! But next chapter would have too much Ken to make up for his absence here! The WIP I posted will be moved to ch10 as well :>

Since I’ve already finished a portion of the next chapter and it’s ready to publish in no time, as it’s a direct continuation from chapter 8’s flashback, here’s a snippet of its introduction so you know what’s in store!

——-

You hear a rapid knocking on the door.

You don’t register it at first, your head pounding from waking up too early. The only thing you can sense is Ken’s warm back against your bare chest, your hands around his waist. You press your face against the back of his neck, groaning at the hour. “Kenji, S’noisy.”

You feel his body shift, and he shrugs you off. “Y’face too cold…”

You just bite his shoulder and tug him closer. He lets you.

Soon, the knocking stops, but Kenji’s phone rings from the bedside table. Groaning, he blindly reaches for it to take the call, and you whine when he shifts in your hold. You realize that you won’t be able to get any sleep, so your eye cracks open to check the clock.

2:17 AM.

Now who—

“Kenji? Kenji are you awake? I’m outside your door. Please let me in.”

You both bolt up when you hear Emiko Sato’s voice from the phone. You slap his back to get him moving. “The sofa,” you hiss, lowering your voice.

Both of you struggle to keep quiet as you rush to find your clothes. Ken quickly pulls out the sofabed, and tosses rumpled blankets onto it to give an illusion that he’s been there the entire time. You find the bra he tossed away earlier on top of a nearby lamp. He grabs an air freshener can to spray lightly across the room— not too much for it to be obvious.

Ken opens the door just after you dive back into the covers, pretending to be asleep.

---

lmk if u want to be on the taglist for future chapters ty!

[crookedkryptonitebeliever]

Best and Worst of Both Worlds (Part 16)

tw: literally Yves watching ur every move, super suffocating stuff, Yandere shenanigans

Yeah ok u guys decided to lust for the creep, then the creep u shall receive

after this chapter i mean

Part 17

You told him your opinion on Montgomery.

"I see." He replied. Yves deadpanned at you before pulling you in for another kiss on the lips. Your face and the tips of your ears heat up, you're still not used to this yet.

He pulled away and chuckled at your bashfulness. Trying to cover your burning face with your hands is futile, as it only makes him tease you more.

__

"Call me if you need to go somewhere. I'm available for you any time." He slung the straps of his handbag around his shoulder, and Yves prepared his car keys in his hand.

You told him 'okay' as you're rubbing the last of his lipstick marks off using a piece of wet wipe.

He stroked your head, traced his fingertips down your jaw and finally held your chin. He tilted your head upwards and gave you a forehead kiss.

You whinged as you now have to wipe off one last print. He bid you goodbye before closing and locking the front door behind him.

Soon after, you dashed back into your room trying to escape your housemates hollering.

Days would go on like this: Yves breaks into your house using the spare key, scare the shit out of you when you open the door to see him standing there, receive adequate kisses, eat (br)lunch, talk for hours, landlord comes over to fix more stuff, eat dinner and finally, at around midnight- sometimes later, Yves would leave.

You would go to sleep almost immediately, but definitely looking forward to the next day.

He started coming in earlier and earlier, working on his things during times where you had nothing to say. You asked him about his work, he tried explaining it to you but you zoned out. It's so boring and complicated. Full of numbers, charts and graphs, you couldn't care less.

Needless to say, he cooked all your meals and did all your chores for you. You always protested, because it isn't his job and you should be responsible for taking out the trash or keeping yourself alive.

Yves would simply ignore you and do them anyway. If you're particularly worried, he assures you that it's some sort of a hobby of his to take good care of you. If you insist that he stops, he will guilt you; making you think that you're unnecessarily taking away part of his joy in this relationship when it isn't even harming you. So you just let him do what he wants, and you benefit from it greatly.

You really like him. He lets you take a nap on his lap while he types away at your desk, Yves listens to you ramble about your interests and occasionally adds his own fascinating commentary to it. You were astonished to know he has a whole database of random fandom trivia in his head. He washed your sheets and made your bed for you every morning.

He lets you hog his portable fan to yourself. But eventually, his bargaining powers lead to your landlord installing a ceiling air conditioner in your room. The best part? No rise in rent.

Yves gradually introduced you to a solid skincare routine. It started off with a simple face cleanser and moisturizer. Then he added toner to the regime. Then a weekly exfoliation and bi-weekly usage of sheet masks. It was hard for you to remember to do it or have the motivation, but Yves didn't mind maintaining your skin.

You just love the tingles you felt when he reclined you on your chair and he massages your face with the moisturizer. His fingers skillfully work to unravel you.

He made your house actually enjoyable to live in. You haven't gone out in three weeks and that didn't alarm you. You are glowing, physically fitter than ever, clean and most importantly, happy.

You have the drive to do so many things. Like learning a new language, learning to code, learning to knit or crochet, learning to draw... anything you wanted to do, Yves is always the expert to consult. He would buy the materials you need and teach you step by step. It made sense for him to be an extraordinary mentor, because you found out that he was also an exemplary lecturer at your university at one point.

You confirmed that he's currently a researcher, specifically, a research mathematician who works together with other branches of academia including but not limited to human Psychology, biology and sociology. The gist of his project has to do with predictive algorithms and probabilities. It's impressive and complicated, too bad you're not interested beyond what was described in a nutshell.

It's no secret that you look up to him, seeing that you're also a student looking to advance their education.

But it begs the question of his age. He has done so much in a short span of time. You wonder what his true age is.

But it's almost impossible to know because he would be offended whenever his age is brought up. It seems like he despised being perceived as ancient, which you understand. He probably comes from a time where youth is overly worshipped. You let it go, it isn't like his age affects you in any way.

It doesn't mean you didn't try searching him up. At first you suspected that he was lying because you couldn't find anything about him working at your university on the internet. But you sent an email to the administration asking about him. They came back with the confirmation that Yves is currently a hired researcher there. Strange that they knew who he is without knowing his last name. You guess there's only one Yves in the entirety of his faculty.

Speaking of names, you were shocked to find out that Yves didn't have a last name. After tons of relentless teasing from Yves for wanting to know his surname and a platitude of shame-induced face coverings later, you finally discovered he doesn't have one. This was bizarre to you, but Yves only told you off for being insensitive towards him, as not everyone has the privilege of a last name. It seems like a touchy subject, better not bring it up again.

Although it has been around a month since you think you first met Yves, you can safely say that you're madly in love with him. He is way more attentive and caring of you than anyone you ever met. Not even your parents or guardians can compare. Absolutely no one in your life has treated you this well.

There is that nagging feeling that something is very wrong. It wasn't a "He is going to leave you for someone better" feeling, it was more of a "what if Yves is secretly an organ harvester and he's healing you up to make a good price on the black market?"

But due to blind love, you forced yourself to brush it off as some implausible, impossible, silly thought.

...is it though? Yves does give off uncanny vibes sometimes no matter how suave and sexy he is. He has a lot of things to hide and the knowledge that you have of him is not enough to save you if he ever decides to steal a kidney or two.

Maybe this relationship isn't good for you. It keeps giving you inner turmoil to lose sleep over. This is definitely too good to be true, no one likes being a full time babysitter for their partner; this has to be a trap! You think you should quickly break it off with Yves before it gets too--

You were interrupted from your thoughts when you felt the chilly air from the air conditioner nip at your skin. The bliss of not being boiled alive by your own fluid trickles down your forehead.

You close your eyes and grin, letting the wind blow on your sweaty hair. This is lovely, you're so grateful to have Yves in your life. If you didn't have him here, you wouldn't be able to enjoy this temperate luxury.

Yves lets his focused gaze linger on your form for a few more seconds before replacing the remote back onto the holder. Yves pressed the button on his stopwatch, the beep was soft enough to go unnoticed.

He checked the temperature, the time and the humidity of your bedroom before logging them all into his computer. Yves turned his head to look at your position on the floor, you're splayed out like a rag as gusts of cold air strike your body.

He opened another file, which is the floorplan of this house. His eyes scanned the screen, noting down the exact coordinates of your precise location.

It would always be like this. You would start formulating thoughts and suspicions on Yves, spiral so much that you contemplated ending everything to protect yourself, then something interrupts your mind and eradicating the unwanted ideas entirely. Be it a change in temperature, texture, hunger or thirst. Sometimes, it's because you feel you hit your Yves-interaction/social quota for the day. So he would excuse himself and leave your house until you recovered.

He always comes back at the perfect time. Just right when you're starting to yearn for him. Yves ensures he never leaves for too long to make you think he's neglecting you. But he wouldn't come back too soon to make you go "yuck, this bitch's face again?"

Your signs could be as minuscule as a lower lip twitch, a brief, split-second movement of the eye, flaring of nostrils, positioning of your arms or even a change in the depth or rhythm of your breathing.

Or it could be an increase in heart rate, body temperature or sweat beading from your pores. Hell, it could even be the sound of you swallowing your spit or the smell of irritation.

They are all telltale signs that you're about to do or think about something undesirable due to overwhelm or underwhelm.

It's scary. He could just detect it with his superhuman senses. But ignorance is bliss, you still didn't know that he's puppeteering your environment accordingly. He would very much like to keep it that way.

Yves must admit, he has been careless. For the past three weeks, he failed to consider that his daily presence is wearing you down. It was his own fault for disregarding his calculations, Yves was originally only supposed to see you four times a week; that was the most optimal arrangement.

But he was enamoured, as desperate and feverish as you to be together. He just hides it impeccably well. Could you blame him, though? This was the first time you acknowledged him, the first time Yves got to kiss, touch, and hug you as freely as he wanted. The first time he gets to observe past the use of cameras- he does not need to hide. He gets to put his elaborate meal plans to use, you're eating his cooking, he's washing your clothes and you're accepting his backrubs. This is the closest so far to the ideal he wanted in his life with you. Anyone would be greedy in his situation.

But he flew too close to the sun like Icarus did. The wax melted off his wings and now he has to face the consequences that would have been avoided if only he had controlled himself better.

He's starting to notice you're not as positively receptive to his kisses as before. Sometimes even outright grimacing and shuddering in disgust when you think he's not looking. You spent a couple minutes longer in the bathroom, sometimes up to an hour, claiming you had stomach issues. But you didn't have problems with your digestion, your boyfriend made sure of that. He meticulously checks everything that goes into your mouth and he knows you didn't even pull your pants down. All you did was sit in the corner and scroll on your phone.

You did it just to escape from Yves and he's fully aware of that.

It devastated him when he went through your internet history:

Yves removed his reading glasses and pinched the bridge of his nose. He checked the timestamps, and you accessed the web since three in the morning.

"Why are my boyfriend's kisses and hugs gross to me now"

"Clingy boyfriend"

"How to tell my boyfriend to stop being clingy without hurting his feelings"

"How to say no to hugs"

"How to say no to hugs and kisses"

"How to say no"

"How to stop people pleasing"

"How to tell people that i dont want to see them but not forever just for a few days"

"Social battery"

"Therapists near me"

"Therapy price"

"is University counseling free"

"university counseling wait times"

"How to break up with my boyfriend"

"Is it rude to break up over text"

"Script for breaking up"

"Nice script for breaking up"

"Kind script for breaking up"

"Breaking up without hurting his feelings script"

"ChatGPT"

"Do retired lecturers have a habit of checking for plagiarism in their day to day life"

"Is AI generated content plagiarism"

"Jobs near me"

He knows he has no one but himself to blame. He had a plan all laid out, if he followed it to a Tee, it would have conditioned you to ultimately accept his intense love without complaints. He was supposed to give you a maximum of one kiss on the lips and four others somewhere else on your face. But gave you a whopping average of 76 kisses a day, 20 of which are on the lips; 1520% of the actual daily cap on kisses.

Likewise, he hugged you too much. Yves was only supposed to give you 12 hugs, lasting 8 seconds each at most, spaced throughout the day. However, you're in his arms for a total of 6 hours a day; 2250% of the maximum.

He is the first thing you see in the morning and the last face you perceive before sleeping, From before sunrise to past beyond sundown, you would be exposed to him; from 6am to 12am the next day; he would already be in your room before you're even awake. Subconsciously, you know he's there because the brain never stops working.

Of course, you would be sick of him! It doesn't matter if you came from an affectionate family or you turned out severely touch-starved, with extreme figures like these, anyone would be nauseated with his presence by the third week!

Yves fought back the urge to run the numbers back the fifth time. The cold hard facts are there, he made a grave mistake. Painstakingly recalculating everything is just a pathetic attempt to appease his denial that he lost control over himself.

He sighed and propped his head up by an elbow, absentmindedly fiddling on his calculator. Yves's eyes flitted up to the monitor. You're curled up into a ball on your bed, scrolling on your phone. Most likely to try and catch up with your own me-time. Yves could see pixels of bags forming under your eyes.

He shook his head and decided he must rectify this. Yves got up from his seat and sauntered out of his office, switching the lights off but leaving his surveillance equipment on.

Meanwhile, you yawned, closing your eyes and letting your phone slip next to you. Finally but reluctantly drifting off to sleep.

[mcyt-longfic-database-project]

Database publishing site: voting

SO! Once the database is finished, the idea is that I publish it somewhere for everyone to access! I want it to be easy to use, sorteable, and nice to look at.

We have TWO options! Google Sheets or small Obsidian based website.

Google sheets:

Pros:

Easy to set up (yay)

You can make your own copy

Easy to add stats and graphs

Cons:

Will look clunky and pretty big

Multiple people being on it at once might mess up the sorting for everyone

Lowkey looks ugly and while I love Google Sheets, it's a bit of a mess sometimes

Obsidian based website:

(example here)

Pros:

Looks nice, I can add pretty custom themes

It's a website so many people can be on it at once and it won't mess up

Can be accessed on any browser

Has cooler features like better sorting, tag management, wiki style links, etc. (i love the wiki styled links so much)

Cons:

Harder to set up (for me)

Doesn't have native stats or graphs, harder to set up too (still need to research this)

Not offline and can't make your own copy

So vote along!! What appeals more to you and your fanfiction reading needs?

[best-non-english-word-torunament]

What's the average language like?

This will be a giant of a post, because this is a subject that I really like. So much of what we think about language just isn't true when you look at the majority of them and I'm not even going into how the languages themselves are constructed, only the people speaking them, if that makes sense. It will make sense in a moment, I promise

First, let's discuss assumptions. When you think of the abstract idea of a language, what do you imagine?

How many speakers?

Where is it spoken geographically?

Do speakers of the language only speak that language or do they speak at least one other language? How many more languages?

Is the language tied to a state/country?

Is the language thriving or endangered?

In what domains is the language used? (home, school, higher education, administration and politics, in the workplace, in popular media...)

Is the language well documented and supported? Are there resources like dictionaries to look up words in, does google translate work for it, does Word/google docs work etc?

Is the language spoken or signed?

Is the language written down? Is it written down in a standardised way?

Do you see where I'm going with this? My perspective on what a language is has completely shifted after studying some linguistics, and this only covers language usage and spread, not how words and grammar work in different languages. Anyways, let's talk facts. (if no other sources are given the source is my uni lectures)

How many speakers does the average language have?

The median language has 7 600 native speakers.

7 600 people is the median number of speakers. Half the world's languages have more, half have less.

Most languages in this tournament have millions of speakers. But maybe that's relatively common? After all, half of the world's languages have more than 7 600 speakers. No.

94% of all languages have less than a million speakers.

Just so you know, big languages are far from the norm. There are 6700-6800 living languages in the world (according to ethnologue and glottolog, the two big language databases. I've taken the numbers for languages having a non-zero number of speakers and not being classed as extinct respectively. Both list more languages).

6% of 6700-6800 languages would be around 400 languages with more than a million speakers. Still a lot, but only a (loud) minority. It's enough to skew the average number of speakers per language upwards though. Counting 8 billion people and 6800 languages, that's almost 1.2 million people per language on average. The minority is Very loud.

Where are most languages spoken?

First of all, I'll present you with these graphs (data stolen from my professor's powerpoint) which I first showed in this post:

49% of all languages are spoken in Africa and Oceania, a disproportionately large amount compared to their population. On the other hand, Europe and Asia have disproportionally few languages, though Asia still has the largest amount of languages. Curious, considering Europe is often thought of as a place with many languages.

Sub-Saharan Africa is a very linguistically interesting place, but we need to talk about New Guinea. One island with 6.4 million people. Somehow over 800 languages. If you count the surrounding islands that's 7.1 million people and 1050 languages. Keep in mind that there are 6700-6800 languages in the world, so those 1050 make up more than a seventh of all languages. The average New Guinean language has less than 3000 speakers. Some are larger, but still less than 250 000 speakers. Remember, this is a seventh of all languages. It's a lot more common than the millions of speakers situation!

So yeah, many languages both in and outside New Guinea are spoken by few people in one or a few villages. Which is to say a small territory. But 7600 speakers spread over a big territory will have a hard time keeping their contact and language alive, so it's not surprising.

Moving on, lets talk about...

Bilingualism! Or multilingualism!

Is it common to speak two or more languages? Yes, it is. This is the situation in most of the world and has been the case historically. Fun fact: monolingual areas are uncommon historically and states which have become monolingual became so relatively recently.

One common thing is to learn a lingua franca in addition to your native language, a language that most people in the area know at least some of so you can use it to communicate with people speaking other languages than you.

As an example, I'm writing this in English which isn't my native language and some of you reading this won't have English as your native language either. Other examples are Swahili in large parts of eastern Africa and Tok Pisin in Papua New Guinea (the autonomous state, not the entire island).

Speakers of minority languages often have to learn the majority language in the country too. It's difficult to live somewhere where most daily life takes place in one language without speaking at least some of it. This is the case for native people in colonised countries, immigrants and smaller ethnic groups just to mention a few situations. All countries don't have majority languages, but some are larger, more influential and used for things like administration, business and higher education. It's common for schooling to transition from local languages to a larger language or lingua franca in countries with many languages.

Another approach than the lingua franca is learning the language of villages or towns surrounding you, which is very common in New Guinea and certainly other parts of the world too. It's not unusual to know multiple languages, in some places in sub-saharan Africa people speak five or six languages on a village level. Monolingualism is a weird outlier.

Speaking of monolingualism, let's move on to...

Languages and countries

This is a big talking point, mostly because it affected my view of language before I started thinking about it. First of all, I'm going to talk about the nation state and how it impacts languages within it and the way people view language (mostly because it's a source of misconceptions which fall apart as soon as you start to think about them, but if you don't the misconceptions will stay). Then I'll move on to countries with lots of languages and what happens there instead.

So, the nation state

The idea is that the people of a nation state share a common culture, history, values and other such things, the most important here being language. We can all agree that this type of nationalism has done lots of harm to various minorities and migrants all over the world, but it's still an idea that has had and still has a big impact on especially the western world. The section on nation states will focus on the West, because that's the area I know enough about to feel comfortable writing about in this regard.

How do you see this in common conceptions of language? It's in statements and thoughts like this: In France people speak French (but what about Breton? Basque? Corsican? Various Arabics? Some of the other 15 indigenous and 18 non-indigenous languages established in France? What about people speaking French outside of France?), in the US people speak English (but what about the 197 living indigenous languages? Or the 34 established non-indigenous languages? And the many extinct indigenous languages forcibly killed by the promotion of English?).

In X country people speak X, except for the people who don't, but let's ignore them and pretend everyone speaks X. Which most might actually do if it's the single national language that's used everywhere, it's common to learn a second language after all.

This is of course a simplified (and eurocentric) picture, as many countries either have multiple national languages or recognise at least some minority languages and give them legal protection and rights to access certain services in their languages (like government agency information). Bi-/multilingual signage is common and getting more common, either on a regional or a national level. Maybe because we're finally getting ready to move on from one language, one people, one state and give indigenous languages the minimum of availability they need to survive.

I wrote a long section about how nation states affect language, but I realised that veered way off topic and should be its own post. The short version is that a language might become more standardised simply by being tied to a country and more mobility among the population leading to less prominent dialects. There's also been (and still is) lots of opression and attempts to wipe out minority (often indigenous) languages in the name of national unity. Lots of atrocities have been comitted. Sometimes the same processes of language loss happen without force, just by economic pressure and misconceptions about bilingualism.

What does this have to do with the average language?

I simply want to challenge two assumptions:

That all languages are these big national languages tied to a country

That it's common that only one language is spoken within a country. If you look closer there will be smaller languages, often indigenous and often endangered. There are also countries in the West where multiple languages hold equal or similar status (just look at Switzerland and its four official languages)

Starting with the second point, let's take a look at how Europe is weird about language again

Majority languges aren't universal

I'm going to present you with a list of the 10 countries with the most living languages, not counting immigrant languages (list taken from wikipedia, which has Ethnologue as the source):

Papua New Guinea, 840 languages

Indonesia, 707 languages

Nigeria, 517 languages

India, 447 languages

China, 302 languages

Mexico, 287 languages

Cameroon, 274 languages

Australia, 226 languages

United states, 219 languages

Brazil, 217 languages

DR Congo, 212 languages

Philippines, 183 languages

Malaysia, 133 languages

Chad, 130 languages

Tanzania, 125 languages

This further challenges the idea of one country one language. Usually there's a lingua franca, but it's not always a native language and it's not always the case that most are monolingual in it (like the US or Australia, both of which have non-indigenous languages as widespread lingua francas). Europe is the outlier here. People might use multiple languages in their day to day lives, which are spoken by a varying number of people.

In some cases the indigenous or smaller local languages are extremely disadvantaged compared to one official language (think the US, Australia and China), while in other places like Nigeria, several larger languages are widely used in their respective areas alongside local languages, with English as the official language even though it's spoken by few people.

It's actually pretty common in decolonised countries to use the colonial language as an official language to avoid favoring one ethnic group and their language over others. Others simply don't have an official language, while South Africa's strategy is having 12 official languages (there are 20 living indigenous languages and 11 non-indigenous languages in total, and one of the official ones is English, so not all languages are official with this strategy either). Indonesia handled decolonisation by picking a smaller language (a dialect of Malay spoken by around 10% at the time, avoiding favouring the Javanese aka the dominating ethnic group by picking their language), modifying it, and started using it as the new national language Indonesian. It's doing very well, but at the cost of many smaller languages.

Going back to the list, it's also interesting to compare the mean speaker number (if every language in a country was spoken by the same amount of people) and the median speaker number (half have more speakers, half have less). The median is always lower than the mean, often by a lot. This means that the languages in a country don't have similar speaker numbers, so one or a few languages with lots of speakers drive the average upwards while the majority of languages are small. Just like for the entire world.

The US and Australia stand out with 12 and 10 median speakers, respectively. About 110 languages in the US have 12 or fewer native speakers. The corresponding number for Australia is 113 languages with 10 or fewer speakers. There are some stable languages with few speakers documented, but they have/had between 40 and 60 speakers, so those numbers point towards a lot of indigenous languages dying very soon unless revitalisation efforts succeed quickly. This brings us to the topic of...

Endangered languages

This is an interesting tool called glottoscope made by Glottolog which you can play around with and view data on endangered languages and description status (which is the next heading).

I'll pull out some numbers for you:

Remember those 6700 languages in Glottolog? That's living languages. How many extinct languages are listed?

936 extinct languages. That's ~12,5% of the languages we know of. (Glottolog doesn't include reconstructed languages like Proto-Indo-European, only languages where we either have enough remaining texts to conclude it was a separate language or reliable account(s) that conclude the same. We can only assume that there are thousands of undocumented languages hiding in history that we'll never know of)

How many more are on the way to become extinct?

Well, only 36% (2800 languages) aren't threatened, which means that the other 64% are either extinct or facing different levels of threat

What makes a language threatened? The short answer is people not speaking the language, especially when it's not passed down to younger generations. The long answer of why that happens comes later.

306 languages are listed as nearly extinct and 412 more as moribound. That means that only the grandparent generation and older speak it and the chain of transmission to younger generations has broken. These two categories include 9,26% of all known languages.

The rest of all languages either fall into the threatened or shifting category. The threatened category means that the language is used by all generations but is losing speakers. The shifting category refers to languages where the parental generation speaks the language but their children don't. In both of these cases it's easier to revive the language, since parents can speak to the children at home instead of having to rely on external structures (for example classes in the heritage language taught like foreign language classes in schools).

Where are languages threatened?

This map is also from glottoscope and can be found here. I recommend playing around with it, you can zoom in and hover over every dot to see which language it represents. The colours signify threat level: green for not threatened, light green for threatened, orange for shifting, red for moribound and nearly extinct, and black for extinct. I'll come back to the shapes later.

As you can see, language death is more common in certain areas, like Australia, Siberia, North America and the Amazon, but it's still spread over the entire world.

Why are languages going extinct?

There are two important dimensions to the vigorousness of a language: The first is the number of speakers who claim the language as their own and speak it with each other. No speakers means no language. If all speakers move to different places or assimilate by shifting to a dominant language in the area (sometimes for work opportunities or for their childrens' future work opportunities. Sometimes because of which language(s) schools are taught in or disinterest from the children in the language and culture. Sometimes migration of an ethnic group for various reasons leads to language shifts. There are many complex reasons to why the link of transmission can break)

The other dimension, which ties into the first one, is the number of situations in which a language is used. There are many domains a language can be used in, like at home, in school, in the workplace, in politics and administration, in higher education, for international communication, in religious activities, in popular media like movies and music etc. When a language is no longer or never used in a particular domain, it might lose the associated vocabulary. When it becomes confined to a singular domain like the home, the usage goes down. The home is usually the last place an endangered language is spoken.

Usage in a domain is a reason to speak or hear the language. It's a reason to keep it alive. People also forget or get worse at languages they don't use. That's why a common revitalisation tactic is producing movies, radio programmes, news reporting, books and other media in a dying language. It gives people both reason and opportunity to use their language skills. Which language is used in schools is also important, as it keeps basic vocabulary for sciences and explaining the world alive. Another revitalisation tactic is making up new words to talk about modern concepts, some examples are the Kaqchikel word rub'eyna'oj from this tournament or creating advanced math vocabulary in Māori.

What does endangered languages have to do with the average language?

Trying to get this post back on track, these are some key points:

64% of all documented languages are either extinct or facing some level of threat. That's the majority of all language

Even excluding the extinct languages, the majority of languages are threatened or worse

This means that the average language is facing a loss of speakers, some more disastrous than others. Being a minority language in an increasingly globalized world is dangerous

Describing a language

Are you able to look up words from your native language in a thesaurus or a dictionary? What about figuring out how a certain piece of grammar works if you're unsure? Maybe you don't need that for your native language, but what about a second language you're learning?

If your native language is English, there are lots of resources, like online and book dictionaries/thesauruses or an extensive grammar (a book about how English grammar works). There's also a plethora of websites and courses to learn English, and large collections of written text or transcribed speech. If a linguist wants to know something about the English language there's an abundance of material. If someone wants to learn English it's easy and courses are offered in most parts of the world.

For other languages, the only published thing might be a list of 20 words and their translation into English or another lingua franca.

Let's take a look at the same map as earlier, but toggled to show documentation status in colour and endangerment status with shapes:

Here, the green signifies a long grammar and the light green a grammar. Both are extensive descriptions of the grammar in a language, but they differ in length. A long grammar has to contain over 300 pages and a grammar over 150. Orange is another type of grammar, namely a grammar sketch. Those are brief overviews of the main grammatical features or features that may be of interest for linguists, typically between 20 and 50 pages. The purpose isn't to be a complete grammar, only a starting point.

The red dots can signify a lot of things, but what they have in common is that there's no extensive description of the grammar. In those cases, the best description of the language might be a list of which sounds it contains, a paper about a specific feature, a collection of texts or recordings, a dictionary, a wordlist (much shorter than dictionaries) or just a mention that it exists.

Why are grammars and descriptions even important?

The better described a language is, the easier it is to learn it and study it. For a community facing language loss, it might be helpful to have a pedagogical grammar or a dictionary to help teach the language to new generation. If the language becomes extinct people might still be able to learn and revive it from the documentation (like current efforts with Manx). It also makes sure unique words or grammatical features as well as knowledge encoded in the language isn't lost even if the language is. It's a way of preserving language, both for research and later learning.

What's an average amount of descripion then?

36,2% of all documented languages have either a grammar or a long grammar. That's pretty good actually

38,2% of all documented languages would be marked by a red dot on this map, meaning that more languages than that don't have any kind of grammar at all, maybe only as little as a short list of words

The remaining 25,6% have a grammar sketch

So as you see, the well documented languages are in minority. On the brighter side, linguists are working hard at describing languages and if they keep going at the same rate as they have since the 1950s, they'll reach the maximum level of description by 2084. Progress!

Tying into both description of languages and domains where language is used...

What about technology and language?

There are many digital tools for language. Translation services, spelling and grammar checks in word processors, unicode characters for different scripts and more. I'm going to focus on the first two:

Did you know that there are only 133 languages on google translate? 103 more are in the process of being added, but that's still a tiny percentage of all languages. As in 2% right now and 3,5% once these other languages are added going with the 6700 language estimation.

Of course, this is for the most part a limination with translation technology. You need translated texts containing millions of words to train the algorithms on and the majority of languages don't have that much written text, let alone translated into English. The low number still surprised me.

There are 106 official language packs for Windows 10 and I counted 260 writing standards you can use for spelling checks in Word. Most were separate languages, but lots were different ways to write the same language, like US or British English. That's a vanishingly small amount. But then again:

Do all languages have a written standard?

No. That much is clear. But how many do? I'll just quote Ethnologue on this:

"The exact number of unwritten languages is hard to determine. Ethnologue (25th edition) has data to indicate that of the currently listed 7,168 living languages, 4,178 have a developed writing system. We don't always know, however, if the existing writing systems are widely used. That is, while an alphabet may exist there may not be very many people who are literate and actually using the alphabet. The remaining 2,990 are likely unwritten."

(note that Ethnologue classes 334 languages without speakers as living, since their definition of living language is having a function for a contemporary language community. I think that's a bad definition and that means it differs from figures earlier in the post)

Spoken vs signed

My last point about average languages is about signed languages, because they're just as much of a language as spoken ones. One common misconception is that signed languages reflect or mimic the spoken language in the area, but they don't. Grammar works differently and some similarities in metaphor might be the only thing the signed language has in common with spoken language in the area.

Another common misconception is that there's only one sign language and that all signers understand each other. That's false, signed languages are just as different from each other as spoken languages, except for some tendencies regarding similarity between certain signs which often mimic an action (signs for eating are similar in many unrelated sign languages for example).

Glottolog lists 141 Deaf sign languages and 76 Rural sign languages, which are the two types of signed language that become entire languages. The difference is in reach.

Rural signs originate in villages with a critical amount of deaf people (around 6) that make up a fully fledged language with complete grammar to communicate. Often large parts of the village learn tha language as well. There are probably more than 76, that's just the ones the linguist community knows of.

What's called Deaf sign languages became a thing in the 1750s when a French guy named Charles-Michel de l'Épóe systematised and built onto a rural sign from Paris to create a national sign language which was then taught in deaf schools for all deaf children in France. Other countries took after the deaf school model and now there's 141 deaf sign languages, each connected to a different country. Much easier to count than spoken languages.

Many were made from scratch (probably building on some rural sign), but some countries recruited teachers from other countries that already had a natinonal sign language and learnt that instead. Of course they changed over time and with influence from children's local signs or home signs (rudimentary signs to communicate with hearing family, not complete languages), so now there's sign language families! The largest one unsurprisingly comes from LSF (Langue des Signes Française, the French one) and has 63 members, among them ASL.

What does this have to do with average languages? Well, languages don't have to be spoken, they can be signed instead. Even if they make up a small share of languages, we shouldn't forget them.

Now for some final words

Thank you for reading this far! I hope you found this interesting and have learned something new! Languages are exciting and this doesn't even go inte the nitty gritty of how different languages can be in their grammar, sounds and vocabulary. Lots of this seem self evident if you think about it, but I remember how someone pointing out facts like this truly shifted my perspective on what the language situation in the world truly looks like. The average language is a lot smaller and diffrerent from the common idea of a language I had before.

Please reblog this post if you liked it. I spent lots of time writing it because I'm passionate about this subject, but I'd love if it spread past my followers

[abalidoth]

what was your PhD dissertation about?

No idea what your level of math is so I'll answer this at a few levels.

Level 1:

Group theory is the study of symmetries of objects -- like how a rectangle is symmetric in the same way the letter H is symmetric, but not in the way the letter S is symmetric. I studied the symmetries of very specific sets of points that live in many-thousand-dimensional space.

Level 2:

I studied a type of object called an association scheme that can be seen either as related to a finite group, or a special type of graph, or a special matrix algebra. My specific research involved digging through a database of finite groups to find schemes with a particular useful property, and proving some generalizations of it.

Level 3:

An association scheme is a special kind of matrix algebra, that's closed not only under regular matrix multiplication but also elementwise matrix multiplication, and has a basis of 0-1 matrices. These basis elements form a series of graphs with special properties -- strongly regular graphs and distance regular graphs are both a type of association scheme. Association schemes can also be developed from a generously transitive group action (one where any pair of elements has a group element that switches them.)

My research involved proving properties from the character theory of finite groups that allows me to probe into the structures of association schemes, and dig through old databases of finite simple groups to prove shit. There's a number on my forearm tattoo (13056) that's the dimensionality of a new association scheme I discovered lurking inside the Co2 (Conway) finite group.

[jabbage]

When people talk about which fictional characters are most like their parents or have the same dynamic, I'm always like - Moominpapa and Moominmama, and Nigel and Mary-Anne Thornberry.

My Dad is the oddball eccentric who always has a new scheme, and my Mum is the calm practical pragmatist who says "Yes dear" and goes along with it.

Although they spend a lot of time together, my Mum and Dad have their own hobbies. My Mum likes to paint and birdwatch. My Dad is a super smart tech whizz and constantly latches onto a new weird project.

A modified Billy Bass. He made a tank for it, and has it singing about freedom, because he wanted it to be free.

He figured out how to make his own little spaceman action figures out of thermoplastics to recreate one he had as a child

He had a phase of renovating 1950s radios.

He's got a full suite of tools for measuring the weather, which then upload that information to a website he designed.

I know some people on this website will know me as the scary Furby lady, I want you to know it is genetic and my Dad is the one who has done truly scary things with Furbies.

Now, my Aunt and Uncle have a different dynamic to my Mum and Dad. They're kind of joined at the hip - they do art classes together, they play the ukulele together, they took up sailing lessons together.

And I know sometimes, my Mum is a little jealous.

So recently she said to my Dad, it would just be really nice if we had a hobby we could do together. My Dad agreed, and said he'd join her in her birdwatching. Ok. Great.

Two days later and my Dad emerges from the garage with a device which records birdsong and matches it against an internal database of recordings of common UK birds, and then transmits that information to the internet so that he can create maps and graphs and charts of all the birds they encounter.

And my Mum, aware that this is both a beautiful declaration of devotion to her and absolutely not what she wanted, just nods and says "Yes dear."

[anonymusbosch]

A specific piece of misinformation I'm responding to is the one originating from this headline:

(x)

spawning responses like

(x) which is... not entirely wrong

and

which is completely misunderstanding the original study - the Carbon Majors Database, CDP Carbon Majors Report 2017.

What this report absolutely does not say is "100 companies burn enough fossil fuels to produce 70% of emissions per year." It says something more like "70% of emissions since the 1988 can be traced back to extraction of fossil fuels by 100 producers." Those 100 producers include 36 state-owned companies, 7 state-owned producers, 41 public companies, and 16 private companies.

It also says that over half of industrial emissions since 1988 can be traced to just 25 producers. Of those 635 gigatons of emitted CO2, 59% come from state-owned producers, 32% from public companies, and 9% from private companies.

The largest shares here at the bottom of the graph are all state-owned producers: an aggregate of Chinese state-owned coal producers, Saudi Aramco (owned by the Saudi Arabian state), Gazprom (a Russian company with majority ownership by the state and partial public ownership), National Iranian Oil (unsurprisingly, nationally owned), and then finally we get to the first non-state-owned company (ExxonMobil).

The fraction is nearly identical for values for yearly emissions in 2015 - 59% of emissions since 1988 are tied to extraction by state-owned producers. Nonetheless:

"Emissions from investor-owned companies are significant: of the 30.6 GtCO2e of operational and product GHG emissions from 224 fossil fuel extraction companies, 30% is public investor-owned, 11% is private investor-owned, and 59% is state-owned."

There is absolutely immense responsibility on producers for extracting, marketing, and selling fossil fuels, and for (in several notable cases) deliberately covering up anthropogenic climate change as an outcome of fossil fuel use. But that extraction doesn't occur in a vacuum - fuels are extracted and burned for heat, for electricity, for transport, for industry.

The tweet about nothing changing if people didn't drive and used plastic straws is exactly wrong: fossil fuels are valuable to extract because they're used for everything around us. In the US, transportation accounts for ~29% of greenhouse gas emissions, and 57% of that is from personal vehicles. In 2016, the average passenger car fuel efficiency in the US was 22.1 miles per gallon; an electric car can easily get > 100 miles-per-gallon-equivalent, some as high as 142 miles-per-gallon-equivalent. Magically substituting all gas cars in the US alone for electric would slash nationwide emissions by 13 percentage points even if all those vehicles were powered by electricity made from fossil fuels! (Clearly there are a lot of gross assumptions and approximations there.) (Also, yes, magic wand car swaps aren't a thing we can do in real life, but it's what the tweet said, so I wanted to toss it in there.)

Like, there's a lot of complexity to global emissions - who's responsible, what levers we have to move things in a better direction, what any individual can or can't do. But this specific piece of misinformation or at least misrepresentation really ought to be excised from the record.

[trans-axolotl]

some of Eli Clare's writing about diagnosis feels very relevant to discussions on tumblr right now:

"It’s impossible to grapple with cure without encountering white Western medical diagnosis—ink on paper in the Diagnostic and Statistical Manual of Mental Disorders and the International Classification of Diseases, a process in the hands of doctors, a system of categorization. I want to read diagnosis as a source of knowledge, sometimes trustworthy and other times suspect. As a tool and a weapon shaped by particular belief systems, useful and dangerous by turns. As a furious storm, exerting pressure in many directions.

Simply put, diagnosis wields immense power. It can provide us access to vital medical technology or shame us, reveal a path toward less pain or get us locked up. It opens doors and slams them shut.

Diagnosis names the conditions in our body-minds, charts the connections between them. It holds knowledge. It organizes visceral realities. It draws borders and boundaries, separating fluid in the lungs from high blood pressure, ulcers from kidney stones, declaring anxiety attacks distinct from heart attacks, post-traumatic stress disconnected from depression. It legitimizes some pain as real; it identifies other pain as psychosomatic or malingering. It reveals little about the power of these borders and boundaries. Through its technology—x-rays, MRIs, blood draws, EKGs, CAT scans—diagnosis transforms our three-dimensional body-minds into two-dimensional graphs and charts, images on light boards, symptoms in databases, words on paper. It holds history and creates baselines. It predicts the future and shapes all sorts of decisions. It unleashes political and cultural forces. At its best, diagnosis affirms our distress, orients us to what’s happening in our body-minds, helps make meaning out of chaotic visceral experiences.

But diagnosis rarely stays at its best. It can also disorient us or de- value what we know about ourselves. It can leave us with doubts, questions, shame. It can catapult us out of our body-minds. All too often diagnosis is poorly conceived or flagrantly oppressive. It is brandished as authority, our body-minds bent to match diagnostic criteria rather than vice versa. Diagnosis can become a cover for what health care providers don’t understand; become more important than our messy visceral selves; become the totality of who we are.

...

It is impossible to name all the ways in which diagnosis is useful.

It propels eradication and affirms what we know about our own body-minds. It extends the reach of genocide and makes meaning of the pain that keeps us up night after night. It allows for violence in the name of care and creates access to medical technology, human services, and essential care. It sets in motion social control and guides treatment that provides comfort. It takes away self-determination and saves lives. It disregards what we know about our own body-minds and leads to cure.

Diagnosis is useful, but for whom and to what ends?"

-Eli Clare, Brilliant Imperfection pg 41-42, 48.

[cyberstudious]

what's it like studying CS?? im pretty confused if i should choose CS as my major xx

hi there!

first, two "misconceptions" or maybe somewhat surprising things that I think are worth mentioning:

there really isn't that much "math" in the calculus/arithmetic sense*. I mostly remember doing lots of proofs. don't let not being a math wiz stop you from majoring in CS if you like CS

you can get by with surprisingly little programming - yeah you'll have programming assignments, but a degree program will teach you the theory and concepts for the most part (this is where universities will differ on the scale of theory vs. practice, but you'll always get a mix of both and it's important to learn both!)

*: there are some sub-fields where you actually do a Lot of math - machine learning and graphics programming will have you doing a lot of linear algebra, and I'm sure that there are plenty more that I don't remember at the moment. the point is that 1) if you're a bit afraid of math that's fine, you can still thrive in a CS degree but 2) if you love math or are willing to be brave there are a lot of cool things you can do!

I think the best way to get a good sense of what a major is like is to check out a sample degree plan from a university you're considering! here are some of the basic kinds of classes you'd be taking:

basic programming courses: you'll knock these out in your first year - once you know how to code and you have an in-depth understanding of the concepts, you now have a mental framework for the rest of your degree. and also once you learn one programming language, it's pretty easy to pick up another one, and you'll probably work in a handful of different languages throughout your degree.

discrete math/math for computer science courses: more courses that you'll take early on - this is mostly logic and learning to write proofs, and towards the end it just kind of becomes a bunch of semi-related math concepts that are useful in computing & problem solving. oh also I had to take a stats for CS course & a linear algebra course. oh and also calculus but that was mostly a university core requirement thing, I literally never really used it in my CS classes lol

data structures & algorithms: these are the big boys. stacks, queues, linked lists, trees, graphs, sorting algorithms, more complicated algorithms… if you're interviewing for a programming job, they will ask you data structures & algorithms questions. also this is where you learn to write smart, efficient code and solve problems. also this is where you learn which problems are proven to be unsolvable (or at least unsolvable in a reasonable amount of time) so you don't waste your time lol

courses on specific topics: operating systems, Linux/UNIX, circuits, databases, compilers, software engineering/design patterns, automata theory… some of these will be required, and then you'll get to pick some depending on what your interests are! I took cybersecurity-related courses but there really are so many different options!

In general I think CS is a really cool major that you can do a lot with. I realize this was pretty vague, so if you have any more questions feel free to send them my way! also I'm happy to talk more about specific classes/topics or if you just want an answer to "wtf is automata theory" lol

[xaltius]

Unlocking the Power of Data: Essential Skills to Become a Data Scientist

In today's data-driven world, the demand for skilled data scientists is skyrocketing. These professionals are the key to transforming raw information into actionable insights, driving innovation and shaping business strategies. But what exactly does it take to become a data scientist? It's a multidisciplinary field, requiring a unique blend of technical prowess and analytical thinking. Let's break down the essential skills you'll need to embark on this exciting career path.

1. Strong Mathematical and Statistical Foundation:

At the heart of data science lies a deep understanding of mathematics and statistics. You'll need to grasp concepts like:

Linear Algebra and Calculus: Essential for understanding machine learning algorithms and optimizing models.

Probability and Statistics: Crucial for data analysis, hypothesis testing, and drawing meaningful conclusions from data.

2. Programming Proficiency (Python and/or R):

Data scientists are fluent in at least one, if not both, of the dominant programming languages in the field:

Python: Known for its readability and extensive libraries like Pandas, NumPy, Scikit-learn, and TensorFlow, making it ideal for data manipulation, analysis, and machine learning.

R: Specifically designed for statistical computing and graphics, R offers a rich ecosystem of packages for statistical modeling and visualization.

3. Data Wrangling and Preprocessing Skills:

Raw data is rarely clean and ready for analysis. A significant portion of a data scientist's time is spent on:

Data Cleaning: Handling missing values, outliers, and inconsistencies.

Data Transformation: Reshaping, merging, and aggregating data.

Feature Engineering: Creating new features from existing data to improve model performance.

4. Expertise in Databases and SQL:

Data often resides in databases. Proficiency in SQL (Structured Query Language) is essential for:

Extracting Data: Querying and retrieving data from various database systems.

Data Manipulation: Filtering, joining, and aggregating data within databases.

5. Machine Learning Mastery:

Machine learning is a core component of data science, enabling you to build models that learn from data and make predictions or classifications. Key areas include:

Supervised Learning: Regression, classification algorithms.

Unsupervised Learning: Clustering, dimensionality reduction.

Model Selection and Evaluation: Choosing the right algorithms and assessing their performance.

6. Data Visualization and Communication Skills:

Being able to effectively communicate your findings is just as important as the analysis itself. You'll need to:

Visualize Data: Create compelling charts and graphs to explore patterns and insights using libraries like Matplotlib, Seaborn (Python), or ggplot2 (R).

Tell Data Stories: Present your findings in a clear and concise manner that resonates with both technical and non-technical audiences.

7. Critical Thinking and Problem-Solving Abilities:

Data scientists are essentially problem solvers. You need to be able to:

Define Business Problems: Translate business challenges into data science questions.

Develop Analytical Frameworks: Structure your approach to solve complex problems.

Interpret Results: Draw meaningful conclusions and translate them into actionable recommendations.

8. Domain Knowledge (Optional but Highly Beneficial):

Having expertise in the specific industry or domain you're working in can give you a significant advantage. It helps you understand the context of the data and formulate more relevant questions.

9. Curiosity and a Growth Mindset:

The field of data science is constantly evolving. A genuine curiosity and a willingness to learn new technologies and techniques are crucial for long-term success.

10. Strong Communication and Collaboration Skills:

Data scientists often work in teams and need to collaborate effectively with engineers, business stakeholders, and other experts.

Kickstart Your Data Science Journey with Xaltius Academy's Data Science and AI Program:

Acquiring these skills can seem like a daunting task, but structured learning programs can provide a clear and effective path. Xaltius Academy's Data Science and AI Program is designed to equip you with the essential knowledge and practical experience to become a successful data scientist.

Key benefits of the program:

Comprehensive Curriculum: Covers all the core skills mentioned above, from foundational mathematics to advanced machine learning techniques.

Hands-on Projects: Provides practical experience working with real-world datasets and building a strong portfolio.

Expert Instructors: Learn from industry professionals with years of experience in data science and AI.

Career Support: Offers guidance and resources to help you launch your data science career.

Becoming a data scientist is a rewarding journey that blends technical expertise with analytical thinking. By focusing on developing these key skills and leveraging resources like Xaltius Academy's program, you can position yourself for a successful and impactful career in this in-demand field. The power of data is waiting to be unlocked – are you ready to take the challenge?

[am--f]

TikTok, Seriality, and the Algorithmic Gaze

Princeton-Weimar Summer School for Media Studies, 2024 Princeton University

If digital moving image platforms like TikTok differ in meaningful ways from cinema and television, certainly one of the most important differences is the mode by which the viewing experience is composed. We are dealing not only with fixed media nor with live broadcast media, but with an AI recommender system, a serial format that mixes both, generated on the fly and addressed to each individual user. Out of this series emerges something like a subject, or at least an image of one, which is then stored and constantly re-addressed.

TikTok has introduced a potentially dominant design for the delivery of moving images—and, potentially, a default delivery system for information in general. Already, Instagram has adopted this design with its Reels feature, and Twitter, too, has shifted towards a similar emphasis. YouTube has been providing video recommendations since 2008. More than other comparable services, TikTok places its proprietary recommender system at the core of the apparatus. The “For You” page, as TikTok calls it, presents a dynamically generated, infinitely scrollable series of video loops. The For You page is the primary interface and homepage for users. Content is curated and served on the For You page not only according to explicit user interactions (such as liking or following) or social graphs (although these do play some role in the curation). Instead, content is selected on the basis of a wider range of user behavior that seems to be particularly weighted towards viewing time—the time spent watching each video loop. This is automatic montage, personalized montages produced in real time for billions of daily users. To use another transmedial analogy—one perhaps justified by TikTok’s approximation of color convergence errors in its luminous cyan and red branding—this montage has the uncanny rhythm of TV channel surfing. But the “channels” you pass through are not determined by the fixed linear series of numbered broadcast channels. Instead, each “channel” you encounter has been preselected for you; you are shown “channels” that are like the ones you have tended to linger on.

The experience of spectatorship on TikTok, therefore, is also an experience of the responsive modeling of one’s spectatorship—it involves the awareness of such modeling. This is a cybernetic loop, in effect, within which future action is performed on the basis of the past behavior of the recommender system as it operates. Spectatorship is fully integrated into the circuit. Here is how it works: the system starts by recommending a sequence of more or less arbitrary videos. It notes my view time on each, and cross-references the descriptive metadata that underwrites each video. (This involves, to some degree, internal, invisible tags, not just user-generated tags.) The more I view something, the more likely I am to be shown something like it in the future. A series of likenesses unfolds, passing between two addresses: my behavior and the database of videos. It’s a serial process of individuation. As TikTok puts it in a 2020 blog post: these likenesses or recommendations increasingly become “polished,” “tailored,” “refined,” “improved,” and “corrected” apparently as a function of consistent use over time.

Like many recommender systems—and such systems are to be found everywhere nowadays—the For You algorithm is a black box. It has not been released to the public, although there seem to have been, at some point, promises to do this. In lieu of this, a “TikTok Transparency Center” run by TikTok in Los Angeles (delayed, apparently, by the 2020 COVID-19 pandemic) opened in 2023. TikTok has published informal descriptions of the algorithm, and by all accounts it appears to be rather straightforward. At the same time, the algorithm has engendered all kinds of folk sciences, superstitions, paranoid theories, and magical practices. What is this algorithm that shows me such interesting, bizarre, entertaining, unexpected things? What does it think I want? Why does it think I want this? How does this algorithm sometimes seem to know me so well, to know what I want to see? What is it watching me watch? (From the side of content creators, of course, there is also always the question: what kind of content do I need to produce in order to be recognized and distributed by the algorithm? How can I go viral and how can I maximize engagement? What kinds of things will the algorithm want to see? Why is the algorithm not seeing me?)

These seem to be questions involving an algorithmic gaze. That is to say: there is something or someone watching prior to the actual instance of watching, something or someone which is beyond empirical, human viewers, “watching” them watch. There is something watching me, whether or not I actually make an optical image of myself. I am looked at by the algorithm. There is a structuring gaze. But what is this gaze? How does it address us? Is this the gaze of a cinematic apparatus? Is it the gaze we know from filmtheory, a gaze of mastery with which we are supposed to identify, a gaze which hails or interpellates us, which masters us? Is it a Foucauldian, panoptic gaze, one that disciplines us? 

Any one of us who uses the major platforms is familiar with how the gaze of the system feels. It a gaze that looks back—looks at our looking—and inscribes our attention onto a balance sheet. It counts and accounts for our attention. This account appears to be a personalized account, a personalized perspective. People use the phrase “my TikTok algorithm,” referring to the personalized model which they have generated through use. Strictly speaking, of course, it’s not the algorithm that’s individualized or that individuates, but the model that is its product. The model that is generated by the algorithm as I use it and as it learns from my activity is my profile. The profile is “mine” because I am constantly “training” it with my attention as its input, and feel a sense of ownership since it’s associated with my account, but the profile is also “of me” and “for me” because it is constantly subjecting me to my picture, a picture of my history of attention. Incidentally, I think this is precisely something that Jacques Lacan, in his 1973 lecture on the gaze in Seminar XI, refers to as a “bipolar reflexive relation,” the ambiguity of the phrase “my image.” “As soon as I perceive, my representations belong to me.” But, at the same time, something looks back; something pictures me looking. “The picture, certainly, is in my eye. But I am in the picture.”

On TikTok, the picture often seems sort of wrong, malformed. Perhaps more often than not. Things drift around and get stuck in loops. The screen fills with garbage. As spectators, we are constantly being shown things we don’t want any more of, or things we would never admit we want, or things we hate (but cannot avoid watching: this is the pleasurable phenomenon of “cringe”). But we are compelled to watch them all. The apparatus seems to endlessly produce desire. Where does this desire come from? Is it from the addictive charge of the occasional good guess, the moment of brief recognition (the lucky find, the Surrealist trouvaille: “this is for me”)? Is it the promise that further training will yield better results? Is it possible that our desire is constituted and propelled in the failures of the machine, in moments of misrecognition and misidentification in the line of sight of a gaze that evidently cannot really see us? 

In the early 1970s, in the British journal Screen, scholars such as Laura Mulvey, Colin MacCabe, and Stephen Heath developed a film-theoretical concept of the gaze. This concept was used to explain how desire is determined, specified, and produced by visual media. In some ways, the theory echoes Lacan’s phenomenological interest in “the pre-existence to the seen of a given-to-be-seen” (Seminar XI, 74). The gaze is what the cinematic apparatus produces as part of its configuration of the given-to-be-seen. 

In Screen theory, as it came to be known, the screen becomes a mirror. On it, all representations seem to belong to me, the individual spectator. This is an illusion of mastery, an imaginary relation to real conditions of existence in the terms of the Althusserian formula. It corresponds to the jubilant identification that occurs in a moment in Lacan’s famous 1949 paper “The Mirror Stage as Formative of the I Function as Revealed in Psychoanalytic Experience,” in which the motor-challenged infant, its body fragmented (en morceaux) in reality, discovers the illusion of its wholeness in the mirror. The subject is brought perfectly in line with this ideal-I, with this spectacle, such that what it sees is simply identical to its desire. There is convergence. To slightly oversimplify: for Screen theory, this moment in mirror stage is the essence of cinema and ideology, or cinema as ideology. 

Joan Copjec, in her essay “The Orthopsychic Subject,” notes that Screen theory considered a certain relationship of property to be one of its primary discoveries. The “screen as mirror”: the ideological-cinematic apparatus produces representations which are “accepted by the subject as its own.” This is what Lacan calls the “belong to me aspect so reminiscent of property.” “It is this aspect,” says Copjec, speaking for Screen theory, “that allows the subject to see in any representation not only a reflection of itself but a reflection of itself as master of all it surveys. The imaginary relation produces the subject as master of the image. . . . The subject is satisfied that it has been adequately reflected on the screen. The ‘reality effect’ and the ‘subject effect’ both name the same constructed impression: that the image makes the subject fully visible to itself” (21–22). 

According to Copjec, “the gaze always remains within film theory the sense of being that point at which sense and being coincide. The subject comes into being by identifying with the image’s signified. Sense founds the subject—that is the ultimate point of the film-theoretical and Foucauldian concepts of the gaze” (22).

But this is not Lacan’s gaze. The gaze that Lacan introduces in Seminar XI is something much less complete, much less satisfying. The gaze concept is not exhausted by the imaginary relation of identification described in Screen theory, where the subject simply appropriates the gaze, assumes the position created for it by the image “without the hint of failure,” as Copjec puts it. In its emphasis on the imaginary, Screen theory neglects the symbolic relation as well as the issue of the real.

In Seminar XI, Lacan explicates the gaze in the midst of a discussion on Sartre and Merleau-Ponty. Again, Lacan’s gaze is something that pre-exists the seeing subject and is encountered as pre-existing it: “we are beings who are looked at, in the spectacle of the world” (75). But—and this is the crucial difference in emphasis—it is impossible to look at ourselves from the position of this all-seeing spectacle. The gaze, as objet a in the field of the visible, is something that in fact cannot be appropriated or inhabited. It is nevertheless the object of the drive, a cause of desire. The gaze “may come to symbolize” the "central lack expressed in the phenomenon of castration” (77). Lacan even says, later in the seminar, that the gaze is “the most characteristic term for apprehending the proper function of the objet a” (270). As objet a, as the object-cause of desire, the gaze is said to be separable and separated off from the subject and has only ever existed as lack. The gaze is just all of those points from which I myself will never see, the views I will never possess or master. I may occasionally imagine that I have the object, that I occupy the gaze, but I am also constantly reminded of the fact that I don’t, by images that show me my partiality, my separation. This is the separation—between eye and gaze—that manifests as the drive in the scopic field. 

The gaze is a position that cannot be assumed. It indicates an impossible real. Beyond everything that is shown to the subject, beyond the series of images to which the subject is subjected, the question is asked: “What is being concealed from me? What in this graphic space does not show, does not stop not writing itself?” This missing point is the point of the gaze. “At the moment the gaze is discerned, the image, the entire visual field, takes on a terrifying alterity,” says Copjec. “It loses its ‘belong-to-me aspect’ and suddenly assumes the function of a screen” (35). We get the sense of being cut off from the gaze completely. We get the sense of a blind gaze, a gaze that “is not clear or penetrating, not filled with knowledge or recognition; it is clouded over and turned back on itself, absorbed in its own enjoyment” (36). As Copjec concludes: “the gaze does not see you” (36).

So the holes and stains in the model continuously produced by the TikTok algorithm—those moments in which what we are shown seems to indicate a misreading, a wrong guess—are those moments wherein the gaze can be discerned. The experience is this: I am watching a modeling process and engaging with the serial missed encounters or misrecognitions (meconnaissance—not only misrecognition but mistaken knowledge—mis-knowing) that the modeling process performs. The Lacanian point would simply be the following: the situation is not that the algorithm knows me too well or that it gives me the illusion of mastery that would be provided by such knowledge. The situation is that the algorithm may not know or recognize me at all, even though it seems to respond to my behavior in some limited way, and offers the promise of knowing or recognizing me. And this is perhaps the stain or tuche, the point at which we make contact with the real, where the network of signifiers, the automaton, or the symbolic order starts to break down. It is only available through the series, through the repeated presentation of likenesses.

As Friedrich Kittler memorably put it, “the discourse of the other is the discourse of the circuit.” It is not the discourse of cinema or television or literature. Computational recommender systems operating as series of moving image loops seem to correspond strangely closely to the Lacanian models, to the gaze that is responsive yet absent, perceptive yet blind, desired yet impossible, perhaps even to the analytic scene. Lacan and psychoanalysis constantly seemed to suggest that humans carry out the same operations as machines, that the psyche is a camera-like apparatus capable of complicated performance, and that the analyst might be replaced with an optical device. Might we substitute recommender media for either psyche or analyst? In any case, it’s clear that the imaginary register of identification does not provide a sufficient model for subjectivity as it is addressed by computational media. That model, as Kittler points out, is to be found in Lacan’s symbolic register: “the world of the machine.”

[digitaldetoxworld]

Data Analysis: Turning Information into Insight

 In nowadays’s digital age, statistics has come to be a vital asset for businesses, researchers, governments, and people alike. However, raw facts on its personal holds little value till it's far interpreted and understood. This is wherein records evaluation comes into play. Data analysis is the systematic manner of inspecting, cleansing, remodeling, and modeling facts with the objective of coming across beneficial information, drawing conclusions, and helping selection-making.

What Is Data Analysis In Research 

What is Data Analysis?

At its middle, records analysis includes extracting meaningful insights from datasets. These datasets can variety from small and based spreadsheets to large and unstructured facts lakes. The primary aim is to make sense of data to reply questions, resolve issues, or become aware of traits and styles that are not without delay apparent.

Data evaluation is used in truely every enterprise—from healthcare and finance to marketing and education. It enables groups to make proof-based choices, improve operational efficiency, and advantage aggressive advantages.

Types of Data Analysis

There are several kinds of information evaluation, every serving a completely unique purpose:

1. Descriptive Analysis

Descriptive analysis answers the question: “What happened?” It summarizes raw facts into digestible codecs like averages, probabilities, or counts. For instance, a store might analyze last month’s sales to decide which merchandise achieved satisfactory.

2. Diagnostic Analysis

This form of evaluation explores the reasons behind beyond outcomes. It answers: “Why did it occur?” For example, if a agency sees a surprising drop in internet site visitors, diagnostic evaluation can assist pinpoint whether or not it changed into because of a technical problem, adjustments in search engine marketing rating, or competitor movements.

3. Predictive Analysis

Predictive analysis makes use of historical information to forecast destiny consequences. It solutions: “What is probable to occur?” This includes statistical models and system getting to know algorithms to pick out styles and expect destiny trends, such as customer churn or product demand.

4. Prescriptive Analysis

Prescriptive analysis provides recommendations primarily based on facts. It solutions: “What have to we do?” This is the maximum advanced type of analysis and often combines insights from predictive analysis with optimization and simulation techniques to manual selection-making.

The Data Analysis Process

The technique of information analysis commonly follows those steps:

1. Define the Objective

Before diving into statistics, it’s essential to without a doubt recognize the question or trouble at hand. A well-defined goal guides the entire analysis and ensures that efforts are aligned with the preferred outcome.

2. Collect Data

Data can come from numerous sources which includes databases, surveys, sensors, APIs, or social media. It’s important to make certain that the records is relevant, timely, and of sufficient high-quality.

3. Clean and Prepare Data

Raw information is regularly messy—it may comprise missing values, duplicates, inconsistencies, or mistakes. Data cleansing involves addressing these problems. Preparation may include formatting, normalization, or growing new variables.

Four. Analyze the Data

Tools like Excel, SQL, Python, R, or specialized software consisting of Tableau, Power BI, and SAS are typically used.

5. Interpret Results

Analysis isn't pretty much numbers; it’s about meaning. Interpreting effects involves drawing conclusions, explaining findings, and linking insights lower back to the authentic goal.

6. Communicate Findings

Insights have to be communicated effectively to stakeholders. Visualization tools including charts, graphs, dashboards, and reports play a vital position in telling the story behind the statistics.

7. Make Decisions and Take Action

The last aim of statistics analysis is to tell selections. Whether it’s optimizing a advertising marketing campaign, improving customer support, or refining a product, actionable insights flip data into real-global effects.

Tools and Technologies for Data Analysis

A big selection of gear is available for facts analysis, each suited to distinct tasks and talent levels:

Excel: Great for small datasets and short analysis. Offers capabilities, pivot tables, and charts.

Python: Powerful for complicated facts manipulation and modeling. Popular libraries consist of Pandas, NumPy, Matplotlib, and Scikit-learn.

R: A statistical programming language extensively used for statistical analysis and statistics visualization.

SQL: Essential for querying and handling information saved in relational databases.

Tableau & Power BI: User-friendly enterprise intelligence equipment that flip facts into interactive visualizations and dashboards.

Healthcare: Analyzing affected person statistics to enhance treatment plans, predict outbreaks, and control resources.

Finance: Detecting fraud, coping with threat, and guiding investment techniques.

Retail: Personalizing advertising campaigns, managing inventory, and optimizing pricing.

Sports: Enhancing performance through participant records and game analysis.

Public Policy: Informing choices on schooling, transportation, and financial improvement.

Challenges in Data Analysis

Data Quality: Incomplete, old, or incorrect information can lead to deceptive conclusions.

Data Privacy: Handling sensitive records requires strict adherence to privacy guidelines like GDPR.

Skill Gaps: There's a developing demand for skilled information analysts who can interpret complicated facts sets.

Integration: Combining facts from disparate resources may be technically hard.

Bias and Misinterpretation: Poorly designed analysis can introduce bias or lead to wrong assumptions.

The Future of Data Analysis

As facts keeps to grow exponentially, the sector of facts analysis is evolving rapidly. Emerging developments include:

Artificial Intelligence (AI) & Machine Learning: Automating evaluation and producing predictive fashions at scale.

Real-Time Analytics: Enabling decisions based totally on live data streams for faster reaction.

Data Democratization: Making records handy and understandable to everybody in an business enterprise

[severr]

Hi!! Whats the graph you made for the jobs look like? I am totally normal about this game and about making graphs so id love to see how you graph'd the job qualifications :0

-@birchforestburrow

OH i am thrilled to share thank you for asking!

there are many excel sheet templates people share for PCE, you can check the forums for very advanced options! i made my own database sheet in Notion bc i like that app and to me it’s much easier to use and adapt to my needs, and nicer to look at :) excel might have more functions tho.

i mostly use it for occupation-related data, though it’s probably possible to also make it handy for keeping track of genetics and stuff (i’m not very interested in that so i haven’t gotten deep into it).

i simplified it to only have the necessary information, like i only list the personality traits and stats relevant for the profession(s) i chose for the kitty, not all of them. it uses my personal color associations and abbreviations, which are not the same as in the game :D but if you’d like to try Notion for this kind of thing, i can make an empty template to share~