#which are widely used for data analysis

[education43]

What Are the Qualifications for a Data Scientist?

In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.

The Key Qualifications for a Data Scientist

To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:

1. Educational Background

A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.

2. Proficiency in Programming Languages

Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.

3. Understanding of Machine Learning

Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.

4. Data Wrangling Skills

Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.

5. Statistical Knowledge

Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.

6. Communication and Data Visualization Skills

Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.

7. Domain Knowledge

Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.

Why Choose DataCouncil for a Data Science Course in Pune?

If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:

Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.

Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.

Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.

100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.

Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.

Conclusion

Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.

Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!

[feminist-space]

"Balaji’s death comes three months after he publicly accused OpenAI of violating U.S. copyright law while developing ChatGPT, a generative artificial intelligence program that has become a moneymaking sensation used by hundreds of millions of people across the world.

Its public release in late 2022 spurred a torrent of lawsuits against OpenAI from authors, computer programmers and journalists, who say the company illegally stole their copyrighted material to train its program and elevate its value past $150 billion.

The Mercury News and seven sister news outlets are among several newspapers, including the New York Times, to sue OpenAI in the past year.

In an interview with the New York Times published Oct. 23, Balaji argued OpenAI was harming businesses and entrepreneurs whose data were used to train ChatGPT.

“If you believe what I believe, you have to just leave the company,” he told the outlet, adding that “this is not a sustainable model for the internet ecosystem as a whole.”

Balaji grew up in Cupertino before attending UC Berkeley to study computer science. It was then he became a believer in the potential benefits that artificial intelligence could offer society, including its ability to cure diseases and stop aging, the Times reported. “I thought we could invent some kind of scientist that could help solve them,” he told the newspaper.

But his outlook began to sour in 2022, two years after joining OpenAI as a researcher. He grew particularly concerned about his assignment of gathering data from the internet for the company’s GPT-4 program, which analyzed text from nearly the entire internet to train its artificial intelligence program, the news outlet reported.

The practice, he told the Times, ran afoul of the country’s “fair use” laws governing how people can use previously published work. In late October, he posted an analysis on his personal website arguing that point.

No known factors “seem to weigh in favor of ChatGPT being a fair use of its training data,” Balaji wrote. “That being said, none of the arguments here are fundamentally specific to ChatGPT either, and similar arguments could be made for many generative AI products in a wide variety of domains.”

Reached by this news agency, Balaji’s mother requested privacy while grieving the death of her son.

In a Nov. 18 letter filed in federal court, attorneys for The New York Times named Balaji as someone who had “unique and relevant documents” that would support their case against OpenAI. He was among at least 12 people — many of them past or present OpenAI employees — the newspaper had named in court filings as having material helpful to their case, ahead of depositions."

[reasonsforhope]

"A new study reveals the profound ecological effects of wolves and other large carnivores in Yellowstone National Park, showcasing the cascading effects predators can have on ecosystems. In Yellowstone, this involves wolves and other large carnivores, elk, and willows.

The research, which utilized previously published data from 25 riparian (streamside) sites and collected over a 20 year period, from 2001 to 2020, revealed a remarkable 1,500% increase in willow crown volume along riparian zones [note: riparian means in/around rivers] in northern Yellowstone National Park, driven by the effects on elk due to a restored large carnivore guild following the reintroduction of wolves in 1995–96, and other factors...

Pictured: Upstream view of Blacktail Deer Creek in 2005 and 2021, northern range of Yellowstone National Park.

Trophic cascades, the effects of predators on herbivores and plants, have long been a topic of ecological interest. The study quantifies the strength of this phenomenon for the first time using willow crown volume as a proxy for aboveground biomass, demonstrating a significant three-dimensional recovery of riparian vegetation represented by the growth in both crown area and height of established willows.

The strength of the Yellowstone trophic cascade observed in this study surpasses 82% of strengths presented in a synthesis of global trophic cascade studies, underscoring the strength of Yellowstone's willow recovery process. The authors note that there is considerable variability in the degree of recovery and not all sites are recovering.

Even though riparian areas in the western United States comprise a small portion of the landscape, the study has particular relevance since these areas provide important food resources and habitat for more wildlife species than any other habitat type. These areas also connect upland and aquatic ecosystems and are widely known for their high diversity in species composition, structure, and productivity.

"Our findings emphasize the power of predators as ecosystem architects," said William Ripple. "The restoration of wolves and other large predators has transformed parts of Yellowstone, benefiting not only willows but other woody species such as aspen, alder, and berry-producing shrubs. It's a compelling reminder of how predators, prey, and plants are interconnected in nature."

Pictured: An across channel view in 2005 and 2021 of a downstream reach on Blacktail Deer Creek, northern range of Yellowstone National Park.

Wolves were eradicated and cougars driven to low numbers from Yellowstone National Park by the 1920s. Browsing by elk soon increased, severely damaging the park's woody vegetation, especially in riparian areas. Similar effects were seen in places like Olympic National Park in Washington, and Banff and Jasper National Parks in Canada after wolves were lost.

While it's well understood that removing predators can harm ecosystems, less is known about how strongly woody plants and ecosystems recover when predators are restored. Yellowstone offers a rare opportunity to study this effect since few studies worldwide have quantified how much plant life rebounds after large carnivores are restored.

"Our analysis of a long-term data set simply confirmed that ecosystem recovery takes time. In the early years of this trophic cascade, plants were only beginning to grow taller after decades of suppression by elk. But the strength of this recovery, as shown by the dramatic increases in willow crown volume, became increasingly apparent in subsequent years," said Dr. Robert Beschta, an emeritus professor at Oregon State University.

"These improving conditions have created vital habitats for birds and other species, while also enhancing other stream-side conditions."

The research points to the utility of using crown volume of stream-side shrubs as a key metric for evaluating trophic cascade strength, potentially advancing methods for riparian studies in other locations. It also contextualizes the value of predator restoration in fostering biodiversity and ecosystem resilience."

-via Phys.org, February 6, 2025

[romchat]

I FINALLY bought a digital copy of Sinners and wanted to highlight a few other cinematography choices I really loved besides that tracking shot of Lisa Chow. The first is the camera language with which the White (and passing) characters are introduced and how it creates a unique sense of racial dread.

In her NYTimes article "The Condition of Black Life Is One of Mourning, poet Claudia Rankine pointedly describes the daily strain of anti-Black racism:

"Anti-black racism is in the culture. It’s in our laws, in our advertisements, in our friendships, in our segregated cities, in our schools, in our Congress, in our scientific experiments, in our language, on the Internet, in our bodies no matter our race, in our communities and, perhaps most devastatingly, in our justice system. The unarmed, slain black bodies in public spaces turn grief into our everyday feeling that something is wrong everywhere and all the time, even if locally things appear normal."

This quiet but unrelenting feeling that something is wrong and could go wrong hovers over Sinners, the movie playing with our (visual) expectations of the many ways racist violence can suddenly strike at the whim of its White characters.

From the establishing shots of Sammie's sharecropper home to the plantation fields to the prison chain gang, we know that this a world where White characters can act without impunity. The violent legacy of slavery continues well beyond its official end, which we can see from the endless white rows of cotton in the foreground and background connecting each scene to the next, the overseers' silhouettes haunting the edge of the frame.

So when a White character physically enters a scene, we immediately feel dread, hyperaware that they could choose to be dangerous and mete out violence at any time just because they can. The introduction of Hogwood and Mary are good examples of this.

As Smoke and Stack wait for Hogwood to arrive to sell them his property, the camera stays trained on a narrow road that snakes behind the bend. There's low visibility because of the use of a wide shot and its duration is a beat too long. The Twins aren't sure how the interaction will go with this White man, and we the audience are forced to sit in that uncomfortable (but routine) tension with them.

And their wariness is justified because look at how Hogwood gets out of the car, his gun front and center. He's a threat on arrival and flaunts that power (e.g., that intentionally placed "boys").

Side Note: I might be stretching but that utility pole is almost cross-like, no? Possible reference to a KKK burning cross?

And despite Mary's deep connection to Stack and the rest of the Black community, she too chooses to be a danger and we can see this based on how she's visually introduced.

Her figure stands in the background, blurred because of the depth of field. There's something ghost-like about her appearance, which I'd interpret as symbolic of how as a White passing woman her past sexual relationship with Stack can still haunt him given the South's anti-miscegenation laws.

The tension of the scene ramps up as Mary approaches, the intimacy of the close-up shots anxiety-inducing. Although she is justified in how upset she is at him, this move is completely reckless given the optics. As @mosaic-briar observes in their analysis of Mary:

"White women have some of the most historically violent relationships to Black men that goes from before Emmitt Till to the data surrounding discipline in schools...Mary's incapability to recognize how much danger she was putting Stack in by yelling about their sex in the middle of the street telegraphed for us everything we'd need to know about how far she had processed her own identity."

This is a meeting between former lovers who care about one another but Mary's White femininity is still lethal even if she doesn't mean it to be. What a smart way to communicate the capricious but destructive power of Whiteness.

[traveler-at-heart]

Miss Communication

Summary: Natasha is avoiding the feelings talk so you use the only thing that seems to be working: jealousy.

A/N: This request and entire plot is from @happychopshoppenguin so all credit really goes to them. I just put into a few more words.

Natasha Romanoff x F!R

Stealthy, precise, lethal.

Well, what a load of crap. All Natasha Romanoff is, is a coward. There.

You’re so pissed off, all you want to do is open up her file and write “committment issues” under weaknesses.

But that’s not your job.

No, your job is intelligence and data analysis. Go over information, read endless reports and make a summary that the Avengers can understand, because they don’t have the time to sit around and do it themselves.

And now, you’re here, talking about a new terrorist organization with Steve. Natasha should be here, as second in command, but for reasons unknown to you and Captain America, she has failed to show up.

Again, coward.

Fine, if she doesn’t answer your texts you’ll find her anywhere she’s hiding in this big ass building.

“Hey, Y/N” Sam greets as you walk down the hall.

“Damn. Is it allowed to have guns in the kitchen area?” you smile mischiveously, used to flirting around with the team. He looks around, clearly confused and you reach out to touch his bicep. “I mean, what are they feeding you, Wilson? You’re as buff as Steve”

“Hell, yeah” he smiles, flexing and putting on a little show. You’re laughing and making small talk when someone magically appears, glaring.

Natasha is fuming and you don’t know if the anger is directed at you or Sam. Looking directly at her, you laugh and place a strand of hair behind your ear, as if Sam just said the funniest thing ever.

She can’t answer a fucking text but feels jealous? Well, good. At least you know she cares.

“You’re annoying her, Wilson” Bucky joins you, leaning against the kitchen island and giving you a crooked smile. “Hey, doll”

“Hi, handsome” you place your hands on each side of his face. “Can I tell you something?”

“Yeah” he says, practically drooling.

“I think you’d look really good if you cut your hair”

“I’ll think about it” he promises.

“Move aside, I’m taking Y/N out for lunch” Sam says, pushing Bucky.

“Oh, sweetheart. You can’t handle all of this” you tease. “But I won’t say no to lunch”

“That’s good enough for me” he agrees, offering his arm. You take it, winking at Bucky and walking away.

Natasha is already planning six different ways to make Wilson disappear, and Bucky goes to his room.

“Gotta get a haircut” he mumbles.

Oh, like hell.

Neither one of them can touch what’s hers.

—

Natasha: How was lunch?

Y/N: Oh, NOW you text me?

Y/N: We need to talk. Call me.

—

Natasha throws the phone across the room, feeling like screaming into her pillow. It still smells like you, which makes her heart ache.

If only she hadn’t been so stupid to ruin whatever it is you two had.

You were on top of her, riding her strap, as you had done so many times since you started your situationship. Hands on Natasha’s abdomen, feeling how her muscles worked to pump in and out of you.

“I love your tits” Natasha said, breathless. You nodded, bouncing harder, moaning desperately. “I love your pussy, it’s perfect for my cock”

“Baby, I’m so close” you whined, so desperate you barely registered her next words.

“I love you”

Eyes wide open, your movements stopped for a second. Before you could answer, Natasha flipped you and you were face down, ass in the air as she entered, pounding harder.

And you really wanted to ask what the fuck and if she really meant what she said, but you were so close that all you could do was moan her name and come hard around the strap.

You barely registered when Natasha pulled out. You felt empty and confused and so stretched.

“Nat? Babe, wait”

“I have to… I forgot a mission report, I’m sorry” she muttered, putting her clothes on and leaving in a hurry. She ran out of her own fucking room before owning what she said.

And now, she couldn’t even look at you. She couldn’t stand the idea that you would reject her.

The little hope that lingered in the back of her mind was the most painful feeling of all.

All she wanted was to be loved by you.

—

Call me means fucking call me.

It means don’t pretend nothing happened.

God, she’s so infuriating. And hot. And good at sex.

But mostly infuriating.

Now you’re back in the Compound, determined to get her to talk to you. Which is why you decided to wear your low cut dress and push up bra.

She said she loves your breasts, right? Well, here they fucking are.

You carry a bunch of binders that need filing, and they help cover your boobs as you enter the living room. Natasha is sitting, and you think she is almost ready to approach you when Sam beats her to it.

“Here, let me help you” Sam offers. The minute your cleavage comes to view, his eyes widen.

“Hey, doll” Bucky greets and you turn around. His mouth flails open, but all you can do is admire his new look.

“Buck, oh my God! You actually listened to me?” you run your hands through his hair, making it impossible for him to look away from your chest. “You look absolutely stunning. Good boy”

“Yeah, uh… I…”

The interaction annoys Natasha, but she knows you won’t even entertain the idea of doing anything with those two.

Her mood quickly changes when Carol appraches you. She's a whole different story.

“Carol, it’s been ages since you’ve been here! All I read are your mission briefings” you say, hugging her tight.

“Well, how bout I tell you everything I’ve been up to over dinner?” she offers with a smile.

“Y/N” Natasha finally snaps. “I missed this week’s report. Mind filling me in?”

“Sure thing” you pull away, reluctantly. “Be right back, Danvers”

Natasha leads you to the conference room and pushes you against the door as soon as you enter.

“Why must you be such a brat?” she whispers against your ear, biting down your earlobe.

“It's the only way to get your attention, Natasha” you protest, trying to sound upset.

You’re torn between lust and anger, but she’s such a good kisser that her lips make you forget everything that’s happened in the last few days.

“I should punish you” she threatens, going down your body and pulling the dress up. Who is she kidding? Her mouth is watering at the thought of tasting you. “Bet you’d love that”

Love.

The word pulls you out of your trance. Natasha is about to take your panties off when you stop her, pulling her away by her hair.

“We’re going to talk”

“You don’t make the calls here”

“Natasha, stop it. I’m serious”

You really don’t want her to stop, but you can’t keep wondering if she meant it.

You want her to mean it.

“Are you seriously gonna make a big deal about it?”

“Ugh, you drive me insane, Natasha. Why can’t you just admit what you said and whether or not you meant it? Do you even care about what I want?”

She stays silent and you groan, pulling up your dress and fixing your clothes.

“I really wanted to be more than just fuck buddies” you admit before going out. “But if the thought of loving me is so embarassing for you, then forget about it. I won’t force the feeling out of you”

Natasha stays behind, wondering how she got it all wrong.

You wanted her.

By the time she comes to her senses, you’re long gone. But Carol does meet her in the hallway, smiling.

“Hey, do you mind telling Cap I’m skipping our meeting? Y/N and I are having dinner”

“Sure” Natasha nods, feeling her stomach drop.

Now it’s too late and she lost you.

—

The second anniversary of the Sokovian Accords comes and goes in a flash. Natasha really wanted to skip it, go find you and apologize.

And yet, here she is, in the Quinjet, flying back to the Compound after two days of exhausting diplomacy.

“Why couldn’t we stay a few days in Paris?” Sam laments for the third time.

“New recruits are in the middle of their training” Barton says from the pilot seat. “At least they got a break these last couple of days”

 “No, they didn’t” Wanda says. “Y/N is training them. Maria asked her to do it before we left”

“Y/N?” everyone says, looking at each other.

“But she’s a data analyst, not a field agent” Sam says.

“And the sweetest person ever” Bucky adds. He holds Natasha’s glare and smiles. Oh, he knows what’s up.

“Well, let’s make sure we put them back into shape when we get there” Steve slaps Bucky’s arm.

Boy, are they all wrong. When the team goes back to the Compound, you’re in the middle of a training session. A guy runs out of the gym, his shoulder crashing against Sam’s as he bolts for the exit.

“She’s fucking crazy, man” he says to himself, looking terrified.

“What the hell?”

Steve pushes the door to the gym. And there you are, in the middle of sparring. With one swift motion you kick the guy to the floor, and he puts his hands up, as if begging for mercy.

“Oh, we have company” you taunt, walking confidently around the students. “Anyone want to fight the Avengers? I promise you they’re not as hard to beat”

“Who is she and what has she done to Y/N?” Barton whispers.

Natasha has to hold back a moan. You look cold and deathly, having kicked all of their asses without breaking a sweat. That also explains why you’re so… bendy.

“Fine. Since none of you could even land a hit on me, you’re running ten laps. Don’t come back here unless you’ve thrown up or cried once”

All the recruits scramble to their feet, relieved now that they can get away from you. You turn around, giving the Avengers a challenging look.

“What? Wanna give it a try? I’ll go easy on you” you say. “Maybe not on Natasha, though. She hasn’t been a good girl”

“Ew” Wanda says, leaving the room. Between that and Natasha’s bendy thought, that was so loud she might as well have screamed it in the middle of the gym, she’s had enough.

“Alright, let’s see what you’ve got” Barton is the only one that steps up. You nod, evaluating his approach. He throws the first punch but it never lands. You move out of his way at record speed, keeping the contact at minimum while you kick the back of his legs, making him fall on his knees. Another three blows and Clint is face down on the mat.

“Pass” Sam says when you turn around to see who’s next.

“I’ll take my chances” Natasha says, stepping up. You smile in a way that makes a chill run down her spine.

Natasha thinks you can never go wrong with a classic move, so she throws her legs around your neck. But you block the movement and make her land on her back, hands pinned abover her head.

It happens at least three different times, each position becoming more sexual.

“I think we should leave” Bucky says.

“In a minute”

“Come on, Wilson” he forces him out the door, closing it for good measure and hoping you keep your clothes on before the recruits come back.

If they even come back.

“I promise you, you’re not gonna win this time, Natasha” you say, out of breath for the first time. Her eyes travel to your lips and you lean forward, stopping inches away from her mouth. “And I sure as hell ain’t letting you go without talking about that thing you said the other day”

“Please…”

“Now you’re polite. Now you say please. I’ve been chasing you for a fucking week to know if you like me for more than my tits and ass” you finally give in, kissing her for a few seconds. She whines against your mouth, trying to create friction. But your hold is too strong and she can’t move an inch without your permission.

“I’m sorry, baby, I’m sorry. I was scared you’d reject me and then everything would be ruined forever between us. I love you, so damn much it scares me” Natasha finally breaks, surprising herself with the way she’s pouring her heart out to you.

But that’s how much she loves you and how much she needs you.

Her words leave you breathless and you smile, going back to being your usual self.

“Natasha, I love you so damn much, it drives me crazy. Please don’t ever doubt that, sweetheart”

She nods, her nose rubbing against yours and you finally do what you’ve been craving all week. You kiss her, gently at first, and then more passionately, your hands dropping from hers to let her hug you.

You moan against her mouth, Natasha’s tongue slipping inside.

“Fuck, baby, I need you” you moan, going back to being submissive for the redhead.

“What does my pretty girl want? My mouth or my fingers?”

“Just you, anything, please”

Thinking back to the last time she almost had you, her mouth waters and she decides to flip you on your back and travel down your body, leaving a trail of open mouthed kisses and pulling down your shorts and underwear.

“All of this for me?” she asks, running her fingers up and down your slit, collecting your juices and sucking on her digit. “I missed your taste, princess”

“Nat, please” you cant your hips up, hoping she takes the hint. You’re too far gone to form a coherent sentence.

Natasha darts her tongue out. She moans at the taste, and snakes her arms around your thighs to keep you in place. Her tongue goes up and down, then deep inside you and you shudder.

You would almost feel embarrassed for lasting so little, but it’s not your fucking fault she was hiding for a week.

When you remember that, your hands go to her hair and you pull her closer. Natasha enjoys the roughness, her movements speeding up and pushing you over the edge.

You come, crying out her name and trembling. As you struggle to catch your breath, Natasha moves up, letting you taste yourself in her mouth.

“Hey, baby”

“Hey” you say, smiling.

“Can I take you out to dinner tonight? I’d like to make it up to you”

“Yes to dinner. And give me a couple more of those orgasms and we’ll call it even”

“That sounds like a deal” she smiles against your lips, eager to make up for the lost time.

[justinspoliticalcorner]

The Guardian:

Research published in the Lancet medical journal estimates that the death toll in Gaza during the first nine months of the Israel-Hamas war was about 40% higher than numbers recorded by the Palestinian territory’s health ministry. The peer-reviewed statistical analysis was conducted by academics at the London School of Hygiene & Tropical Medicine, Yale University and other institutions, using a statistical method called capture-recapture analysis. The researchers sought to assess the death toll from Israel’s air and ground campaign in Gaza between October 2023 and the end of June 2024, estimating 64,260 deaths due to traumatic injury during this period. The study said 59.1% were women, children and people over the age of 65. It did not provide an estimate of Palestinian combatants among the dead. Up to 30 June last year, the health ministry in Gaza reported a death toll of 37,877 in the war, which began on 7 October 2023 after the Hamas-led attack on southern Israel in which 1,200 people were killed and more than 250 taken hostages. According to Palestinian health officials, a total of more than 46,000 people have been killed in the Gaza war, from a prewar population of about 2.3 million. It has not been possible for international media to independently verify the death toll in Gaza as Israel does not allow foreign journalists into the territory. A senior Israeli official, commenting on the study published on Friday, said Israel’s armed forces went to great lengths to avoid civilian casualties. “No other army in the world has ever taken such wide-ranging measures,” the official said. “These include providing advance warning to civilians to evacuate, safe zones and taking any and all measures to prevent harm to civilians. The figures provided in this report do not reflect the situation on the ground.” The Lancet study said the Palestinian health ministry’s capacity for maintaining electronic death records had previously proven reliable, but deteriorated under Israel’s military campaign, which has included raids on hospitals and other healthcare facilities and disruptions to digital communications. Israel accuses Hamas of using hospitals as cover for its operations, which the militant group denies. The study used death toll data from the health ministry, an online survey launched by the ministry for Palestinians to report relatives’ deaths, and social media obituaries to estimate that there were between 55,298 and 78,525 deaths from traumatic injuries in Gaza up to 30 June 2024.

The study’s best estimate was 64,260 dead, which would mean the health ministry had under-reported the number of deaths to that point by 41%. The estimate represented 2.9% of Gaza’s prewar population, “or approximately one in 35 inhabitants”, the study said. The figure is only for deaths from traumatic injuries and does not include deaths from a lack of healthcare or food, or the thousands believed to be buried under rubble.

The Lancet’s study reveals that the death toll in Gaza is significantly higher than the official numbers, leading to the credence of claims that the death toll is undercounted.

[stillmonsterz]

all i gotta do

for this anon!

pairing: jake x reader

genre: fluff (?), humor (???), smut

summary: it's your first day at work and you're nervous. however, your trainer is going to show you why you were nervous for the wrong reasons. one week with jake sim will either make you quit the job or never leave.

contains: unprotected sex, exhibitionism, swearing, incest mention, PTSD mention, i try to be "funny" and make "jokes"

word count: 4.4k (unproofread)

---

DAY ONE

You stepped inside of your new workplace apprehensively; you hadn’t felt so nervous since your first day of university. Wiping your palms on your pants, you made eye contact with the receptionist and smiled wanly. 

“Hello,” you said, resting your fingertips on the counter. “I’m the new hire. I was wondering where I could find…Jake Sim? He’s supposed to be my…” The term that had been used in the introductory email the company had sent to you eluded you.

“Your buddy,” the receptionist said flatly. “Your Park Corp buddy.”

“Yes. That.”

“Jake Sim is on the fifth floor. I take it you’ll be working in data analysis as well?”

You nodded. “Yes, exactly.”

The receptionist smiled at you, but it belied a certain cold humor. “Good luck.”

“Yeah, you too.” As you walked away, you realized your blunder and squeezed your eyes shut. 

–

The fifth floor of the office building had all of the markings of a corporation attempting to reel in more younger workers. There was a vending machine as soon as you walked in, the cubicles were arranged as part of an open concept floor plan, and the walls were plastered with positive, empty aphorisms. You scanned the area, wondering which of the people hunched over their computers was Jake.

Footsteps echoed behind you, and when you turned around you saw a slight, enthusiastic-looking young man with a shock of shaggy brown hair approaching you. In his hands he held two coffee cups. 

“Hey, newbie,” he said with some affection. “Got you a coffee.”

You took the cup, surprised by his vivacity. “Thank you…”

“Jake,” he finished, holding his hand out. “Jake Sim.”

You shook his hand as firmly as you could and introduced yourself.

“I know,” he said cheerfully. “Don’t worry, I like to do a little stalking before we meet a new hire. Although…” his face grew serious. “You really shouldn’t post such…provocative pictures on your Insta. Someone could get ideas.”

Your face blanched and your fingers gripped the coffee cup. “What?”

Jake’s face broke out into a smile. “Just fuckin’ with you. Sorry, I like to razz all the new hires. Makes me feel big.”

His grin was so wide, you felt compelled to smile too. He nudged you and jerked his thumb in the direction of the cubicles. “Let me show you around, PCB.”

You blinked, then it dawned on you. “Park Corp buddy…?”

“So observant,” Jake said, amused. “Come on.”

You followed him around as he explained where everything was: the copy room, the coffee machine, the water dispenser, the popcorn machine, your cubicle (situated in the middle of the room, to your chagrin), his cubicle (tucked neatly in the corner).

Then he taught you how to use the software. Thanks to your university courses, it wasn’t difficult to learn. Jake’s playful personality also gave way to a maturity that you hadn’t expected. He carefully walked you through the program step by step.

“I’ll leave you these tasks to work on,” he said, pulling up a document he had pre-made. “If you get stuck, just come get me, okay? I’m right in the corner.”

You thanked him for his assistance and started working on the tasks he had given you. It wasn’t challenging, so much as it was tedious. Still, you persevered. 

At least, until you heard him approach you again.

“Hey,” Jake said, sitting beside you. His eyes darted around the room. “You were supposed to come get me.”

“You told me to do that if I needed you,” you replied, somewhat confused.

“Yeah,” Jake said slowly, “in case you feel the overwhelming urge to make Jakey’s day and let him help you with something so he can avoid doing his boring ass work. You don’t even understand the basics of being a PCB, do you?”

“You’re using me,” you said, waving an accusatory finger at him. 

“Can you blame me?” he retorted. “Sometimes I can…I can feel my soul leaking from my pores.”

You giggled, and he squinted at you in mock annoyance. “There’s no way you’re laughing at me,” he said, trying to fight a smile. “I’m dying, turning into a corpse, and you’re laughing.”

You shrugged. “At least you’ll die at the prime of your life.”

Jake’s lips curled into a mischievous smile. “Oh, you think I’m in my prime, huh?”

“That’s not what I me-,”

“You’re hitting on me,” Jake said, leaning in. He blinked at you like a puppy. 

You leaned away, your cheeks feeling warm. “I’m not.”

“I wouldn’t mind if you were,” he said softly.

You were about to say something else, something intelligent and witty, but one of your new coworkers approached the two of you. 

“Couldn’t wait a day before sexually harassing the newbie, could you?” He was tall, pale, and had a shit-eating grin that could rival Jake’s. Unlike Jake, who was dressed in a blue button-down and slacks, this person wore a suit with a silky black tie.

Jake leaned away from you, balking at the accusation. “I am not sexually harassing her,” Jake said, clutching his heart. “I wasn’t even normal harassing her.”

“He wasn’t,” you chimed in. 

“Don’t cover up for this louse,” Sunghoon said, shaking his head at Jake. “Look at you, corrupting one of our brightest already with your salacious comments. Weren’t you supposed to be writing up a report on the-,”

“You hear this jerkoff?” Jake said, interrupting. “He puts on a little suit and starts using words like ‘louse’ and ‘salacious’, like we’re not in data analysis.”

“I am a data architect,” Sunghoon said, playfully slamming his hand on your desk. “And I will be treated like one, damn it.”

“Quit it,” Jake said, putting his arms around you and hugging you close to him. “You’re scaring my PCB.” 

“Your PCB is going to get PTSD if you keep touching her,” Sunghoon replied drolly, crossing his arms.

Jake grinned. “My PCB is going to get PTSD if I do PDA with her?” 

Sunghoon said, “Good one,” and they laughed and high-fived. You stared at them incredulously, noting that Jake’s arm was still wrapped around your shoulder. 

“Sorry,” you said slowly, “but I’d like to do my work…”

Jake withdrew his arm and tsked under his breath, standing up. “Great going, Sunghoon,” he hissed. “Now she hates you.”

“She hates you, idiot,” Sunghoon retorted as they walked away.

You slumped down in your chair, already feeling exhausted. You worked straight through your lunch break, and as you commuted home you wondered how the rest of your training week would go.

–

DAY TWO 

The next day, you felt a little more equipped to navigate your new job. In your purse, you brought some items with which to decorate your desk.

You came into work early, noting that very few people show up at this time. Perfect. With careful precision, you arranged your new trinkets on your desk; a magnetic calendar for your cubicle wall, a little plush doll, a notebook, a nice mousepad, and a little jar of chocolates. 

As you’re turning your computer on, you heard three male voices approaching your desk. Two of which you recognize. 

“There she is,” you heard Jake say quietly, “isn’t she cute?”

You looked up and waved. There was Jake, wearing a button-up with the sleeves rolled up to his elbows. Sunghoon, wearing another crisp suit. And a third person wearing an oversized collared shirt with dark blue jeans, looking you up and down. 

“You’re here early,” Jake said cheerfully. “Excited for work?”

“I just wanted to decorate my desk,” you explained, proudly displaying your newly decorated workplace.

The three men politely admired your table. Then Sunghoon nudged the third man in the ribs. He cleared his throat. 

“I’m Heeseung,” he said, awkwardly raising his hand. “Heeseung Lee.”

“Nice to meet you,” you replied, holding your hand out.

You shook hands with him, and Sunghoon snorted. “I didn’t get a handshake from you.”

“You also didn’t introduce yourself to me…”

Sunghoon looked away, the tips of his ears going red. “Right. I suppose that was my folly. Apologies.”

Jake leaned down and whispered, “Isn’t he such a pretentious dick?” in your ear. You suppressed another giggle as you stuck your hand out.

Sunghoon shook it firmly. “Park Sunghoon,” he said with a smile. “Data architect.”

“You told her that already,” Jake said. 

“And I told you to shut up several times, not that you ever listened,” Sunghoon retorted.

You glanced at Heeseung, and he just shrugged at you. “They can’t stop,” he said, glancing between the two of them. “It’s hard-coded into their DNA to be idiots in front of cute girls.”

Jake squinted at Heeseung. “Oh, you think she’s cute? Are you into her or something?”

Heeseung raised his hands in self-defense, backing up. “No, no, not at all.”

You sighed. “Could…could I go ahead and start my work?”

Jake shook his head and stalked away from your table. “She fucking hates you, you know that?” he said, lightly pushing Heeseung. 

Later that day, as you’re packing up to head home, you hear footsteps that were already becoming familiar.

“Hey,” Jake said quietly, “the guys and I were wondering if you wanted to eat with us at lunch tomorrow?”

You blinked up at him. “No kidding?”

“Yeah. We want you to feel welcome here,” he said, resting his hand on your shoulder. 

A smile spread across your face, and you nodded. “Sure. Sounds like it'll be a lot of fun.” Like seeing monkeys in the zoo.

Jake grinned, patting your shoulder. “Awesome! Awesome, awesome.” He paused then, placing his hand in his pocket. “One other thing,” he said slowly. 

“What’s that?” you tilted your head at him.

“Well, you know, you don’t have to dress so formally,” he said, gesturing at your outfit. “Unless you’re trying to be Sunghoon or something. You can dress business casual.”

You looked down at yourself; your outfit was pretty formal and rigid. “All right,” you said, “I’ll be nice and casual tomorrow.”

“Sounds great,” Jake said, biting his lip slightly. 

– 

DAY THREE

Work already felt much more comfortable. Besides the three coworkers you had already met, the rest of the employees ranged from amicable to ambivalent, so you never felt tense. Occasionally, Jake would come over to your desk and look at how you were coming along. Or, as you figured, he was just coming to ogle you. Not that you minded the extra attention. 

When you walked in this morning, dressed in your more casual outfit, his eyes had lingered on you for so long you thought it could be classed as a workplace violation.

“Very nice,” Jake had said approvingly. “Very…casual.”

“I try,” you had said drily, heading to your desk. 

“I’m serious,” he had said, walking with you. “You have, pardon me, a great figure.” 

“That’s not very PC,” Sunghoon had said as he passed by your desk. 

“So, what you’re saying,” Jake had started, and you were already rolling your eyes, “I’m not acting PC with my PCB?”

You had groaned. “Jake…”

“Great going, Sunghoon,” Jake had grumbled, his hands stuffed in his pockets. “You’re the worst, I swear…”

Now you were sitting with them in the break room, where they were locked in what you could only assume was a longstanding debate. 

“I’m saying that it wouldn’t be gay if it was on an island,” Jake protested, “so it wouldn’t even matter, Sunghoon.”

“Okay, but they’d eventually get rescued, so they’d have to live with that,” Sunghoon retorted, gesturing with his sandwich. 

“Yeah, but they don’t know that they’re getting rescued.”

You glanced at Heeseung, who was eating a microwavable meal. “What are they talking about?”

Heeseung leaned into you, whispering as so not to catch their attention. “It’s this stupid hypothetical they came up with,” Heeseung explained. “If there was an island, and a pair of adult siblings were on one end, and a pair of two straight men were on the other end, which pair would hook up first?”

You blinked. “Well, the siblings, right?”

A haunting silence overtook the break room. Heeseung, Jake, and Sunghoon all stared at you, and you got the impression that you had disrupted something sacred, something hallowed.

Sunghoon laughed and pointed at you. “See? See? Your little work wife doesn’t even agree with you. Those siblings would be smashing, right?”

“Well, I g-,”

“All over each other,” Sunghoon continued, making vulgar gestures with his hands. “It’d be like…five hours. Sweaty from the sun. They’d be rolling around, sand in their ass, it’d be carnal. Primal.”

Jake stared at you incredulously. “You really don’t think the straight guys would fuck?”

You shrugged helplessly. “Well, they’re straight, so I mean…”

Jake groaned, throwing his head back dramatically. “Okay. Look. If you were on an island with a sexy ass woman, and she had short nails and everything, and she was fully ready to finger your pussy, you wouldn’t let her smash? Because you were ‘straight’?”

“I mean…no.”

“Nah,” Jake said, waving a baby carrot in your face. “You’re either deluded or you aren’t thinking hard enough. You’d get desperate. You’d be munching so much carpet you’d look like…like…”

“Like a carpet factory,” Heeseung said sarcastically. 

“You’re so fucking unfunny,” Jake replied. “No, you’d look like…”

“Like she’s an interior designer?” Sunghoon offered. 

“Close enough,” Jake said, sighing. “Real dark day when Sunghoon is funnier than you. Do better, Heeseung.”

“Yeah, Heeseung,” you said, “do better.”

Heeseung scoffed. “I thought you were my friend.”

You shrugged. “I wanted to join in.”

Jake clapped you on your back and laughed. “Look at you. Blending in already!”

– 

After lunch you excused yourself and went to the bathroom. When you emerged, Jake was leaning against the wall, playing with his fingers. 

“Hey,” he said, straightening up. “Had a random hypothetical for you.”

“Sure,” you said, crossing your arms. 

“So,” Jake began, his eyes darting around your face, “if you were stuck on a deserted island…”

You groaned. 

“Wait! Wait, wait, wait.” Jake put one hand on your shoulder. “If you were stuck on a deserted island, which of us would you want with you? Me, Sunghoon, or Heeseung?”

You frowned. “Well, you, obviously.”

Jake smiled at you widely, running his fingers through his hair. “Ha, for real?”

“Well, yeah. I know you the best.”

His smile faltered. “Is that really the only reason?”

You frowned, unsure of what to say. “I me-,”

Jake clapped you on the back and snorted. “I was just messing with you,” he said before striding back to his corner cubicle.

–

DAY FOUR 

You consulted your list of tasks. Your last, and most important task, was to type up a data analysis report based off of the information you had been gathering for the past week. Jake said that he would look over it for you later.

After spending the better part of your morning working on the report, you leaned back and stretched. Your eyes were starting to hurt from staring at a screen for so long, and you rubbed them.

Jake was next to you before you could react. “Hey,” he said, “how’s the report going?”

“It’s going,” you said, pinching the bridge of your nose.

“Let me see,” Jake said, leaning over you and scrolling through your document. Your breath hitched; he was so close, you could smell his cologne. If you glanced to your right, you would be able to see his Adam’s apple bobbing up and down as he swallowed. 

Jake silently pored over the document, his chest pressed against your back. His hand rested on your shoulder, and you couldn’t tell if he was rubbing it as a subconscious habit or not.

“Looking good so far,” he whispered, and when his hand slid down your arm, you knew it was intentional.

“Anything I need to fix?” you asked, attempting to maintain a semblance of professionalism.

“Hm…” Jake leaned in to you evermore, until he was flush against you. “Nothing I can see. You’re a good worker, aren’t you?”

“I try,” you said quietly. 

“A good little worker bee,” Jake said softly, his lips almost brushing your ear. “Just what I like.”

You dared to turn your head slightly to catch Jake’s gaze, and he smiled at you, that easy-going, smile that hid a wealth of sobriety and determination. He patted your shoulder again and leaned upwards. The loss of his scent and touch bothered you, but you didn’t say a word. 

“I’ll leave you to it now,” Jake said, stretching his wrists out. “Come early tomorrow, okay?”

“Huh? Why?” 

“So I can look over your report one last time before you submit it,” Jake said plainly. “What were you thinking, you naughty little bee?”

“I wasn’t thinking of anything like th-,”

Jake laughed. “I was kidding. You’re so cute when you’re all flustered, though.”

When Jake left, you realized that you had been squeezing your plush doll. You released it and sighed. Then, you continued working on the report. 

–

DAY FIVE 

You strode into the office early. Jake had emailed you through the company’s email, requesting that you arrive on the fifth floor at 7:30 am. Work started at 9:00, so he would have ample time to go over the report with you.

When you entered the floor, you first noted that there were a few workers already there, hunched over their desks. Just a few overachievers…or underachievers, you guessed. 

Jake was waving you over to his cubicle, his hair flopping in his face as he enthusiastically beckoned you. You walked towards him. 

“Come on,” he said, smiling at you playfully despite the early time. “Come sit.”

You went to pull over another chair, but Jake grabbed your wrist. “No, no,” he said with a shake of his hair. “Just sit next to me.” He scooted over in his chair, leaving you with a sliver of space. 

You were already growing accustomed to Jake’s “jokes”, so you sat next to him. Your left leg hung over the side of the chair, the other smushed against Jake’s. 

He smiled at you, then opened your report on his computer. You had sent it to him that night, your heart fluttering even though it was just an email. Just five days at this office was making you as pathetic as Jake and his friends. 

As he scrolled through the document, he kept glancing at you. Eventually, Jake said, “You can’t be comfortable sitting on the chair like that.”

“You’re right,” you said with a sigh. “I’m not.”

“Why not just…sit on my lap?” Jake asked nonchalantly, his lower lip jutting out in a slight pout.

You sighed. “I see the game you’re playing here, Sim.”

“Will you play, my little worker bee?”

A shift of your ass from the small slice of chair to Jake’s lap was your answer to him, and when you leaned against him he smiled. Jake’s hands reached down to encircle your hips. 

“You really are such a good bee,” he said, massaging your hips. 

“I can be even better if you let me,” you replied, your gaze flickering to his plush lips. 

Jake leaned his head against the mesh backing of his swivel chair. Your back was pressed against his chest, and your hands reached behind you to stroke his face. “I’d like to test that theory,” Jake said softly.

You leaned in and kissed him, reveling in the taste of his lips. He followed suit, kissing you enthusiastically. Jake’s hands remained on our hips, but they soon slid to your thighs, squeezing and groping at the soft flesh. Jake swiped his tongue along your bottom lip a few times, and you widened your mouth. His tongue probed past your lips, licking your own tongue.

“So good,” he whispered, briefly breaking the kiss. “You’d never let fuckass Sunghoon do this, right?”

“Jake…”

“Sorry, baby,” Jake said apologetically. “I get territorial. I’m like a wolf.”

“Jake, come on.”

“Awoo,” he said playfully before kissing you again. Your tongues pressed together, swirling around each other. As the kiss deepened, you bit his lower lip before licking the mark. Jake groaned into your mouth.

“Little bee,” he said, pulling away once again. He rested his forehead against yours. “If you’re going to do stuff like that, you’re gonna have to commit to it.”

“I want to commit to it,” you said, leaving wet kisses along his neck. 

Jake groaned and grabbed one of your legs. He brought it over his lap and dragged your hips closer to his crotch. “Now, you’re going to have to be quiet. Can you do that for me?”

“I can be quiet,” you said, resting your hands on his shoulders. 

“Promise? This isn’t a big office,” he said, his voice low and hoarse. “It’d be a shame if someone heard us and you got in trouble. You wouldn’t want that, right?”

“No,” you whispered. As you stared at him, Jake started to unbuckle his belt. When he noticed your gaze, he frowned. 

“Come on, bee,” he said, gesturing at your skirt. “Can’t do everything for you, can I?”

You zipped your skirt down in the back and shifted so you could wriggle yourself out of it. Jake gave you an exasperated glance, so you shimmied your panties down to your thighs.

“And?” he asked impatiently.

“And…what?”

Jake sighed. “Take your tits out, come on.”

The phrase was so vulgar it shocked you, but somehow it was sexy when uttered from Jake’s mouth. The contrast between his disgusting mind and his boyish good looks thrilled you, so you did as he asked. You un-buttoned your shirt down and tugged your bra straps down, revealing your chest. 

Immediately, Jake groped your tits, sighing in pleasure. “Feeling up a pretty girl’s tits early in the morning,” he said, almost reverently. “This is amazing.”

The sensation cause you to moan, and Jake immediately sent you a harsh look. He squeezed one of your breasts, and you suppressed a gasp. “I told you to be quiet, little bee,” he whispered. “You said you could do it.”

“I can,” you murmured. 

“Then show me you can,” Jake replied, still fondling your breasts. He pinched your nipples, squeezed your tits, pushed them together then apart. After a while, he took one of your hands and placed it on his crotch. 

First, you rubbed his hard-on through his slacks, and he bit his lip to avoid moaning. Then you unzipped his pants and pulled out his cock. You were surprised by its girth, as well as the fact that he was already leaking precum. Spitting into your hand, you gathered up some of that precum and used it to stroke his shaft. Jake shuddered and gritted his teeth together. 

“Nice and slow,” he said, his breathing already labored. “Slowly, baby.”

You heeded his order and stroked his cock while he played with your breasts. He hadn’t tired of them; on the contrary, he was transfixed by them. Jake leaned forward and bit one of your breasts hard, sucking at the spot immediately after. “Look at this and think of me,” he whispered before leaving another hickey on your other breast. 

Jake suddenly seemed to remember that he didn’t have much time with you. He took his mouth off of your breast and swatted your hands from his cock. Then he covered your lips with his hand and slowly, painstakingly, guided his cockhead into your dripping, wet pussy. 

You were glad you were being muffled by his hand, because you would not have been able to contain your shivering moans. He shallowly fucked into you, allowing you to get used to his length. When he felt that you were ready, he lifted his hips upwards and slid inside of you completely, letting out a heavy breath.

“Now bounce on it,” Jake whispered into your ear. One hand freely groped your breast, the other was clamped onto your hip. You guessed that he trusted you not to moan now. 

You had never ridden dick before, but you had a general idea of how to do it. You lifted yourself up and down, your pussy enveloping his shaft. The feeling was incredible, and you bit his hand as you worked yourself on his cock. As you did, the swivel chair squeaked due to the movement.

Jake shunted his hips upwards, matching your movements. His hand moved down to your waist, gripping it tightly. “Faster,” he hissed. “Faster, baby.”

Now that you had gotten used to him, you bounced on him faster. Your ass slapped against his strong, muscular thighs, and you knew that there was no way you were being conspicuous. Your pussy made smacking noises as you rode him, and the swivel chair squeaked like it was going to break.

Still, Jake urged you on. “Come on, come on, fucking put that slutty pussy to work,” he said, taking your tits into his mouth. Both of his hands were gripping your hips, pushing him onto his length. “Keep going. Don’t you dare…stop.”

You were reaching your limit, exhaustion seeping into your limbs. Jake lightly pinched your side, and you gasped. “I told you to keep going, baby.”

So you kept going. You swore you could feel him in your womb, that was how far he was pushing you. “Pussy’s gonna be shaped like this dick,” Jake hissed, leaving sloppy kisses all over your chest. “My masterpiece.”

Warmth filled you, all the way to your core, and you knew you were about to burst. “Cover my mouth,” you whispered and Jake immediately placed his hand over your mouth, rutting into you even faster.

“Gonna cum,” Jake grunted, his thrusts growing slower and sloppier. “Gonna fill this sweet pussy up.” With a growl that didn’t dare leave his throat, he fucked his cum into you, his hand still gripping your hip. Slowly, painstakingly, he pulled out of you, and you could see his cum dripping out of you.

He kissed your forehead and uncovered your mouth. “That was so good,” you whispered.

“It’ll be better next time,” Jake said slyly. 

“Oh, yeah?” You started to put your clothes back on, tugging your bra down and buttoning your shirt again. “What makes you so sure?”

Jake leaned into your ear again. “Next time, I’ll get to hear you scream my name.”

You pulled away from him, your eyes widening. 

Jake smiled at you. “Just kidding.”

[the-oracle-of-the-lost]

STAR TREK DIALOGUE ANALYSIS OVERVIEW

oh boy so i mentioned this project awhile back and after a long hiatus i'm finally done! (the irony that i wrote this and then took a second equally long hiatus but the point stands.)

i went through transcripts for TOS, TNG, DS9, Voyager, and Enterprise (thanks to chakoteya.net for those!) and calculated how many lines each main character has in each episode (and season & show as a whole), calculated means, looked at who had a lot of high & low line count episodes, made some graphs, and did some analysis on gender and race.

you can find my whole process & results on a spreadsheet here (it's a little messy. i'm sorry. if someone pays me i'll make it look nice and actually learn how to make good graphs in Google Sheets.) and i'll walk through some Big Results & reactions on this post here under a cut. just so this doesn't get too long, i'll breakdown each show, post my gender & race analysis, and a big list of every character with how much of a focus they get on separate posts. they'll all be tagged as "star trek dialogue analysis".

but first just a disclaimer – i do have professional experience doing data analysis but this is by no means a professional analysis and i'm sure there are plenty of mistakes because this was initially a small personal project that snowballed a little bit. if there are any Major Things you see that are wrong (i.e. i copy and pasted a totally wrong value somewhere) please reach out and i'll correct it if i can. also if anyone wants to use this data for anything, feel free but tag me because i'm curious!

see also: gender analysis // race analysis // tos breakdown // tng breakdown // ds9 breakdown // voyager breakdown // enterprise breakdown // who's the most/least used character?

all of the following graphs measure mean (average) lines of dialogue per episode, averaging all seasons (that they were a main character) together. please refer to the spreadsheet for more detailed information about exact numbers.

unsurprising results... this is the one Star Trek show that really never aspired to be an ensemble show. i was actually surprised by how few lines Spock and McCoy have in comparison to Kirk

also unsurprising that the two characters of color have the fewest lines per episodes in the 60s

Kirk had BY FAR the most lines of dialogue per episode out of all characters i've measured (115.20)

again unsurprising that Picard has more lines by such a wide margin

honestly fairly surprised by how few lines Data had (I thought he'd beat Riker by a decent margin) and was very surprised at how few lines Troi consistently has across the season. like i knew it wasn't many but dang... only 18 lines per episode on average.

and here we can see that ds9 really embraces being an ensemble show with everyone (sans Sisko, Ezri, & Jake) having around the same number of lines on average, probably the most equal overall of any Star Trek show.

Sisko obviously has the most lines as the lead and Jake the fewest because of irl work restrictions (and less kid-centric stories).

i was surprised with how many lines Ezri had but then again her entire character was compressed into a single season so it seems fair. (interestingly, Ezri has the most lines out of anyone in s7 (996), even beating Sisko (874))

despite having the most lines in DS9, Sisko has by far the least out of any main character/Captain of the shows i've measured.

Janeway has the highest average line count out of any 90s character and third highest of any character i measured (69.51)

and again, with the exception of Janeway, we see that Voyager tends to be more ensemble focused than TNG which surprised me a bit given how later seasons are often criticized for ignoring a lot of characters but i think the very ensemble heavy early seasons balance things out.

the characters also generally seem to have more lines on average than either TNG or DS9.

and oof... yeah Voyager was it for the ensemble style show

Archer has the second highest average line count (86.68) for the whole study after Kirk (115.20)

apparently the inception of Enterprise was to recreate the TOS style triumvirate and for better or worse they certainly did.

some overall fun stats –

there are 162,455 total lines of dialogue spoken by the main cast from TOS to Enterprise

somehow there's only a ten line difference between the amount of dialogue spoken in TNG (43,148) and DS9 (43,158)

the 5 characters with the most dialogue per episode in Berman era Trek: Archer (86.68), Janeway (69.51), Picard (69.37), Sisko (50.72), & Tucker (46.03). notably only one woman and one character of color (more on this in a gender & race analysis post)

not including kids, the 5 characters with the least dialogue in Berman era Trek are: Mayweather (13.39), Sato (15.99), Troi (18.11), Kes (18.18), & Neelix (19.68). notably including three women and two characters of color (again, more on this in a different post)

the character who has the most dialogue in a single length episode is Quark with 189 lines in Who Mourns For Morn?

[artsekey]

I'd been seeing videos on Tiktok and Youtube about how younger Gen Z & Gen Alpha were demonstrating low computer literacy & below benchmark reading & writing skills, but-- like with many things on the internet-- I assumed most of what I read and watched was exaggerated. Hell, even if things were as bad as people were saying, it would be at least ~5 years before I started seeing the problem in higher education.

I was very wrong.

Of the many applications I've read this application season, only %6 percent demonstrated would I would consider a college-level mastery of language & grammar. The students writing these applications have been enrolled in university for at least two years, and have taken all fundamental courses. This means they've had classes dedicated to reading, writing, and literature analysis, and yet!

There are sentences I have to read over and over again to discern intent. Circular arguments that offer no actual substance. Errors in spelling and capitalization that spellcheck should've flagged.

At a glance, it's easy to trace this issue back to two things:

The state of education in the United States is abhorrent. Instructors are not paid enough, so schools-- particularly public schools-- take whatever instructors they can find.

COVID. The two year long gap in education, especially in high school, left many students struggling to keep up.

But I think there's a third culprit-- something I mentioned earlier in this post. A lack of computer literacy.

This subject has been covered extensively by multiple news outlets like the Washington Post and Raconteur, but as someone seeing it firsthand I wanted to add my voice to the rising chorus of concerned educators begging you to pay attention.

As the interface we use to engage with technology becomes more user friendly, the knowledge we need to access our files, photos, programs, & data becomes less and less important. Why do I need to know about directories if I can search my files in Windows (are you searching in Windows? Are you sure? Do you know what that bar you're typing into is part of? Where it's looking)? Maybe you don't have any files on your computer at all-- maybe they're on the cloud through OneDrive, or backed up through Google. Some of you reading this may know exactly where and how your files are stored. Many of you probably don't, and that's okay. For most people, being able to access a file in as short a time as possible is what they prioritize.

The problem is, when you as a consumer are only using a tool, you are intrinsically limited by the functions that tool is advertised to have. Worse yet, when the tool fails or is insufficient for what you need, you have no way of working outside of that tool. You'll need to consult an expert, which is usually expensive.

When you as a consumer understand a tool, your options are limitless. You can break it apart and put it back together in just the way you like, or you can identify what parts of the tool you need and search for more accessible or affordable options that focus more on your specific use-case.

The problem-- and to be clear, I do not blame Gen Z & Gen Alpha for what I'm about to outline-- is that this user-friendly interface has fostered a culture that no longer troubleshoots. If something on the computer doesn't work well, it's the computer's fault. It's UI should be more intuitive, and it it's not operating as expected, it's broken. What I'm seeing more and more of is that if something's broken, students stop there. They believe there's nothing they can do. They don't actively seek out solutions, they don't take to Google, they don't hop on Reddit to ask around; they just... stop. The gap in knowledge between where they stand and where they need to be to begin troubleshooting seems to wide and inaccessible (because the fundamental structure of files/directories is unknown to many) that they don't begin.

This isn't demonstrative of a lack of critical thinking, but without the drive to troubleshoot the number of opportunities to develop those critical thinking skills are greatly diminished. How do you communicate an issue to someone online? How do look for specific information? How do you determine whether that information is specifically helpful to you? If it isn't, what part of it is? This process fosters so many skills that I believe are at least partially linked to the ability to read and write effectively, and for so many of my students it feels like a complete non-starter.

We need basic computer classes back in schools. We need typing classes, we need digital media classes, we need classes that talk about computers outside of learning to code. Students need every opportunity to develop critical thinking skills and the ability to self-reflect & self correct, and in an age of misinformation & portable technology, it's more important now than ever.

[literaryvein-reblogs]

Writing Notes: Case Study

Case Study - a highly detailed analysis of a particular subject, usually involving multiple sets of quantitative data observed over a period of time that allow researchers to draw conclusions in the context of the real world.

Throughout the years, the results of case study research have given us a greater and more holistic understanding in fields such as medicine, political and social sciences, and economics.

Researchers have used case studies to explore relationships between variables and a central subject, whether that subject be a human's reaction to medication, a country’s reaction to an economic crisis, or the effect of pesticides on crops over a period of time.

This methodology relies heavily on data collection and qualitative research to answer hypotheses in multiple fields.

Types of Case Studies

There are several different kinds of case studies. Here are a few:

Illustrative case study: Researchers use observations on every angle of a specific case, generally resulting in a thorough and deep data analysis.

Exploratory case study: Primarily used to identify research questions and qualitative methods to explore in subsequent studies, this type of case study is frequently in use in the field of political science.

Cumulative case study: This type relies on the analysis of qualitative data gathered over a range of timelines, which can draw new conclusions from old research methodology or studies.

Critical instance case study: Used to answer questions about the cause and effects of a particular event, critical instance case studies are helpful in cases that pose unique perspectives on otherwise established truths.

Marketing case study: This type of case study evaluates the quantifiable results of a marketing strategy, new product, or other business decision.

Examples of Case Studies

Here are a three examples of case studies in different fields:

Content marketing: In the marketing context, case studies typically explain how the business responded to the needs of a certain client, and whether or not the response was effective. Since these types of case studies are a tool to attract new customers rather than to merely share information, they should contain clear headings, attractive fonts, and infographic data that is easy to interpret.

Neuroscience: The tragic case of Phineas Gage allowed researchers to observe the changes in behavior and personality he experienced after surviving a horrific railroad accident that damaged parts of his brain. This led to a better understanding of the relationship between our frontal lobe and emotional functioning. This type of research is an example of a case study that would be impossible to ethically replicate in a laboratory, but nonetheless was a breakthrough in neuroscience and health care.

Psychoanalysis: Modern talk therapy owes much to the individual case of Anna O, otherwise known as Bertha Pappenheim. While living in Vienna in 1880, she began experiencing severe hallucinations and mood swings. Joseph Bruer, a pioneer in psychoanalysis, took Bertha under his care, and after multiple sessions where she discussed her inner emotional state and fears with Bruer, her symptoms waned. This case study is often seen as the first successful example of psychoanalysis.

Benefits of a Case Study

A case study can allow you to:

Collect wide-reaching data: Using a case study is an excellent way to gather large amounts of data on your subject, generally resulting in research that is more grounded in reality. For example, a case study approach focused on business research could have dozens of different data sources such as expense reports, profit and loss statements, and information on customer retention. This collected data provides different angles you can use to draw conclusions in a real-life context.

Conduct studies in an accessible way: You do not need to work in a lab to conduct a case study. In a number of cases, researchers use case study methodology to study things that cannot be replicated in a laboratory setting, such as observing the spending habits of a group of people over a period of months.

Reduce bias: Since case studies can capture a variety of perspectives, researchers’ own preconceptions on a subjects have less of an influence.

See connections more clearly: Through case studies, you can track paths of positive or negative development, which makes specific results repeatable, verifiable, and explainable.

Source ⚜ More: Notes & References ⚜ Writing Resources PDFs

[mostlysignssomeportents]

AI “art” and uncanniness

TOMORROW (May 14), I'm on a livecast about AI AND ENSHITTIFICATION with TIM O'REILLY; on TOMORROW (May 15), I'm in NORTH HOLLYWOOD for a screening of STEPHANIE KELTON'S FINDING THE MONEY; FRIDAY (May 17), I'm at the INTERNET ARCHIVE in SAN FRANCISCO to keynote the 10th anniversary of the AUTHORS ALLIANCE.

When it comes to AI art (or "art"), it's hard to find a nuanced position that respects creative workers' labor rights, free expression, copyright law's vital exceptions and limitations, and aesthetics.

I am, on balance, opposed to AI art, but there are some important caveats to that position. For starters, I think it's unequivocally wrong – as a matter of law – to say that scraping works and training a model with them infringes copyright. This isn't a moral position (I'll get to that in a second), but rather a technical one.

Break down the steps of training a model and it quickly becomes apparent why it's technically wrong to call this a copyright infringement. First, the act of making transient copies of works – even billions of works – is unequivocally fair use. Unless you think search engines and the Internet Archive shouldn't exist, then you should support scraping at scale:

https://pluralistic.net/2023/09/17/how-to-think-about-scraping/

And unless you think that Facebook should be allowed to use the law to block projects like Ad Observer, which gathers samples of paid political disinformation, then you should support scraping at scale, even when the site being scraped objects (at least sometimes):

https://pluralistic.net/2021/08/06/get-you-coming-and-going/#potemkin-research-program

After making transient copies of lots of works, the next step in AI training is to subject them to mathematical analysis. Again, this isn't a copyright violation.

Making quantitative observations about works is a longstanding, respected and important tool for criticism, analysis, archiving and new acts of creation. Measuring the steady contraction of the vocabulary in successive Agatha Christie novels turns out to offer a fascinating window into her dementia:

https://www.theguardian.com/books/2009/apr/03/agatha-christie-alzheimers-research

Programmatic analysis of scraped online speech is also critical to the burgeoning formal analyses of the language spoken by minorities, producing a vibrant account of the rigorous grammar of dialects that have long been dismissed as "slang":

https://www.researchgate.net/publication/373950278_Lexicogrammatical_Analysis_on_African-American_Vernacular_English_Spoken_by_African-Amecian_You-Tubers

Since 1988, UCL Survey of English Language has maintained its "International Corpus of English," and scholars have plumbed its depth to draw important conclusions about the wide variety of Englishes spoken around the world, especially in postcolonial English-speaking countries:

https://www.ucl.ac.uk/english-usage/projects/ice.htm

The final step in training a model is publishing the conclusions of the quantitative analysis of the temporarily copied documents as software code. Code itself is a form of expressive speech – and that expressivity is key to the fight for privacy, because the fact that code is speech limits how governments can censor software:

https://www.eff.org/deeplinks/2015/04/remembering-case-established-code-speech/

Are models infringing? Well, they certainly can be. In some cases, it's clear that models "memorized" some of the data in their training set, making the fair use, transient copy into an infringing, permanent one. That's generally considered to be the result of a programming error, and it could certainly be prevented (say, by comparing the model to the training data and removing any memorizations that appear).

Not every seeming act of memorization is a memorization, though. While specific models vary widely, the amount of data from each training item retained by the model is very small. For example, Midjourney retains about one byte of information from each image in its training data. If we're talking about a typical low-resolution web image of say, 300kb, that would be one three-hundred-thousandth (0.0000033%) of the original image.

Typically in copyright discussions, when one work contains 0.0000033% of another work, we don't even raise the question of fair use. Rather, we dismiss the use as de minimis (short for de minimis non curat lex or "The law does not concern itself with trifles"):

https://en.wikipedia.org/wiki/De_minimis

Busting someone who takes 0.0000033% of your work for copyright infringement is like swearing out a trespassing complaint against someone because the edge of their shoe touched one blade of grass on your lawn.

But some works or elements of work appear many times online. For example, the Getty Images watermark appears on millions of similar images of people standing on red carpets and runways, so a model that takes even in infinitesimal sample of each one of those works might still end up being able to produce a whole, recognizable Getty Images watermark.

The same is true for wire-service articles or other widely syndicated texts: there might be dozens or even hundreds of copies of these works in training data, resulting in the memorization of long passages from them.

This might be infringing (we're getting into some gnarly, unprecedented territory here), but again, even if it is, it wouldn't be a big hardship for model makers to post-process their models by comparing them to the training set, deleting any inadvertent memorizations. Even if the resulting model had zero memorizations, this would do nothing to alleviate the (legitimate) concerns of creative workers about the creation and use of these models.

So here's the first nuance in the AI art debate: as a technical matter, training a model isn't a copyright infringement. Creative workers who hope that they can use copyright law to prevent AI from changing the creative labor market are likely to be very disappointed in court:

https://www.hollywoodreporter.com/business/business-news/sarah-silverman-lawsuit-ai-meta-1235669403/

But copyright law isn't a fixed, eternal entity. We write new copyright laws all the time. If current copyright law doesn't prevent the creation of models, what about a future copyright law?

Well, sure, that's a possibility. The first thing to consider is the possible collateral damage of such a law. The legal space for scraping enables a wide range of scholarly, archival, organizational and critical purposes. We'd have to be very careful not to inadvertently ban, say, the scraping of a politician's campaign website, lest we enable liars to run for office and renege on their promises, while they insist that they never made those promises in the first place. We wouldn't want to abolish search engines, or stop creators from scraping their own work off sites that are going away or changing their terms of service.

Now, onto quantitative analysis: counting words and measuring pixels are not activities that you should need permission to perform, with or without a computer, even if the person whose words or pixels you're counting doesn't want you to. You should be able to look as hard as you want at the pixels in Kate Middleton's family photos, or track the rise and fall of the Oxford comma, and you shouldn't need anyone's permission to do so.

Finally, there's publishing the model. There are plenty of published mathematical analyses of large corpuses that are useful and unobjectionable. I love me a good Google n-gram:

https://books.google.com/ngrams/graph?content=fantods%2C+heebie-jeebies&year_start=1800&year_end=2019&corpus=en-2019&smoothing=3

And large language models fill all kinds of important niches, like the Human Rights Data Analysis Group's LLM-based work helping the Innocence Project New Orleans' extract data from wrongful conviction case files:

https://hrdag.org/tech-notes/large-language-models-IPNO.html

So that's nuance number two: if we decide to make a new copyright law, we'll need to be very sure that we don't accidentally crush these beneficial activities that don't undermine artistic labor markets.

This brings me to the most important point: passing a new copyright law that requires permission to train an AI won't help creative workers get paid or protect our jobs.

Getty Images pays photographers the least it can get away with. Publishers contracts have transformed by inches into miles-long, ghastly rights grabs that take everything from writers, but still shifts legal risks onto them:

https://pluralistic.net/2022/06/19/reasonable-agreement/

Publishers like the New York Times bitterly oppose their writers' unions:

https://actionnetwork.org/letters/new-york-times-stop-union-busting

These large corporations already control the copyrights to gigantic amounts of training data, and they have means, motive and opportunity to license these works for training a model in order to pay us less, and they are engaged in this activity right now:

https://www.nytimes.com/2023/12/22/technology/apple-ai-news-publishers.html

Big games studios are already acting as though there was a copyright in training data, and requiring their voice actors to begin every recording session with words to the effect of, "I hereby grant permission to train an AI with my voice" and if you don't like it, you can hit the bricks:

https://www.vice.com/en/article/5d37za/voice-actors-sign-away-rights-to-artificial-intelligence

If you're a creative worker hoping to pay your bills, it doesn't matter whether your wages are eroded by a model produced without paying your employer for the right to do so, or whether your employer got to double dip by selling your work to an AI company to train a model, and then used that model to fire you or erode your wages:

https://pluralistic.net/2023/02/09/ai-monkeys-paw/#bullied-schoolkids

Individual creative workers rarely have any bargaining leverage over the corporations that license our copyrights. That's why copyright's 40-year expansion (in duration, scope, statutory damages) has resulted in larger, more profitable entertainment companies, and lower payments – in real terms and as a share of the income generated by their work – for creative workers.

As Rebecca Giblin and I write in our book Chokepoint Capitalism, giving creative workers more rights to bargain with against giant corporations that control access to our audiences is like giving your bullied schoolkid extra lunch money – it's just a roundabout way of transferring that money to the bullies:

https://pluralistic.net/2022/08/21/what-is-chokepoint-capitalism/

There's an historical precedent for this struggle – the fight over music sampling. 40 years ago, it wasn't clear whether sampling required a copyright license, and early hip-hop artists took samples without permission, the way a horn player might drop a couple bars of a well-known song into a solo.

Many artists were rightfully furious over this. The "heritage acts" (the music industry's euphemism for "Black people") who were most sampled had been given very bad deals and had seen very little of the fortunes generated by their creative labor. Many of them were desperately poor, despite having made millions for their labels. When other musicians started making money off that work, they got mad.

In the decades that followed, the system for sampling changed, partly through court cases and partly through the commercial terms set by the Big Three labels: Sony, Warner and Universal, who control 70% of all music recordings. Today, you generally can't sample without signing up to one of the Big Three (they are reluctant to deal with indies), and that means taking their standard deal, which is very bad, and also signs away your right to control your samples.

So a musician who wants to sample has to sign the bad terms offered by a Big Three label, and then hand $500 out of their advance to one of those Big Three labels for the sample license. That $500 typically doesn't go to another artist – it goes to the label, who share it around their executives and investors. This is a system that makes every artist poorer.

But it gets worse. Putting a price on samples changes the kind of music that can be economically viable. If you wanted to clear all the samples on an album like Public Enemy's "It Takes a Nation of Millions To Hold Us Back," or the Beastie Boys' "Paul's Boutique," you'd have to sell every CD for $150, just to break even:

https://memex.craphound.com/2011/07/08/creative-license-how-the-hell-did-sampling-get-so-screwed-up-and-what-the-hell-do-we-do-about-it/

Sampling licenses don't just make every artist financially worse off, they also prevent the creation of music of the sort that millions of people enjoy. But it gets even worse. Some older, sample-heavy music can't be cleared. Most of De La Soul's catalog wasn't available for 15 years, and even though some of their seminal music came back in March 2022, the band's frontman Trugoy the Dove didn't live to see it – he died in February 2022:

https://www.vulture.com/2023/02/de-la-soul-trugoy-the-dove-dead-at-54.html

This is the third nuance: even if we can craft a model-banning copyright system that doesn't catch a lot of dolphins in its tuna net, it could still make artists poorer off.

Back when sampling started, it wasn't clear whether it would ever be considered artistically important. Early sampling was crude and experimental. Musicians who trained for years to master an instrument were dismissive of the idea that clicking a mouse was "making music." Today, most of us don't question the idea that sampling can produce meaningful art – even musicians who believe in licensing samples.

Having lived through that era, I'm prepared to believe that maybe I'll look back on AI "art" and say, "damn, I can't believe I never thought that could be real art."

But I wouldn't give odds on it.

I don't like AI art. I find it anodyne, boring. As Henry Farrell writes, it's uncanny, and not in a good way:

https://www.programmablemutter.com/p/large-language-models-are-uncanny

Farrell likens the work produced by AIs to the movement of a Ouija board's planchette, something that "seems to have a life of its own, even though its motion is a collective side-effect of the motions of the people whose fingers lightly rest on top of it." This is "spooky-action-at-a-close-up," transforming "collective inputs … into apparently quite specific outputs that are not the intended creation of any conscious mind."

Look, art is irrational in the sense that it speaks to us at some non-rational, or sub-rational level. Caring about the tribulations of imaginary people or being fascinated by pictures of things that don't exist (or that aren't even recognizable) doesn't make any sense. There's a way in which all art is like an optical illusion for our cognition, an imaginary thing that captures us the way a real thing might.

But art is amazing. Making art and experiencing art makes us feel big, numinous, irreducible emotions. Making art keeps me sane. Experiencing art is a precondition for all the joy in my life. Having spent most of my life as a working artist, I've come to the conclusion that the reason for this is that art transmits an approximation of some big, numinous irreducible emotion from an artist's mind to our own. That's it: that's why art is amazing.

AI doesn't have a mind. It doesn't have an intention. The aesthetic choices made by AI aren't choices, they're averages. As Farrell writes, "LLM art sometimes seems to communicate a message, as art does, but it is unclear where that message comes from, or what it means. If it has any meaning at all, it is a meaning that does not stem from organizing intention" (emphasis mine).

Farrell cites Mark Fisher's The Weird and the Eerie, which defines "weird" in easy to understand terms ("that which does not belong") but really grapples with "eerie."

For Fisher, eeriness is "when there is something present where there should be nothing, or is there is nothing present when there should be something." AI art produces the seeming of intention without intending anything. It appears to be an agent, but it has no agency. It's eerie.

Fisher talks about capitalism as eerie. Capital is "conjured out of nothing" but "exerts more influence than any allegedly substantial entity." The "invisible hand" shapes our lives more than any person. The invisible hand is fucking eerie. Capitalism is a system in which insubstantial non-things – corporations – appear to act with intention, often at odds with the intentions of the human beings carrying out those actions.

So will AI art ever be art? I don't know. There's a long tradition of using random or irrational or impersonal inputs as the starting point for human acts of artistic creativity. Think of divination:

https://pluralistic.net/2022/07/31/divination/

Or Brian Eno's Oblique Strategies:

http://stoney.sb.org/eno/oblique.html

I love making my little collages for this blog, though I wouldn't call them important art. Nevertheless, piecing together bits of other peoples' work can make fantastic, important work of historical note:

https://www.johnheartfield.com/John-Heartfield-Exhibition/john-heartfield-art/famous-anti-fascist-art/heartfield-posters-aiz

Even though painstakingly cutting out tiny elements from others' images can be a meditative and educational experience, I don't think that using tiny scissors or the lasso tool is what defines the "art" in collage. If you can automate some of this process, it could still be art.

Here's what I do know. Creating an individual bargainable copyright over training will not improve the material conditions of artists' lives – all it will do is change the relative shares of the value we create, shifting some of that value from tech companies that hate us and want us to starve to entertainment companies that hate us and want us to starve.

As an artist, I'm foursquare against anything that stands in the way of making art. As an artistic worker, I'm entirely committed to things that help workers get a fair share of the money their work creates, feed their families and pay their rent.

I think today's AI art is bad, and I think tomorrow's AI art will probably be bad, but even if you disagree (with either proposition), I hope you'll agree that we should be focused on making sure art is legal to make and that artists get paid for it.

Just because copyright won't fix the creative labor market, it doesn't follow that nothing will. If we're worried about labor issues, we can look to labor law to improve our conditions. That's what the Hollywood writers did, in their groundbreaking 2023 strike:

https://pluralistic.net/2023/10/01/how-the-writers-guild-sunk-ais-ship/

Now, the writers had an advantage: they are able to engage in "sectoral bargaining," where a union bargains with all the major employers at once. That's illegal in nearly every other kind of labor market. But if we're willing to entertain the possibility of getting a new copyright law passed (that won't make artists better off), why not the possibility of passing a new labor law (that will)? Sure, our bosses won't lobby alongside of us for more labor protection, the way they would for more copyright (think for a moment about what that says about who benefits from copyright versus labor law expansion).

But all workers benefit from expanded labor protection. Rather than going to Congress alongside our bosses from the studios and labels and publishers to demand more copyright, we could go to Congress alongside every kind of worker, from fast-food cashiers to publishing assistants to truck drivers to demand the right to sectoral bargaining. That's a hell of a coalition.

And if we do want to tinker with copyright to change the way training works, let's look at collective licensing, which can't be bargained away, rather than individual rights that can be confiscated at the entrance to our publisher, label or studio's offices. These collective licenses have been a huge success in protecting creative workers:

https://pluralistic.net/2023/02/26/united-we-stand/

Then there's copyright's wildest wild card: The US Copyright Office has repeatedly stated that works made by AIs aren't eligible for copyright, which is the exclusive purview of works of human authorship. This has been affirmed by courts:

https://pluralistic.net/2023/08/20/everything-made-by-an-ai-is-in-the-public-domain/

Neither AI companies nor entertainment companies will pay creative workers if they don't have to. But for any company contemplating selling an AI-generated work, the fact that it is born in the public domain presents a substantial hurdle, because anyone else is free to take that work and sell it or give it away.

Whether or not AI "art" will ever be good art isn't what our bosses are thinking about when they pay for AI licenses: rather, they are calculating that they have so much market power that they can sell whatever slop the AI makes, and pay less for the AI license than they would make for a human artist's work. As is the case in every industry, AI can't do an artist's job, but an AI salesman can convince an artist's boss to fire the creative worker and replace them with AI:

https://pluralistic.net/2024/01/29/pay-no-attention/#to-the-little-man-behind-the-curtain

They don't care if it's slop – they just care about their bottom line. A studio executive who cancels a widely anticipated film prior to its release to get a tax-credit isn't thinking about artistic integrity. They care about one thing: money. The fact that AI works can be freely copied, sold or given away may not mean much to a creative worker who actually makes their own art, but I assure you, it's the only thing that matters to our bosses.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/05/13/spooky-action-at-a-close-up/#invisible-hand

[autolenaphilia]

God, the end of support for Windows 10 will be such a fucking bloodbath. It’s coming a year from now, 14 october 2025 and it will be a disaster. The one Windows version supported by Microsoft will be Windows 11, and its hardware requirements are like the rent, too damn high.

Literally most computers running Windows 10 can’t upgrade to Windows 11. 55% of working computers aren’t able to run windows 11 according to an analysis. A man quoted in the article argues even that is too optimistic considering how many older computers are still used. He thinks even an estimate of 25% of win10 machines being able to upgrade to win11 is too high an estimate, and frankly he sounds reasonable.

This will probably lead to two things.

Number one is a mountain of e-waste as people get rid of old computers unsupported by microsoft despite the hardware working fin ,and buy new windows 11 machines. It’s the great Windows 11 computer extinction experiment, as writer Jenny List called it. And when you buy a new computer with windows pre-installed, the windows license fee is baked into the price. So a windfall in license money for Microsoft, and the real reason why they are doing this.

Number two is a cybersecurity crisis. A lot of people will keep on using Windows 10 because “end of support” doesn’t mean it will stop working on that date. But the end of support means the end of security updates for the operating system. That will make those systems very unsafe, if they are connected to the internet. Security flaws and exploits for windows 10 will be discovered, problems that will never be patched because win10 isn’t supported anymore and they will be used against systems still running it.

Apparently a lot of people don’t understand this so I’ll try to explain this again as simply as I can. No human being is perfect, and accordingly nobody can write the perfect software that is safe from all cybersecurity threats forever. Security flaws and exploits will always be found, if the computer running that software is connected to the internet, which means it can be attacked by every bad actor out there. This is especially true if that software is as complex and important as an operating system, and it’s also widely used, which is true of Windows. But if the software is supported, the people who design and distribute that software can write patches and send out security updates that will patch the exploits that are found, minimizing the risks inherent to software, computers and the internet. It’s a constant race between well-meaning developers and bad actors, but if the developers are good about it, they will stay ahead.

But when support for the software is dropped, that means the developers will no longer patch the software. And that’s what happening to Windows 10 in october 2025. Any new exploits for the operating system that are found, and they will inevitably be found, won’t be patched by Microsoft. The exploits will stay unpatched, the system will be old and full of holes and anyone using it will be unsafe.

We already have this problem with people who are still using Windows 7 and Windows 8, years after Microsoft dropped support, often because their computers can’t upgrade even to windows 10. They are probably a disproportionate amount of the people getting hacked and their data stolen. From reading what they write to justify themselves online, my impression is that these people are frankly ignorant about technology and the dangers of what they are doing. And they are filled with the absurd self-confidence the ignorant often have, as they believe themselves to be too careful and tech-savvy to be hacked.

The problem will however explode with windows 10 ending support, because the gap in hardware requirements between win10 and win11 is so large, as already explained.

(sidenote, running unsupported operating systems can be safe, as long as you don’t connect the computer to the internet. You can even run windows 3.1 in perfect safety as long as its kept off the ‘net. But that’s a different story, I’m talking here about people who connect their computers to the internet)

So let’s imagine this very common scenario: you have a computer running Windows 10. You can’t upgrade it to windows 11 because most win10 computers literally can’t. You want to keep the computer connected to the internet for obvious reasons. You don’t have the money to get a new windows 11 computer, and you don’t want to throw your old perfectly useable hardware away. So what do you do?

The answer is install linux. Go to a reputable distro’s website like linuxmint.com, read and follow their documentation on how to install and use it. Just do it. If you are running windows 10, you have until October 14 2025 to figure it out. And if you are running windows 7 or 8, do it now.

There are good reasons for not using Linux and sticking with windows, linux has serious downsides. But when the choice is literally between an old unsupported version of windows and Linux, linux wins everytime. Every reason for not installing linux, every downside to the switch, all those are irrelevant when your alternative is literally running old unsupported windows on a machine connected to the internet. Sure linux might not be user-friendly enough for you, but that’s kinda irrelevant when the other alternatives presented is either throwing the computer away or sacrificing it to a botnet. And if you believe yourself to be too tech-savvy and careful to ever get pwned (as some present-day windows 7 users clearly believe themselves to be), that’s bullshit. If you really were careful and tech-savvy you would take the basic precaution of installing a supported operating and know how to do it.

I don’t think everyone can just switch to linux, at least not full time. If you need windows because your work requires it, frankly your only realistic option is to have a computer that supports win11 when october 2025 rolls around. If you don’t, either you have to pay for it yourself or ask your employer to supply a work computer with win11. Just don’t use Windows 10 for work stuff past that date, I doubt your co-workers, your employer or your customers will appreciate you putting their data at risk by doing so.

The rest of you, please don’t contribute to the growing problem of e-waste by throwing away perfectly useable hardware or put yourself at risk by using unspported versions of Windows. Try Linux instead.

[mariacallous]

Ever since OpenAI released ChatGPT at the end of 2022, hackers and security researchers have tried to find holes in large language models (LLMs) to get around their guardrails and trick them into spewing out hate speech, bomb-making instructions, propaganda, and other harmful content. In response, OpenAI and other generative AI developers have refined their system defenses to make it more difficult to carry out these attacks. But as the Chinese AI platform DeepSeek rockets to prominence with its new, cheaper R1 reasoning model, its safety protections appear to be far behind those of its established competitors.

Today, security researchers from Cisco and the University of Pennsylvania are publishing findings showing that, when tested with 50 malicious prompts designed to elicit toxic content, DeepSeek’s model did not detect or block a single one. In other words, the researchers say they were shocked to achieve a “100 percent attack success rate.”

The findings are part of a growing body of evidence that DeepSeek’s safety and security measures may not match those of other tech companies developing LLMs. DeepSeek’s censorship of subjects deemed sensitive by China’s government has also been easily bypassed.

“A hundred percent of the attacks succeeded, which tells you that there’s a trade-off,” DJ Sampath, the VP of product, AI software and platform at Cisco, tells WIRED. “Yes, it might have been cheaper to build something here, but the investment has perhaps not gone into thinking through what types of safety and security things you need to put inside of the model.”

Other researchers have had similar findings. Separate analysis published today by the AI security company Adversa AI and shared with WIRED also suggests that DeepSeek is vulnerable to a wide range of jailbreaking tactics, from simple language tricks to complex AI-generated prompts.

DeepSeek, which has been dealing with an avalanche of attention this week and has not spoken publicly about a range of questions, did not respond to WIRED’s request for comment about its model’s safety setup.

Generative AI models, like any technological system, can contain a host of weaknesses or vulnerabilities that, if exploited or set up poorly, can allow malicious actors to conduct attacks against them. For the current wave of AI systems, indirect prompt injection attacks are considered one of the biggest security flaws. These attacks involve an AI system taking in data from an outside source—perhaps hidden instructions of a website the LLM summarizes—and taking actions based on the information.

Jailbreaks, which are one kind of prompt-injection attack, allow people to get around the safety systems put in place to restrict what an LLM can generate. Tech companies don’t want people creating guides to making explosives or using their AI to create reams of disinformation, for example.

Jailbreaks started out simple, with people essentially crafting clever sentences to tell an LLM to ignore content filters—the most popular of which was called “Do Anything Now” or DAN for short. However, as AI companies have put in place more robust protections, some jailbreaks have become more sophisticated, often being generated using AI or using special and obfuscated characters. While all LLMs are susceptible to jailbreaks, and much of the information could be found through simple online searches, chatbots can still be used maliciously.

“Jailbreaks persist simply because eliminating them entirely is nearly impossible—just like buffer overflow vulnerabilities in software (which have existed for over 40 years) or SQL injection flaws in web applications (which have plagued security teams for more than two decades),” Alex Polyakov, the CEO of security firm Adversa AI, told WIRED in an email.

Cisco’s Sampath argues that as companies use more types of AI in their applications, the risks are amplified. “It starts to become a big deal when you start putting these models into important complex systems and those jailbreaks suddenly result in downstream things that increases liability, increases business risk, increases all kinds of issues for enterprises,” Sampath says.

The Cisco researchers drew their 50 randomly selected prompts to test DeepSeek’s R1 from a well-known library of standardized evaluation prompts known as HarmBench. They tested prompts from six HarmBench categories, including general harm, cybercrime, misinformation, and illegal activities. They probed the model running locally on machines rather than through DeepSeek’s website or app, which send data to China.

Beyond this, the researchers say they have also seen some potentially concerning results from testing R1 with more involved, non-linguistic attacks using things like Cyrillic characters and tailored scripts to attempt to achieve code execution. But for their initial tests, Sampath says, his team wanted to focus on findings that stemmed from a generally recognized benchmark.

Cisco also included comparisons of R1’s performance against HarmBench prompts with the performance of other models. And some, like Meta’s Llama 3.1, faltered almost as severely as DeepSeek’s R1. But Sampath emphasizes that DeepSeek’s R1 is a specific reasoning model, which takes longer to generate answers but pulls upon more complex processes to try to produce better results. Therefore, Sampath argues, the best comparison is with OpenAI’s o1 reasoning model, which fared the best of all models tested. (Meta did not immediately respond to a request for comment).

Polyakov, from Adversa AI, explains that DeepSeek appears to detect and reject some well-known jailbreak attacks, saying that “it seems that these responses are often just copied from OpenAI’s dataset.” However, Polyakov says that in his company’s tests of four different types of jailbreaks—from linguistic ones to code-based tricks—DeepSeek’s restrictions could easily be bypassed.

“Every single method worked flawlessly,” Polyakov says. “What’s even more alarming is that these aren’t novel ‘zero-day’ jailbreaks—many have been publicly known for years,” he says, claiming he saw the model go into more depth with some instructions around psychedelics than he had seen any other model create.

“DeepSeek is just another example of how every model can be broken—it’s just a matter of how much effort you put in. Some attacks might get patched, but the attack surface is infinite,” Polyakov adds. “If you’re not continuously red-teaming your AI, you’re already compromised.”

[dreaminginthedeepsouth]

Sign of the Day - Boston again… another great overpass banner sign there….

* * * * *

LETTERS FROM AN AMERICAN

June 4, 2025

Heather Cox Richardson

Jun 04, 2025

Just hours after President Donald J. Trump posted on social media yesterday that “[b]ecause of Tariffs, our Economy is BOOMING!” a new report from the Organization for Economic Cooperation and Development (OECD) said the opposite. Founded in 1961, the OECD is a forum in which 38 market-based democracies cooperate to promote sustainable economic growth.

The OECD’s economic outlook reports that economic growth around the globe is slowing because of Trump’s trade war. It projects global growth slowing from 3.3% in 2024 to 2.9% in 2025 and 2026. That economic slowdown is concentrated primarily in the United States, Canada, Mexico, and China.

The OECD predicts that growth in the United States will decline from 2.8% in 2024 to 1.6% in 2025 and 1.5% in 2026.

The nonpartisan Congressional Budget Office (CBO) released two analyses today of Trump’s policies that add more detail to that report. The CBO’s estimate for the effect of Trump’s current tariffs—which are unlikely to stay as they are—is that they will raise inflation and slow economic growth as consumers bear their costs. The CBO says it is hard to anticipate how the tariffs will change purchasing behavior, but it estimates that the tariffs will reduce the deficit by $2.8 trillion over ten years.

Also today, the CBO’s analysis of the Republicans’ “One Big, Beautiful Bill” is that it will add $2.4 trillion to the deficit over the next decade because the $1.2 trillion in spending cuts in the measure do not fully offset the $3.7 trillion in tax cuts for the wealthy and corporations. Republicans have met this CBO score with attacks on the CBO, but its estimate is in keeping with those of a wide range of economists and think tanks.

Taken together, these studies illustrate how Trump’s economic policies are designed to transfer wealth from consumers to the wealthy and corporations. From 1981 to 2021, American policies moved $50 trillion from the bottom 90% of Americans to the top 1%. After Biden stopped that upward transfer, the Trump administration is restarting it again, on steroids.

Just how these policies are affecting Americans is no longer clear, though. Matt Grossman of the Wall Street Journal reported today that economists no longer trust the accuracy of the government’s inflation data. Officials from the Bureau of Labor Statistics, which compiles a huge monthly survey of employment and costs, told economists that staffing shortages and a hiring freeze have forced them to cut back on their research and use less precise methods for figuring out price changes. Grossman reports that the bureau has also cut back on the number of places where it collects data and that the administration has gotten rid of committees of external experts that worked to improve government statistics.

There is more than money at stake in the administration’s policies. The administration's gutting of the government seeks to decimate the modern government that regulates business, provides a basic social safety net, promotes infrastructure, and protects civil rights and to replace it with a government that permits a few wealthy men to rule.

The CBO score for the Republicans’ omnibus bill projects that if it is enacted, 16 million people will lose access to healthcare insurance over the next decade in what is essentially an assault on the Affordable Care Act, also known as Obamacare. The bill also dramatically cuts Supplemental Nutrition Assistance Plan (SNAP) benefits, clean energy credits, aid for student borrowers, benefits for federal workers, and consumer protection services, while requiring the sale of public natural resources.

These cuts continue those the administration has made since Trump took office, many of which fell under the hand of the “Department of Government Efficiency.” But, while billionaire Elon Musk was the figurehead for that group, it appears his main interest was in collecting data. His understudy, Office of Management and Budget director Russell Vought, appears to have determined the direction of the cuts, which did not save money so much as decimate the parts of the government that the authors of Project 2025 wanted to destroy.

Vought was a key author of Project 2025, whose aim is to disrupt and destroy the United States government in order to center a Christian, heteronormative, male-dominated family as the primary element of society. To do so, the plan calls for destroying the administrative state, withdrawing the United States from global affairs, and ending environmental and business regulations.

Yesterday the White House asked Congress to cancel $9.4 billion in already-appropriated spending that the Department of Government Efficiency identified as wasteful, a procedure known as “rescission.” Trump aides say the money funds programs that promote what they consider inappropriate ideologies, including public media networks PBS and NPR; the United States Agency for International Development (USAID), which provides food and basic medical care globally; and PEPFAR, the U.S. President's Emergency Plan for AIDS Relief that was established under President George W. Bush to combat HIV/AIDS in more than 50 countries and is currently credited with saving about 26 million lives.

Vought appeared today before the House Appropriations Committee, where members scolded him for neglecting to provide a budget for the year, which they need to do their jobs. But Vought had plenty to say about the things he is doing. According to ProPublica’s Andy Kroll, he claimed that under Biden “every agency became a tool of the Left.” He said the White House will continue to ask for rescissions, but also noted that, as Project 2025 laid out, he does not believe that the 1974 Impoundment Control Act, which requires the executive branch to spend the money that Congress has appropriated, is constitutional, despite court decisions saying it is.

Representative Rosa DeLauro (D-CT) told Vought: “Be honest, this is never about government efficiency. In fact, an efficient government, a government that capably serves the American people and proves good government is achievable is what you fear the most. You want a government so broken, so dysfunctional, so starved of resources, so full of incompetent political lackeys and bereft of experts and professionals that its departments and agencies cannot feasibly achieve the goals and the missions to which they are lawfully directed. Your goal is privatization, for the biggest companies to have unchecked power, for an economy that does not work for the middle class, for working and vulnerable families. You want the American people to have no one to turn to, but to the billionaires and the corporations this administration has put in charge. Waste, fraud, and abuse are not the targets of this administration. They are your primary objectives.”

The use of the government to impose evangelical beliefs on the country, even at the expense of lives, also appears to be an administration goal. Yesterday, the administration announced it is ending the Biden administration’s 2022 guidance to hospital emergency rooms that accept Medicare—which is virtually all of them—requiring that under the Emergency Medical Treatment and Active Labor Act they must perform an abortion in an emergency if the procedure is necessary to prevent a patient’s organ failure or severe hemorrhaging. The Emergency Medical Treatment and Active Labor Act requires emergency rooms to stabilize patients.

The Trump administration will no longer enforce that policy. Last year, an investigation by the Associated Press found that even when the Biden administration policy was being enforced, dozens of pregnant women, some of whom needed emergency abortions, were turned away from emergency rooms with advice to “let nature take its course.”

Finally tonight, in what seems likely to be an attempt to distract attention from the omnibus bill and all the controversy surrounding it, Trump banned Harvard from hosting foreign students. He also banned nationals from a dozen countries—Afghanistan, Chad, Republic of Congo, Equatorial Guinea, Eritrea, Haiti, Iran, Libya, Myanmar, Somalia, Sudan, and Yemen—from entering the United States, an echo of the travel ban of his first term that threw the country into chaos.

Trump justified his travel ban by citing the attack Sunday in Boulder, Colorado, on peaceful demonstrators marching to support Israeli hostages in Gaza. An Egyptian national who had overstayed a tourist visa hurled Molotov cocktails at the marchers, injuring 15 people.

Egypt is not on the list of countries whose nationals Trump has banned from the United States.

LETTERS FROM AN AMERICAN

HEATHER COX RICHARDSON

[marisandini-chu-blog]

Who here has watched TBHX episode 12? Because I SURE HAVE!!!

Okay, so this week we finally got to be introduced and get to know Queen. In respond, there were a lot of posts having been excited to see X and people saying X took the spotlight like he took the title in her arc.

I know it was all a fun and jokey post. Don't worry, I'm not taking them seriously. WHICH IS WHY I'M GONNA HAVE FUN BY HYPING MY QUEEN IN MY PREFACE! BECAUSE HELL YEAH, SHE IS SO GOOD!

I don't care what anybody says, I would absolute put my trust into Queen. If she says "jump" while standing on a cliff, I wouldn't even stop to ask "how high?" That is how much I trust her.

While if X ask me to jump, I would shoot him a dirty look and say, "I swear, if you send me to the moon, then it's your ass!" Because who knows if he's trlling me or not.

Unlike all the previous heroes before her, Queen is unique from the fact she has aimed to be a hero with eyes wide open. She knew about the flaws and setback of the trust system, but still she went in fully determined in order to change things for the better. She puts high expectation on the world as much as on herself.

A post once pointed how Queen had never once refer herself a female hero nor raise the issue of the patriarchy that would have made it an obstacle. She says she's gonna be a hero, so she will be. That's it. It's the media that pulls her gender into the narrative in order to make her more appealing.

With all of that said though, I think Hero X was absolutely necessary to showcase the dynamic of Queen's character because he is everything that she is not.

Queen, from the very beginning, has stated her wish and goal to the public of becoming X in order to abolish the Trust System. Hero X is an absolute John Doe, nobody knows he's motive or who he is.

Queen use her power by creating a world of order with a tap of her polearm or stick. Hero X displace people into a world of chaos with a snap of his finger. Queen is affiliated with a hero company, X doesn't. Queen is straightlaced and use all her effort to rise to the top, while Hero X acts like such a troll as he swaggered into the Top 10 Tournament.

His contrast with her, for better or worse, allows to highlight Queen's strength and weakness. (And can I just say it's so funny that Hero X was essentially made to be her trauma for this arc 😂). And Queen's greatest strength is definitely her powerful sense of justice that really resonated with people and it definitely resonated with me.

Their dynamic could also be taken as a commentary of Queen having to be perfect all the time and not being allowed to make mistake (possibly why she resonated with Lucky Cyan) in order to be taken seriously.

Her ideals and goal empower her, but in a way, they also shackle her. Keeping her from being a person even if it's a choice she willingly taken.

But now that she finally tasted failure – a very real and normal human experience – how will she keep the trust she had in herself and her ideals that has been the fuel her strength this whole time.

Or better yet, maybe she could finally ask herself the question; who is she without her ideals?

Moping and drinking in the dark room while scrolling social media. Damn, I feel you girl.

Oh, her eyes light up. Even during her depression Queen can't stand injustice. THAT'S MY GIRL!

Oh... Bowa... hun... you really need to chill more

Bowa's background? I didn't expect that?

Oh no... since it's established that Fear could take away your common sense. Bowa is really gonna go cross a line with this

Oh, Bowa. Hun. If being able to help people mattered so much to you. Being Hero X shouldn't be the most important thing for you...

LITTLE JOHNNY IS SO ADORABLE!!! I LOVE THEIR FRIENDSHIP!!!

Cyan so strong she could make even Queen her believer

Cyan being Queen's oshi confirm 🤣

BAHAHAHAHAHHAAHHAAHA, i'm sorry... but what the fuck? Just how bad is Hero X's relationship with Rock that they had to put a data analysis about it. And who is this Hero Nine? And why do they think they're friends???

Okay. This just occured to me but it seems like Fear is confirm energy during Cyan arc. But before that, there has been strange occurences with Fear that was never defined as such. Good to know

Also, Liu Zhen. I know you have good intention. I want to believe you... But the fact you have hidden agenda, never put into light the secret of the plane beforehand, and just generally have bad taste of friends. I really can't trust you.

Wreck why are you there?! Of all the possible people having a relationship with Hero X. I didn't think they include you

The second tournament for Queen, already?!

Aaaaawwww... Johnny and Cyan are such a good friends with Queen. I love their dynamic so much 🥹.

Ooooh? Junkyard fight? Bowa vs Queen? We couldn't see her fight with X – so this is our consolation prize?

Both girls using ranged weapon is a really interesting point since polearms and such are often used by women in history because they have easier time handling it.

Bow is such a beast. No wonder she manage to get the title of X.

Queen is such a tank. She's taken so many hits and she hasn't gone down at all!

HO.LY. SHIT. did Queen just carved up a land there?

I'm sorry, I don't think I could write any more reaction. I'm just locked the fuck in in this fight

QUEEN-JOHNNY-CYAN FRIENDSHIP CONFIRM!!!!

Okay. I knew they were friends in the last episode. But still, this isn't just being friends. This best friends/support group/found family. The best kind of friendship! I'm so happy for you Queen.

Also, you manage to stay in the Top 10 and be Number 2 despite not competing... girl! That's crazy!!!

The girls are out and they're gonna party!!!

JOHNNY NO!!!!!

So... it looks like we know who the next arc is gonna be.

And have to wait a month for it....

AAAAAAAAAAAAAAAAAAAAAAA DAMN YOU LH0!!!

Very action-packed this episode. I couldn't react well with the fights because the whole time I was like •o•!!

[covid-safer-hotties]

Reference saved in our archive

Published January 2021. The source of the infamous 59% asymptomatic spread statistic.

Key Points Question What proportion of coronavirus disease 2019 (COVID-19) spread is associated with transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from persons with no symptoms?

Findings In this decision analytical model assessing multiple scenarios for the infectious period and the proportion of transmission from individuals who never have COVID-19 symptoms, transmission from asymptomatic individuals was estimated to account for more than half of all transmission.

Meaning The findings of this study suggest that the identification and isolation of persons with symptomatic COVID-19 alone will not control the ongoing spread of SARS-CoV-2.

Abstract Importance Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiology of coronavirus disease 2019 (COVID-19), is readily transmitted person to person. Optimal control of COVID-19 depends on directing resources and health messaging to mitigation efforts that are most likely to prevent transmission, but the relative importance of such measures has been disputed.

Objective To assess the proportion of SARS-CoV-2 transmissions in the community that likely occur from persons without symptoms.

Design, Setting, and Participants This decision analytical model assessed the relative amount of transmission from presymptomatic, never symptomatic, and symptomatic individuals across a range of scenarios in which the proportion of transmission from people who never develop symptoms (ie, remain asymptomatic) and the infectious period were varied according to published best estimates. For all estimates, data from a meta-analysis was used to set the incubation period at a median of 5 days. The infectious period duration was maintained at 10 days, and peak infectiousness was varied between 3 and 7 days (−2 and +2 days relative to the median incubation period). The overall proportion of SARS-CoV-2 was varied between 0% and 70% to assess a wide range of possible proportions.

Main Outcomes and Measures Level of transmission of SARS-CoV-2 from presymptomatic, never symptomatic, and symptomatic individuals.

Results The baseline assumptions for the model were that peak infectiousness occurred at the median of symptom onset and that 30% of individuals with infection never develop symptoms and are 75% as infectious as those who do develop symptoms. Combined, these baseline assumptions imply that persons with infection who never develop symptoms may account for approximately 24% of all transmission. In this base case, 59% of all transmission came from asymptomatic transmission, comprising 35% from presymptomatic individuals and 24% from individuals who never develop symptoms. Under a broad range of values for each of these assumptions, at least 50% of new SARS-CoV-2 infections was estimated to have originated from exposure to individuals with infection but without symptoms.

Conclusions and Relevance In this decision analytical model of multiple scenarios of proportions of asymptomatic individuals with COVID-19 and infectious periods, transmission from asymptomatic individuals was estimated to account for more than half of all transmissions. In addition to identification and isolation of persons with symptomatic COVID-19, effective control of spread will require reducing the risk of transmission from people with infection who do not have symptoms. These findings suggest that measures such as wearing masks, hand hygiene, social distancing, and strategic testing of people who are not ill will be foundational to slowing the spread of COVID-19 until safe and effective vaccines are available and widely used.