#Sue Fisher

[jgroffdaily]

@sunsetblvdmusical Finding new ways to dream with @caradelevingne, Jonathan Groff, @bensplatt, & @reneerapp 📸 Thanks for visiting us at Sunset Blvd.

Photo: @andyhenderson

Jonathan is with his high school drama teacher Sue Fisher, who probably baked the cookies for the cast.

[darwuzhere]

I have so many video ideas and one of them is 100% doing scene packs of the LPS2012 characters.

[dwobbitfromtheshire]

What if Steve saw Eddie's performance in the Upside Down?

Nancy made sure that Steve stayed with Dustin and Eddie while they were the distractions because she knew why Steve needed to stay even if he didn't. Meanwhile, Vickie would be going with her and Robin. It had been Vickie who tracked them down, looking for revenge for a cousin she never got to know. Thanks to Chrissy's mother, they never got to know each other. Luckily, Vickie had been open to listening and never once believed that Robin would harbor a murderer. So, the three young women marched off to kill Vecna while the three young men stayed behind.

"It's a big step for woman kind everywhere. They're going off to war while the men folk stay behind," Eddie said cheerfully, and Steve gave him a look while they set up the trailer. "What? I mean it. I'm totally down for being the one barefoot and pregnant in the kitchen. Let the women be the badasses they always have been."

"Yeah. I wouldn't mind being Mr. Mom," Steve said. "I definitely love to cook. If I could find the right man or woman. . .I mean. . . Shit."

"You too, huh?" Eddie asked, his eyes twinkling. "Man, can I tell you something, and you promise not to laugh?"

"Yeah, of course," Steve said.

"I've always been a bit envious that women can grow an entire human inside of them. It's like fucking magic," Eddie said, pausing, and before he knew it, he was rambling. "I feel like we should be worshipping at their feet with all the shit they have to go through. I was young, but I remember when my mom was pregnant with my brother, and it was tough on her. It was a rough pregnancy, and my dad was a misogynistic piece of shit. The doctors didn't think they would make it. It was so bad. I was there in the delivery room after begging to be there. The look on her face. . .she was so determined to bring him into this world, and she did. She was a warrior. He died a few months later. My dad was supposed to be watching him. He left him on the changing table and stepped out. . .well, you can guess what happened. She never forgave him, and I didn't either. She died a year later, and her heart had given out. She tried man, really, she did."

Eddie sniffled as he worked on turning the trailer into a cage. Steve stared at him with big eyes, his heart hurting for him.

"I'm sorry, Eddie," Steve said softly.

"He was just starting to get his Munson curls. They were the cutest little things. I think that's why I've gotten attached to Dustin. He would have been Dustin's age right now, and sometimes I wonder if he would be anything like Dustin is now. I try not to compare him to a ghost, but it's hard," Eddie said. "I definitely think of him like a brother, though."

A loud sob came from his left, and before he knew it, Dustin was throwing himself into Eddie's arms. Steve let them have their moment as he finished up, smiling softly as a deep wave of affection hit his chest. Once they broke the hug, they got the amps hooked up on the roof, and then they climbed up with Eddie's guitar. Steve watched as he flipped the guitar around, a look of glee on his face. He ripped his necklace off, his face serious.

"Chrissy, this is for you," Eddie said.

Then he was playing, and Steve watched in amazement. If anything was magic, it was him. Steve’s mouth was open as he watched his fingers move across the guitar and the way he focused. . .the way he put everything into it, he was beautiful. The lightning flashed in the background, enveloped him like it was a radiant light and not shitty weather from another dimension. It was like Eddie owned this world, like he was their God. He threw his head back and exposed his throat, his hair cascading backward. Steve was watching threw heavy eyelids now, and his heart was pounding nearly as loudly as the music. Steve knew he was gaping like an idiot now. Eddie glanced briefly at him and winked. Steve closed his mouth, blushing. Suddenly, he felt like maybe he should throw his underwear at him. Weird. He felt an elbow dig into his side, and he looked over to find Dustin wiggling his eyebrows at him. Steve rolled his eyes.

"You know if he married you, he really would be my brother," Dustin whispered.

"That's illegal," Steve scoffed.

"So, is us harboring a fugitive," Dustin scowled at him. "Why would that stop you both?"

"And your mom never officially adopted me," Steve said rolling his eyes.

"Yet. She's still arguing about it with Sue," Dustin said. "I keep telling them they can both adopt you."

"Sue wants to adopt me, too?" Steve asked.

"Oh, yeah, it's a thing," Dustin said.

"Technically, I'm an adult," Steve said.

"You can adopt adults, Steve."

The bats started coming. They climbed down and rushed into the trailer. Eddie pulled them into a hug, jumping up and down.

"That was ho - awesome!" Steve said, catching himself.

"What's hoawesome?" Dustin asked.

"Yes, Stevie, what is hoawesome?" Eddie asked, crossing his arms.

Suddenly, the bats started trying to get through the vents in the living room.

"Is this the only vent?!" Steve asked.

"My room!" Eddie yelled.

"Got it!" Steve yelled, grabbing his shield and running into Eddie's room.

Once they got the vents sealed, Eddie and Steve helped Dustin through the gate. They stood at the sheet and stared at each other. Eddie bowed, raising his hand to let Steve go first. He rolled his eyes and started climbing up. Eddie watched him with a grin, his eyes focused on his ass. He couldn't help but whistle.

"What was that?" Steve asked.

"Nothing," Eddie said quickly.

Once Steve made it through, Eddie started climbing up when he paused midway. He stared up at Steve, then looked down and looked back up as if he knew what he had to do. Steve glared at him. He knew that self sacrificing look.

"No you fucking don't!" Steve yelled out.

"Sorry."

He jumped down and cut the sheet. Steve cursed as he watched him run out the door. He turned to Dustin.

"For the sake of our mother, stay here," Steve said. "I'll bring him back."

He jumped into the gate, did a flip, and then ran out the door. Eddie was peddling off onto a bike. He knew what that asshole was doing. He was trying to buy the others more time, but Steve couldn't let him do it alone. It wasn't because Steve wanted to be the hero. It was because he was afraid that Eddie might die trying to do it, and he couldn't let that happen. He grabbed a molotov out of his bag. When the bats drew closer to Eddie, they knocked him off his bike. He pulled the cloth out and wrapped it around his spear. He doused it in alcohol and lit the spear on fire. Steve saw them bite into Eddie, their tails wrapped around his throat. He hollered and started waving the spear at them, beating them off Eddie. Suddenly, they all dropped. Eddie stood up shakily, clutching his side.

"Thanks, Ste-"

Steve drew him into a furious kiss. Eddie clutched his waist as he deepened the kiss, not caring that he was bleeding all over Steve or the fact that that he was bleeding. All he cared about was Steve's mouth and slipping his tongue inside. Suddenly, a pair of hands were pulling him away from Steve.

"Hey!" Eddie yelped.

"It's you who's bleeding," Nancy said furiously.

"Jesus, Wheeler. If you didn't want me kissing Steve all you had to do was say something," Eddie said.

"I'm perfectly happy with you kissing, Steve," Nancy said. "I just don't want you to die while doing it."

"It would be so worth it," Eddie replied and then pointed excitedly. "Oh, hey!"

Meanwhile, Vickie and Robin stood behind her with worried looks as they held hands.

"Yeah, we had the same idea, except we did it without the blood," Vickie replied.

"Smart," Eddie said, nodding.

"Alright, let's get the fuck out of here," Steve said.

As they walked towards the gate, Eddie leaned heavily on Steve. He realized something.

"Hey, we match!" Eddie exclaimed.

"Yeah, I think I'd rather we have matching tattoos," Steve said.

"That can be arranged, big boy," Eddie said.

"By the way," Steve whispered in his ear. "Your performance. . .so hot."

"I fucking knew that's what you meant to say," Eddie said. "So, back to those matching tattoos. . ."

"I don't know, I have to ask my moms but they're not going to like that interdimensional bats gave me some piercings, I doubt that they're going to let me get inked with a metalhead that's wanted by the police," Steve hummed.

"That's not a no!"

TWO DAYS LATER. . .

The world had been saved, Max was alright, Hop was alive, Eddie had been cleared of all charges, and Steve had been properly bullied into a hospital bed by both of his moms.

"Hey, moms, I was just wondering, and you can say no if you want, but can I get a matching tattoo with Eddie?" Steve asked.

"Absolutely not," Sue said, fluffing his pillows. "We're happy you found Eddie, but you are not getting a tattoo."

"What if it gets infected and you die?" Claudia asked as she fussed with his blankets.

"Dad -," Steve started.

"You're new to having family that cares, son," Charles said, without looking up from his paper. "Let me tell you something, mothers are usually right about this. Better let them swaddle you. I'm pretty sure that's what Claudia is trying to do now."

Claudia dropped the blanket and gave him a look.

"They said no, Eddie," Steve said to the other bed in the room.

"I heard," Eddie pouted.

[fleursfairiesedits]

editing random ppl

[vicontheinternet]

Good by to the beautiful fancasting of Kedar Williams-Sterling, Jordan fisher, mason gooding and Johnathan Davis and mason gooding as Johnny storm (I would’ve even takes Rudy pankow as Johnny) they would’ve embodied Johnny as well and they had his hotness too now we’re stuck with Joseph Quinn because y’all hype up white mediocrity and went ravenous of a mediocre white mans looks

[galpalaven]

WHAT if… I give my ILITW MC powers after being brought back from being Redfield (canon), and my ILW MC already has powers (canon), AND I give my ILB MC powers after defeating her grandmother and saving the town??

Jaxson has shadow powers and mind control for corruptions

Evie has the power to control water and some amount of sway over corruptions

Nalani has. Whatever bunch of powers Nalani has lol

BONUS: Penny has powers where you can take on someone’s illness/injury and they heal instantly as well as a certain amount of ability to sense the wellbeing of others. She also cannot be killed due to the terms of the deal she made with the Power :3c

[salfishersimp2]

This is the cutest thing I've ever seen and I just saw a Will Solace fanart

can i request a drawing of sal from sally face with gizmo

yes!!!!!

(thank you for all the lovely requests so far by the way!! i hope to get to more of them when i can ^^)

[mostlysignssomeportents]

Gig apps trap reverse centaurs in Skinner boxes

Enshittification is the process by which digital platforms devour themselves: first they dangle goodies in front of end users. Once users are locked in, the goodies are taken away and dangled before business customers who supply goods to the users. Once those business customers are stuck on the platform, the goodies are clawed away and showered on the platform’s shareholders:

https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys

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/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men

Enshittification isn’t just another way of saying “fraud” or “price gouging” or “wage theft.” Enshittification is intrinsically digital, because moving all those goodies around requires the flexibility that only comes with a digital businesses. Jeff Bezos, grocer, can’t rapidly change the price of eggs at Whole Foods without an army of kids with pricing guns on roller-skates. Jeff Bezos, grocer, can change the price of eggs on Amazon Fresh just by twiddling a knob on the service’s back-end.

Twiddling is the key to enshittification: rapidly adjusting prices, conditions and offers. As with any shell game, the quickness of the hand deceives the eye. Tech monopolists aren’t smarter than the Gilded Age sociopaths who monopolized rail or coal — they use the same tricks as those monsters of history, but they do them faster and with computers:

https://doctorow.medium.com/twiddler-1b5c9690cce6

If Rockefeller wanted to crush a freight company, he couldn’t just click a mouse and lay down a pipeline that ran on the same route, and then click another mouse to make it go away when he was done. When Bezos wants to bankrupt Diapers.com — a company that refused to sell itself to Amazon — he just moved a slider so that diapers on Amazon were being sold below cost. Amazon lost $100m over three months, diapers.com went bankrupt, and every investor learned that competing with Amazon was a losing bet:

https://slate.com/technology/2013/10/amazon-book-how-jeff-bezos-went-thermonuclear-on-diapers-com.html

That’s the power of twiddling — but twiddling cuts both ways. The same flexibility that digital businesses enjoy is hypothetically available to workers and users. The airlines pioneered twiddling ticket prices, and that naturally gave rise to countertwiddling, in the form of comparison shopping sites that scraped the airlines’ sites to predict when tickets would be cheapest:

https://pluralistic.net/2023/02/27/knob-jockeys/#bros-be-twiddlin

The airlines — like all abusive businesses — refused to tolerate this. They were allowed to touch their knobs as much as they wanted — indeed, they couldn’t stop touching those knobs — but when we tried to twiddle back, that was “felony contempt of business model,” and the airlines sued:

https://www.cnbc.com/2014/12/30/airline-sues-man-for-founding-a-cheap-flights-website.html

And sued:

https://www.nytimes.com/2018/01/06/business/southwest-airlines-lawsuit-prices.html

Platforms don’t just hate it when end-users twiddle back — if anything they are even more aggressive when their business-users dare to twiddle. Take Para, an app that Doordash drivers used to get a peek at the wages offered for jobs before they accepted them — something that Doordash hid from its workers. Doordash ruthlessly attacked Para, saying that by letting drivers know how much they’d earn before they did the work, Para was violating the law:

https://www.eff.org/deeplinks/2021/08/tech-rights-are-workers-rights-doordash-edition

Which law? Well, take your pick. The modern meaning of “IP” is “any law that lets me use the law to control my competitors, competition or customers.” Platforms use a mix of anticircumvention law, patent, copyright, contract, cybersecurity and other legal systems to weave together a thicket of rules that allow them to shut down rivals for their Felony Contempt of Business Model:

https://locusmag.com/2020/09/cory-doctorow-ip/

Enshittification relies on unlimited twiddling (by platforms), and a general prohibition on countertwiddling (by platform users). Enshittification is a form of fishing, in which bait is dangled before different groups of users and then nimbly withdrawn when they lunge for it. Twiddling puts the suppleness into the enshittifier’s fishing-rod, and a ban on countertwiddling weighs down platform users so they’re always a bit too slow to catch the bait.

Nowhere do we see twiddling’s impact more than in the “gig economy,” where workers are misclassified as independent contractors and put to work for an app that scripts their every move to the finest degree. When an app is your boss, you work for an employer who docks your pay for violating rules that you aren’t allowed to know — and where your attempts to learn those rules are constantly frustrated by the endless back-end twiddling that changes the rules faster than you can learn them.

As with every question of technology, the issue isn’t twiddling per se — it’s who does the twiddling and who gets twiddled. A worker armed with digital tools can play gig work employers off each other and force them to bid up the price of their labor; they can form co-ops with other workers that auto-refuse jobs that don’t pay enough, and use digital tools to organize to shift power from bosses to workers:

https://pluralistic.net/2022/12/02/not-what-it-does/#who-it-does-it-to

Take “reverse centaurs.” In AI research, a “centaur” is a human assisted by a machine that does more than either could do on their own. For example, a chess master and a chess program can play a better game together than either could play separately. A reverse centaur is a machine assisted by a human, where the machine is in charge and the human is a meat-puppet.

Think of Amazon warehouse workers wearing haptic location-aware wristbands that buzz at them continuously dictating where their hands must be; or Amazon drivers whose eye-movements are continuously tracked in order to penalize drivers who look in the “wrong” direction:

https://pluralistic.net/2021/02/17/reverse-centaur/#reverse-centaur

The difference between a centaur and a reverse centaur is the difference between a machine that makes your life better and a machine that makes your life worse so that your boss gets richer. Reverse centaurism is the 21st Century’s answer to Taylorism, the pseudoscience that saw white-coated “experts” subject workers to humiliating choreography down to the smallest movement of your fingertip:

https://pluralistic.net/2022/08/21/great-taylors-ghost/#solidarity-or-bust

While reverse centaurism was born in warehouses and other company-owned facilities, gig work let it make the leap into workers’ homes and cars. The 21st century has seen a return to the cottage industry — a form of production that once saw workers labor far from their bosses and thus beyond their control — but shriven of the autonomy and dignity that working from home once afforded:

https://doctorow.medium.com/gig-work-is-the-opposite-of-steampunk-463e2730ef0d

The rise and rise of bossware — which allows for remote surveillance of workers in their homes and cars — has turned “work from home” into “live at work.” Reverse centaurs can now be chickenized — a term from labor economics that describes how poultry farmers, who sell their birds to one of three vast poultry processors who have divided up the country like the Pope dividing up the “New World,” are uniquely exploited:

https://onezero.medium.com/revenge-of-the-chickenized-reverse-centaurs-b2e8d5cda826

A chickenized reverse centaur has it rough: they must pay for the machines they use to make money for their bosses, they must obey the orders of the app that controls their work, and they are denied any of the protections that a traditional worker might enjoy, even as they are prohibited from deploying digital self-help measures that let them twiddle back to bargain for a better wage.

All of this sets the stage for a phenomenon called algorithmic wage discrimination, in which two workers doing the same job under the same conditions will see radically different payouts for that work. These payouts are continuously tweaked in the background by an algorithm that tries to predict the minimum sum a worker will accept to remain available without payment, to ensure sufficient workers to pick up jobs as they arise.

This phenomenon — and proposed policy and labor solutions to it — is expertly analyzed in “On Algorithmic Wage Discrimination,” a superb paper by UC Law San Franciscos Veena Dubal:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4331080

Dubal uses empirical data and enthnographic accounts from Uber drivers and other gig workers to explain how endless, self-directed twiddling allows gig companies pay workers less and pay themselves more. As @brianmerchant@mastodon.social explains in his LA Times article on Dubal’s research, the goal of the payment algorithm is to guess how often a given driver needs to receive fair compensation in order to keep them driving when the payments are unfair:

https://www.latimes.com/business/technology/story/2023-04-11/algorithmic-wage-discrimination

The algorithm combines nonconsensual dossiers compiled on individual drivers with population-scale data to seek an equilibrium between keeping drivers waiting, unpaid, for a job; and how much a driver needs to be paid for an individual job, in order to keep that driver from clocking out and doing something else. @ Here’s how that works. Sergio Avedian, a writer for The Rideshare Guy, ran an experiment with two brothers who both drove for Uber; one drove a Tesla and drove intermittently, the other brother rented a hybrid sedan and drove frequently. Sitting side-by-side with the brothers, Avedian showed how the brother with the Tesla was offered more for every trip:

https://www.youtube.com/watch?v=UADTiL3S67I

Uber wants to lure intermittent drivers into becoming frequent drivers. Uber doesn’t pay for an oversupply of drivers, because it only pays drivers when they have a passenger in the car. Having drivers on call — but idle — is a way for Uber to shift the cost of maintaining a capacity cushion to its workers.

What’s more, what Uber charges customers is not based on how much it pays its workers. As Uber’s head of product explained: Uber uses “machine-learning techniques to estimate how much groups of customers are willing to shell out for a ride. Uber calculates riders’ propensity for paying a higher price for a particular route at a certain time of day. For instance, someone traveling from a wealthy neighborhood to another tony spot might be asked to pay more than another person heading to a poorer part of town, even if demand, traffic and distance are the same.”

https://qz.com/990131/uber-is-practicing-price-discrimination-economists-say-that-might-not-be-a-bad-thing/

Uber has historically described its business a pure supply-and-demand matching system, where a rush of demand for rides triggers surge pricing, which lures out drivers, which takes care of the demand. That’s not how it works today, and it’s unclear if it ever worked that way. Today, a driver who consults the rider version of the Uber app before accepting a job — to compare how much the rider is paying to how much they stand to earn — is booted off the app and denied further journeys.

Surging, instead, has become just another way to twiddle drivers. One of Dubal’s subjects, Derrick, describes how Uber uses fake surges to lure drivers to airports: “You go to the airport, once the lot get kind of full, then the surge go away.” Other drivers describe how they use groupchats to call out fake surges: “I’m in the Marina. It’s dead. Fake surge.”

That’s pure twiddling. Twiddling turns gamification into gamblification, where your labor buys you a spin on a roulette wheel in a rigged casino. As a driver called Melissa, who had doubled down on her availability to earn a $100 bonus awarded for clocking a certain number of rides, told Dubal, “When you get close to the bonus, the rides start trickling in more slowly…. And it makes sense. It’s really the type of shit that they can do when it’s okay to have a surplus labor force that is just sitting there that they don’t have to pay for.”

Wherever you find reverse-centaurs, you get this kind of gamblification, where the rules are twiddled continuously to make sure that the house always wins. As a contract driver Amazon reverse centaur told Lauren Gurley for Motherboard, “Amazon uses these cameras allegedly to make sure they have a safer driving workforce, but they’re actually using them not to pay delivery companies”:

https://www.vice.com/en/article/88npjv/amazons-ai-cameras-are-punishing-drivers-for-mistakes-they-didnt-make

Algorithmic wage discrimination is the robot overlord of our nightmares: its job is to relentlessly quest for vulnerabilities and exploit them. Drivers divide themselves into “ants” (drivers who take every job) and “pickers” (drivers who cherry-pick high-paying jobs). The algorithm’s job is ensuring that pickers get the plum assignments, not the ants, in the hopes of converting those pickers to app-dependent ants.

In my work on enshittification, I call this the “giant teddy bear” gambit. At every county fair, you’ll always spot some poor jerk carrying around a giant teddy-bear they “won” on the midway. But they didn’t win it — not by getting three balls in the peach-basket. Rather, the carny running the rigged game either chose not to operate the “scissor” that kicks balls out of the basket. Or, if the game is “honest” (that is, merely impossible to win, rather than gimmicked), the operator will make a too-good-to-refuse offer: “Get one ball in and I’ll give you this keychain. Win two keychains and I’ll let you trade them for this giant teddy bear.”

Carnies aren’t in the business of giving away giant teddy bears — rather, the gambit is an investment. Giving a mark a giant teddy bear to carry around the midway all day acts as a convincer, luring other marks to try to land three balls in the basket and win their own teddy bear.

In the same way, platforms like Uber distribute giant teddy bears to pickers, as a way of keeping the ants scurrying from job to job, and as a way of convincing the pickers to give up whatever work allows them to discriminate among Uber’s offers and hold out for the plum deals, whereupon then can be transmogrified into ants themselves.

Dubal describes the experience of Adil, a Syrian refugee who drives for Uber in the Bay Area. His colleagues are pickers, and showed him screenshots of how much they earned. Determined to get a share of that money, Adil became a model ant, driving two hours to San Francisco, driving three days straight, napping in his car, spending only one day per week with his family. The algorithm noticed that Adil needed the work, so it paid him less.

Adil responded the way the system predicted he would, by driving even more: “My friends they make it, so I keep going, maybe I can figure it out. It’s unsecure, and I don’t know how people they do it. I don’t know how I am doing it, but I have to. I mean, I don’t find another option. In a minute, if I find something else, oh man, I will be out immediately. I am a very patient person, that’s why I can continue.”

Another driver, Diego, told Dubal about how the winners of the giant teddy bears fell into the trap of thinking that they were “good at the app”: “Any time there’s some big shot getting high pay outs, they always shame everyone else and say you don’t know how to use the app. I think there’s secret PR campaigns going on that gives targeted payouts to select workers, and they just think it’s all them.”

That’s the power of twiddling: by hoarding all the flexibility offered by digital tools, the management at platforms can become centaurs, able to string along thousands of workers, while the workers are reverse-centaurs, puppeteered by the apps.

As the example of Adil shows, the algorithm doesn’t need to be very sophisticated in order to figure out which workers it can underpay. The system automates the kind of racial and gender discrimination that is formally illegal, but which is masked by the smokescreen of digitization. An employer who systematically paid women less than men, or Black people less than white people, would be liable to criminal and civil sanctions. But if an algorithm simply notices that people who have fewer job prospects drive more and will thus accept lower wages, that’s just “optimization,” not racism or sexism.

This is the key to understanding the AI hype bubble: when ghouls from multinational banks predict 13 trillion dollar markets for “AI,” what they mean is that digital tools will speed up the twiddling and other wage-suppression techniques to transfer $13T in value from workers and consumers to shareholders.

The American business lobby is relentlessly focused on the goal of reducing wages. That’s the force behind “free trade,” “right to work,” and other codewords for “paying workers less,” including “gig work.” Tech workers long saw themselves as above this fray, immune to labor exploitation because they worked for a noble profession that took care of its own.

But the epidemic of mass tech-worker layoffs, following on the heels of massive stock buybacks, has demonstrated that tech bosses are just like any other boss: willing to pay as little as they can get away with, and no more. Tech bosses are so comfortable with their market dominance and the lock-in of their customers that they are happy to turn out hundreds of thousands of skilled workers, convinced that the twiddling systems they’ve built are the kinds of self-licking ice-cream cones that are so simple even a manager can use them — no morlocks required.

The tech worker layoffs are best understood as an all-out war on tech worker morale, because that morale is the source of tech workers’ confidence and thus their demands for a larger share of the value generated by their labor. The current tech layoff template is very different from previous tech layoffs: today’s layoffs are taking place over a period of months, long after they are announced, and laid off tech worker is likely to be offered a months of paid post-layoff work, rather than severance. This means that tech workplaces are now haunted by the walking dead, workers who have been laid off but need to come into the office for months, even as the threat of layoffs looms over the heads of the workers who remain. As an old friend, recently laid off from Microsoft after decades of service, wrote to me, this is “a new arrow in the quiver of bringing tech workers to heel and ensuring that we’re properly thankful for the jobs we have (had?).”

Dubal is interested in more than analysis, she’s interested in action. She looks at the tactics already deployed by gig workers, who have not taken all this abuse lying down. Workers in the UK and EU organized through Worker Info Exchange and the App Drivers and Couriers Union have used the GDPR (the EU’s privacy law) to demand “algorithmic transparency,” as well as access to their data. In California, drivers hope to use similar provisions in the CCPA (a state privacy law) to do the same.

These efforts have borne fruit. When Cornell economists, led by Louis Hyman, published research (paid for by Uber) claiming that Uber drivers earned an average of $23/hour, it was data from these efforts that revealed the true average Uber driver’s wage was $9.74. Subsequent research in California found that Uber drivers’ wage fell to $6.22/hour after the passage of Prop 22, a worker misclassification law that gig companies spent $225m to pass, only to have the law struck down because of a careless drafting error:

https://www.latimes.com/california/newsletter/2021-08-23/proposition-22-lyft-uber-decision-essential-california

But Dubal is skeptical that data-coops and transparency will achieve transformative change and build real worker power. Knowing how the algorithm works is useful, but it doesn’t mean you can do anything about it, not least because the platform owners can keep touching their knobs, twiddling the payout schedule on their rigged slot-machines.

Data co-ops start from the proposition that “data extraction is an inevitable form of labor for which workers should be remunerated.” It makes on-the-job surveillance acceptable, provided that workers are compensated for the spying. But co-ops aren’t unions, and they don’t have the power to bargain for a fair price for that data, and coops themselves lack the vast resources — “to store, clean, and understand” — data.

Co-ops are also badly situated to understand the true value of the data that is extracted from their members: “Workers cannot know whether the data collected will, at the population level, violate the civil rights of others or amplifies their own social oppression.”

Instead, Dubal wants an outright, nonwaivable prohibition on algorithmic wage discrimination. Just make it illegal. If firms cannot use gambling mechanisms to control worker behavior through variable pay systems, they will have to find ways to maintain flexible workforces while paying their workforce predictable wages under an employment model. If a firm cannot manage wages through digitally-determined variable pay systems, then the firm is less likely to employ algorithmic management.”

In other words, rather than using market mechanisms too constrain platform twiddling, Dubal just wants to make certain kinds of twiddling illegal. This is a growing trend in legal scholarship. For example, the economist Ramsi Woodcock has proposed a ban on surge pricing as a per se violation of Section 1 of the Sherman Act:

https://ilr.law.uiowa.edu/print/volume-105-issue-4/the-efficient-queue-and-the-case-against-dynamic-pricing

Similarly, Dubal proposes that algorithmic wage discrimination violates another antitrust law: the Robinson-Patman Act, which “bans sellers from charging competing buyers different prices for the same commodity. Robinson-Patman enforcement was effectively halted under Reagan, kicking off a host of pathologies, like the rise of Walmart:

https://pluralistic.net/2023/03/27/walmarts-jackals/#cheater-sizes

I really liked Dubal’s legal reasoning and argument, and to it I would add a call to reinvigorate countertwiddling: reforming laws that get in the way of workers who want to reverse-engineer, spoof, and control the apps that currently control them. Adversarial interoperability (AKA competitive compatibility or comcom) is key tool for building worker power in an era of digital Taylorism:

https://www.eff.org/deeplinks/2019/10/adversarial-interoperability

To see how that works, look to other jursidictions where workers have leapfrogged their European and American cousins, such as Indonesia, where gig workers and toolsmiths collaborate to make a whole suite of “tuyul apps,” which let them override the apps that gig companies expect them to use.

https://pluralistic.net/2021/07/08/tuyul-apps/#gojek

For example, ride-hailing companies won’t assign a train-station pickup to a driver unless they’re circling the station — which is incredibly dangerous during the congested moments after a train arrives. A tuyul app lets a driver park nearby and then spoof their phone’s GPS fix to the ridehailing company so that they appear to be right out front of the station.

In an ideal world, those workers would have a union, and be able to dictate the app’s functionality to their bosses. But workers shouldn’t have to wait for an ideal world: they don’t just need jam tomorrow — they need jam today. Tuyul apps, and apps like Para, which allow workers to extract more money under better working conditions, are a prelude to unionization and employer regulation, not a substitute for it.

Employers will not give workers one iota more power than they have to. Just look at the asymmetry between the regulation of union employees versus union busters. Under US law, employees of a union need to account for every single hour they work, every mile they drive, every location they visit, in public filings. Meanwhile, the union-busting industry — far larger and richer than unions — operate under a cloak of total secrecy, Workers aren’t even told which union busters their employers have hired — let alone get an accounting of how those union busters spend money, or how many of them are working undercover, pretending to be workers in order to sabotage the union.

Twiddling will only get an employer so far. Twiddling — like all “AI” — is based on analyzing the past to predict the future. The heuristics an algorithm creates to lure workers into their cars can’t account for rapid changes in the wider world, which is why companies who relied on “AI” scheduling apps (for example, to prevent their employees from logging enough hours to be entitled to benefits) were caught flatfooted by the Great Resignation.

Workers suddenly found themselves with bargaining power thanks to the departure of millions of workers — a mix of early retirees and workers who were killed or permanently disabled by covid — and they used that shortage to demand a larger share of the fruits of their labor. The outraged howls of the capital class at this development were telling: these companies are operated by the kinds of “capitalists” that MLK once identified, who want “socialism for the rich and rugged individualism for the poor.”

https://twitter.com/KaseyKlimes/status/821836823022354432/

There's only 5 days left in the Kickstarter campaign for the audiobook of my next novel, a post-cyberpunk anti-finance finance thriller about Silicon Valley scams called Red Team Blues. Amazon's Audible refuses to carry my audiobooks because they're DRM free, but crowdfunding makes them possible.

Image: Stephen Drake (modified) https://commons.wikimedia.org/wiki/File:Analog_Test_Array_modular_synth_by_sduck409.jpg

CC BY 2.0 https://creativecommons.org/licenses/by/2.0/deed.en

 — 

Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

 — 

Louis (modified) https://commons.wikimedia.org/wiki/File:Chestnut_horse_head,_all_excited.jpg

CC BY-SA 2.0 https://creativecommons.org/licenses/by-sa/2.0/deed.en

[Image ID: A complex mandala of knobs from a modular synth. In the foreground, limned in a blue electric halo, is a man in a hi-viz vest with the head of a horse. The horse's eyes have been replaced with the sinister red eyes of HAL9000 from Kubrick's '2001: A Space Odyssey.'"]

[companion-showdown]

Anniversary Tournament

Last year for Doctor Who's anniversary I ran a tournament between Doctor Who stories, and I wanted to so something different again this year. A tournament between real people important to the history of Doctor Who, actors, writers, producers, directors, composers, production designers. Technically it'll be a tournament for the most infuential person to Doctor Who and its development over the years, but really I want it to be a celebration of all of these people, and not just the winner.

To that end, the nomination form, you can also submit nominations normally, ie sending me an ask or replying to this post, however I won't be accepting propaganda through those methods.

I'm thinking I'll close nominations on the 18th of November, that might change but probably not by much

Current Nominations:

if green then at least one person has submitted propaganda for them

Actors

Arthur Darvil

Billie Piper

Carole Ann Ford

Christopher Eccleston

Colin Baker

David Graham and Peter Hawkins

David Tennant

Frazer Hines

Freema Agyeman

India Fisher

Jacqueline Hill

Jodie Whittaker

John Simm

Jon Pertwee

Lisa Bowerman

Liz Sladen

Matt Smith

Ncuti Gatwa

Nicholas Courtney

Pat Gorman

Patrick Troughton

Paul McGann

Peter Capaldi

Peter Davison

Rodger Delgado

Sean Carlsen

Sophie Aldred

Stuart Fell

Sylvester McCoy

Tom Baker

William Hartnell

William Russell

Composer

Delia Derbyshire

Dudley Simpson

Murray Gold

Paddy Kingsland

Peter Howell

Rob Harvey

Ron Grainer

Segun Akinola

The BBC Radiophonic Workshop

Designers

June Hudson

Peter Brachacki

Raymond Cusic

Directors

Christopher Barry

Graeme Harper

Paddy Russell

Rachel Talalay

Richard Martin

Waris Hussein

Fandom

Marnal Gate

TARDIS wiki creator

The Audience

Craig Ferguson

Producers

Barry Letts

Graham Williams

John Nathan Turner

Philip Hinchcliffe

Verity Lambert

Julie Gardner

Writers (including script editors and showrunners)

Alan Moore

Anthony Coburn

Chris Chibnall

David Whittaker

Donald Wilson

Douglas Adams

Eric Saward

Gerry Davis

Grant Morrison

John Lucarotti

Johnathan Blum

Justine Richards

Kate Orman

Kit Pedler

Lance Parkin

Lawrence Miles

Marc Platt

Paul Cornell

Robert Holmes

Robert Shearman

Rona Munro

Russell T Davies

Steven Moffatt

Terrance Dicks

Terry Nation

Other/impossible to categorise

all the thousands of people who've worked behind the scenes

Michael Grade (BBC higherup who hated doctor who so so much)

Peter Cregeen (actually cancelled Doctor Who)

Sydney Newman

Nicholas Briggs

Gary Russell

John F Kennedy

Sue from Catering

The real historical figures who've appeared in the show

Shakespeare

[jgroffdaily]

@ericalehman My (very belated) Christmas present to my niece was going to see #merrilywerollalong on Broadway. The play was BRILLIANT and with a little serendipity (me sort of yelling like a maniac), #jonathangroff saw my niece’s sign and was kind enough to take this picture. #auntoftheyear

[vorpalmuchness]

a web weave for Ruby Van Omerta

Incendies// Craig Santos Perez// Mitski, Francis Forever// Clementine Von Radics// Carrie Fisher, Princess Diarist// Lorde, Supercut// Lana Del Rey, Cinnamon Girl// Bilbo, Fellowship of the Ring// Sue Zhao// Hooyo Isn't Home, Warsan Shire// Ethel Cain, Sunbleached Files// Ocean Vuong// @wandalives

[uncharismatic-fauna]

Uncharismatic Fact of the Day

Identifying species can be an extremely difficult job for biologists-- especially when the animal in question has too few distinguishing features, or too many. Perhaps no species demonstrates this better than Littorina saxatilis, aka the rough periwinkle snail. Due to the extreme variations in shell shape, size, and color, this species has been misidentified by taxonomists 112 times! Even today, scientists are still in dispute over whether genetically distinct populations should be considered separate species.

(Image: Six rough periwinkle snails (Littorina saxatilis) by Sue Scott)

Want to request some art or uncharismatic facts? Just send me proof of donation of any amount to any of the fundraisers on this list, or a Palestinian organization of your choice!

Bonus: check out the list of L. saxatilis' former names below the cut!

Litorina groenlandica Menke, 1830

Litorina incarnata Philippi, 1846

Litorina marmorata L. Pfeiffer, 1839

Litorina sulcata Menke, 1830

Littorina castanea Deshayes in Deshayes & Milne Edwards, 1843

Littorina danieli Locard, 1886

Littorina groenlandica (Menke, 1830)

Littorina neglecta Bean, 1844

Littorina nervillei Dautzenberg, 1893

Littorina nervillei var. major Pallary in Seurat, 1924

Littorina nigrolineata Gray, 1839

Littorina palliata var. turritella Schlesch, 1916

Littorina rudis (Maton, 1797) (synonym)

Littorina rudis f. elatior Middendorff, 1849

Littorina rudis var. albida Dautzenberg, 1887

Littorina rudis var. alticola Dacie, 1917

Littorina rudis var. aurantia Dautzenberg, 1887

Littorina rudis var. brevis Dautzenberg, 1887

Littorina rudis var. conoidea Schlesch, 1916

Littorina rudis var. fasciata Dautzenberg, 1887

Littorina rudis var. finmarchia Herzenstein, 1885

Littorina rudis var. globosa Jeffreys, 1865

Littorina rudis var. globosa Martel, 1901

Littorina rudis var. laevis Jeffreys, 1865

Littorina rudis var. major Dautzenberg & P. Fisher, 1912

Littorina rudis var. rubescens Monterosato, 1878

Littorina rudis var. scotia S.M. Smith, 1979

Littorina rudis var. similis Jeffreys, 1865

Littorina rudis var. sulcata Martel, 1901

Littorina rudis var. tenebrosapallida L.E. Adams, 1896

Littorina rudis var. tessellata Dautzenberg, 1893

Littorina saxatile La Roque, 1953

Littorina saxatile saxatile La Roque, 1953

Littorina saxatilis Johnston, 1842

Littorina saxatilis f. abbreviata Dautzenberg & P. Fisher, 1912

Littorina saxatilis f. conoidea Dautzenberg & P. Fisher, 1912

Littorina saxatilis f. elongata Dautzenberg & P. Fisher, 1912

Littorina saxatilis f. minor Dautzenberg & P. Fisher, 1912

Littorina saxatilis groenlandica (Menke, 1830)

Littorina saxatilis groenlandica var. sculpta Schlesch, 1931

Littorina saxatilis jugosa Montagu, 1803

Littorina saxatilis jugosa var. bynei Dautzenberg & P. Fisher, 1912

Littorina saxatilis jugosa var. tenuis James, 1968

Littorina saxatilis nigrolineata Gray, 1839

Littorina saxatilis rudis (Maton, 1797)

Littorina saxatilis rudis var. rudissimoides James, 1968

Littorina saxatilis scotia Graham, 1988

Littorina saxatilis tenebrosa (Montagu, 1803)

Littorina saxatilis tenebrosa var. biinterrupta Fischer-Piette & Gaillard, 1963

Littorina saxatilis tenebrosa var. bizonaria James, 1963

Littorina saxatilis tenebrosa var. elata Dautzenberg & P. Fisher, 1912

Littorina saxatilis tenebrosa var. maculata Fischer-Piette & Gaillard, 1963

Littorina saxatilis var. clarilineata Fischer-Piette & Gaillard, 1971

Littorina saxatilis var. flammulata Dautzenberg & P. Fisher, 1912

Littorina saxatilis var. fulva Dautzenberg & P. Fisher, 1912

Littorina saxatilis var. fusca Dautzenberg & P. Fisher, 1912

Littorina saxatilis var. gascae Fischer-Piette & Gaillard, 1971

Littorina saxatilis var. groenlandica (Menke, 1830)

Littorina saxatilis var. hieroglyphica Fischer-Piette, Gaillard & Jouin, 1961

Littorina saxatilis var. interrupta Fischer-Piette, Gaillard & Jouin, 1961

Littorina saxatilis var. lagunae Barnes, 1993

Littorina saxatilis var. lineata Dautzenberg & P. Fisher, 1912

Littorina saxatilis var. lugubris Dautzenberg & P. Fisher, 1912

Littorina saxatilis var. nigra Fischer-Piette & Gaillard, 1971

Littorina saxatilis var. nojensis Fischer-Piette & Gaillard, 1964

Littorina saxatilis var. rubra Fischer-Piette & Gaillard, 1971

Littorina saxatilis var. rubrolineata Fischer-Piette, Gaillard & Delmas, 1967

Littorina saxatilis var. salvati Fischer-Piette, Gaillard & Delmas, 1967

Littorina saxatilis var. sanguinea Coen, 1933

Littorina saxatilis var. sellensis Fischer-Piette & Gaillard, 1964

Littorina saxatilis var. tractibus Fischer-Piette, Gaillard & Jouin, 1961

Littorina saxatilis var. trifasciata Dautzenberg & P. Fisher, 1912

Littorina saxatilis zonata Daniel, 1883

Littorina saxoides Nardo, 1847

Littorina simplex Reeve, 1857

Littorina tenebrosa (Montagu, 1803)

Littorina tenebrosa f. elatior Middendorff, 1849

Littorina tenebrosa var. costulata Middendorff, 1849

Littorina tenebrosa var. densecostulata Middendorff, 1849

Littorina tenebrosa var. grisolacteus Middendorff, 1849

Littorina tenebrosa var. intermedia Forbes & Hanley, 1850

Littorina tenebrosa var. rubidus Middendorff, 1849

Littorina tenebrosa var. tessellatus Middendorff, 1849

Littorina tenebrosa var. zonatus Middendorff, 1849

Littorina zonaria Bean, 1844

Nerita rustica Nardo, 1847

Turbo obligatus Say, 1822

Turbo rudis Maton, 1797

Turbo rudissimus Johnston, 1842

[rinandsketches]

Still on the train of thought about Blue Eye Samurai. I been seeing people really diss Taigen so...Let's talk about him.

I'm going into a dive into his character cause people only see a bully that might have a toxic relationship to Mizu. I'm going to dive in from start to finish and give my theories and takes on this fisher man's son to where he is know.

Beginning in episode 1-

So..I'm pretty sure everyone's first reaction was like mine. We wanted this guy to be knocked down a peg. Meeting him as that one kid bully who was going to take things to far with a rock. In the adult years he has worked hard and managed to get not only high honors but the love of a princess.

I kinda ship Mizu and Taigen (sue me) but this one episode is where people draw their conclusions to judge off Taigen as mostly irredeemable. He's proud, cocky, a brat, and he openly cheats on Akemi with some girls while celebrating his engagement, he was arrogant, proud of it and had every right to be, this is proof by the size of top not. its bigger then the rest of the students, literally showing his importance as the top samurai in the dojo. Placing my cards on the table here, if Mizu had not shown up, Taigen would have just become like Akemi's father. Its a small hint by the father stating that he also started small and worked hard like Taigen, seeing himself in Taigen.

What saved him was Mizu.

The duel happened and his chonmage was cut off by Mizu. She stripped everything from Taigen. Yet he is a prideful guy, he goes out to try and get back what his. I think the spot where his hair was cut is a way to show he is now ,not only a member of the outcast as a disgraced warrior, but he was ready to regrow again.

during his adventure with Mizu, fighting with her (alongside and against her), his wants begins to change. I don't know how many people noticed this but Taigen's hair does grow back by the last two episodes which is in the span of a few days or Possible a week. It could signal the new change in Taigen, he's softer to Mizu, less arrogant, and despite his feelings towards the fact Akemi is married he still saves her husband. Now he did get mad at Mizu and its kind of understandable, they have been at the forge for a week and she didn't say anything about Akemi and Fowler's plan until much later. Depsite that he fights with her against fowler.

This leads to the final scene with Taigen,

After everything single God damn thing he been through, he's reached this point. As Mizu said, he's not good but he can be great. She was not referring to his combat skills, she was talking about his character. Taigen also comes to figure this out, he doesn't need to be good with a blade to be great nor does he want to. If this had been episode 1 Taigen, I believe he would have thrown a fit if Akemi told him she wanted not be with him instead he must have took her back to her husband before leaving.

To sum up: yes, Taigen was a jackass, and an arrogant one to boot. I believe he was looking for a way to be happy with the options he had. Clearly it wasn't easy for him growing up, as Mizu probably thinks. Speaking of Mizu, the two need to have a conversation. Taigen definitely has regrets about not making her life easy, but Mizu also needs to begin a forgiving process. Its safe to say Mizu has a hard time letting things go..so it might take a while before the two can let their past go and continue to grow as people, and possible companions.

[allthecanadianpolitics]

Fisher River Cree Nation wants class-action status for its lawsuit against the federal government, which alleges the $5 annuities paid to Treaty 5 First Nations over the last 148 years violate the agreement because they don't keep up with inflation. The First Nation wants to represent all Treaty 5 nations and their members who opt in to the class action. Stefan Lorne Cochrane, a former chief and band councillor of Fisher River, would be the lead plaintiff, according to the statement of claim filed at the Manitoba Court of King's Bench on Dec. 12. In the suit, Fisher River claims the Crown breached its obligations under Treaty 5 by failing to regularly increase the $5 annuities to maintain their value at the time of the document's 1875 signing.

Continue Reading

Tagging @politicsofcanada

[nightwhispcrs]

✧･ﾟ: ✧･ﾟ — here's my post-hiatus/new season starter call for my muses that could use more threads! at least some of these will have a fall/autumn theme and for my sanity many of them will probably be set at my muses' place of work.

adam newman, 33, senator & coffee shop owner — ( 1/3 ) drusilla

arnold novak, 28, socially awkward landscaper — ( 1/3 ) helaena targaryen

craig manning, 23, musician & photographer — ( 2/3 ) emily junk, nettles

gael martinez, 29, artist — (2/2 ) nie huaisang, kauul hilo

irina denali, 28, vampire esthetician law school student — ( 2/3 ) nettles, lucy westenra

dr. jack shephard, 35, spinal surgeon — ( 2/3 ) carlisle, pildo

jim hopper, 45, private investigator — ( 2/3 ) jihyo, joel miller

lenny pierce, appears 25, twilight oc hybrid — ( 1/2 ) astrid hofferson

michael guerin, appears 31, space alien cowboy — ( 2/3 ) jake wheeler, martin blackwood

monica geller — ( 1/1 ) dain aetos

naomi pierce, 34, luxuy smuggler socialite — ( 1/2 ) kenna

ramona flowers, 25, vintage store manager — ( 2/3 ) helaena targaryen, evie grimhilde

dr. reid oliver, 37, asshole neurosurgeon — ( 0/3 )

roman roy, 36, bar owner — ( 0/2 )

sarah walker, 29, cia agent — ( 3/3 ) mia winters, dale cooper, will graham

sue storm, 31, meterologist — (2/3 ) kate carter, yoon jisoo

violet baudelaire, 24, mechanical engineer — ( 1/3 ) archie kennedy

zoe rivas, 24, actress & wine bar host — ( 2/2 ) gina porter, jeremiah fisher