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[wagnis-trip]

Air Fare Ticket Price

No matter how challenging Kedarnath's goal is, lovers are drawn to the location by Lord Shiva's heavenly grace because of the place's profound tornado and allure. For Hindu devotees, it is regarded as one of the Chota Char Dhams and a well-known travel hindrance. Situated at an elevation of 3583 meters, the lovely environment is further enhanced by the mesmerizing Mandakini holy stream. The challenging Kedarnath Mandir Pilgrimage Tour is usually welcomed by devotees during the extended months of May through June and September through October. Winter blankets the entire area in snow, making it challenging for lovers to reach each other. For this reason, people organize the Kedarnath Yatra 2022 ahead of time.

Nevertheless, when planning the Kedarnath Yatra, the first thing that comes to mind is the practical option. You cannot ignore how important it is to reserve suitable accommodations in an area where the environment is really harsh. Among the three Char Dham sanctuaries, it is also the most remote area.

Its popularity as a travel destination also means that you can't ignore the rush and organize the entire trip on your own. Because of this, it is imperative that you plan your visit well in advance because it's possible that the space will be fully reserved. Reserve your vacation packages.

To protect yourself from the latest potential inconvenience The top ten places to stay in Kedarnath for 2022 are listed below. The best time to visit is in the summer, and Kedarnath Dham's entrance will open on May 6, 2022. We think you should plan your Kedarnath trip with Air Fare Ticket Price expertly and without any pressure at all. Planning beforehand for the Kedarnath Tour's convenience will result in a substantial financial savings.

[wagnistrip123]

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[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

 — 

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

 — 

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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.'"]

[thealogie]

do you or any peanuts have any recommendations on finding cheap flights to london from the US?? and/or affordable accommodations in london?? i live in a large city with an international airport which helps, but i’ve never planned international travel before and macbeth is haunting me

I would recommend you start looking on Kayak now. In terms of a flights, if your airport has Norse Airlines or another one of those speciality cheap airlines, I’d recommend that. For example, I can do a round trip from Los Angeles to London for as low as $200. It’s not the best most comfortable but it’s safe and fine. If you want something a little better I would say (1) If you have a credit card see if you can use some points (this is how I flew to London for 0 dollars) or see if they have a booking system which sometimes offers discounts or (2) keep looking on kayak and other travel sites!

For accommodations, I have stayed at some nice hostels in London and honestly had fun meeting and going out with people from the hostel! Alas this was years ago and my hostel days are behind me but I’d recommend looking around for ones that are trying to be slightly trendy or boutique. You can definitely find a private room in a hostel for £60 a night.

If you’re looking for something nicer than a hostel, this is a good list of semi-affordable hotels. Two neighborhoods I’ve stayed in that were fun but cost effective: Shoreditch and Paddington

[marygusmans]

Get Deals on Flights, Hotels, and Tours | Lloydtravels.com https://lloydtravels.com/ Lloydtravels.com is a travel booking site that compares millions of cheap flights, hotels, rental cars, airport taxis, and many other useful tools. Visit us now!

[bookviaus]

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[flighthotelgo]

Flight Hotel Go is a comprehensive travel service platform designed to streamline the booking process for flights and hotels. Whether you're planning a vacation, business trip, or a quick weekend getaway, Flight Hotel Go offers seamless options to book both your flight and accommodation in one go. The platform provides users with a vast selection of airlines and hotel chains worldwide, ensuring competitive pricing, real-time availability, and tailored recommendations based on personal preferences.

[stardust-swan]

How to Fly Like a Hollywood Star - Part 2: Before the Airport and At the Airport

[Part 1 - Packing]

Before the Airport

🛩 If booking flight tickets online, use incognito mode. Airline websites use cookies to adjust the prices of tickets, so if you visit a website often, the price will be more expensive. Using incognito mode prevents this.

🛩 You can't book tickets through this site, but it tells you who has the cheapest fares.

🛩 Flight Connections can be your best friend when booking flights.

🛩 Be careful with low budget airlines. The tickets may be cheap, but they try and make you pay through the nose for every else, like food, checked bags, seat assignments, etc.

🛩 First flights of the day are always your best bets in terms of availability and options if you get bumped, at least on major routes. If you have two options to take a leg always plan to take the first one I.e. Ten seats on the 7am departure is far more likely than ten seats on the 9am. People oversleep, people change their flights, people get stuck in traffic, etc.

🛩 Study what type of plane you'll be on prior to booking seats. Business class will nearly always have only two seats per row, but on some big jets, economy class will have two seats towards the back of the plane. This is because the plane narrows there. This is good, because there's extra space next to you on the floor if you're in the window seat, and you won't be in the dreaded middle seat. Be aware that some planes have the latrine next to that aisle (but sometimes it's the galley, so you'll have the aroma of fresh coffee near you throughout the entire flight). You can find a map of your flight's seats here.

🛩 Get window or aisle seats if you can. Aisle seats are better if you need to pee a lot, but the downside is that you'll have to get up for other people in your row. Window seats are good for not being disturbed, but you'll have to ask people in your row to move if you need the toilet. Avoid middle seats if possible, there's no benefit to them.

🛩 Get business class tickets if you can. On some airlines they're only a little bit more expensive than economy, and the experience is so much better.

🛩 Sometimes, saying you're a doctor can get you upgraded ahead of others. So try your luck and fill out the "Title" section with "Dr" when you fly.

🛩 Bring a powerbank for your phone, just in case your phone battery dies. The flight may not have a charging outlet, and they can be difficult to find in an airport, which is a nightmare if you have your boarding pass or vaccination proof on your phone.

🛩 Take a screenshot of the airport map, your boarding pass, and vaccine cert just in case you have difficulties accessing the airport WiFi. Make a photocopy of your passport and keep it in your luggage.

🛩 Download some music ahead of your flight (this app is the best for downloading music if you're an android user), and bring something to read on board. Use Library Genesis to download any books you want to read on an electronic device offline.

🛩 Take a picture of your luggage in case it gets lost.

🛩 If your luggage gets lost, in many places airlines are obligated to pay you compensation, so don't just let it slide. Use this site to get compensation (going directly to the airline may cause them to do the runaround so you won't get anything). Keep the receipts of clothing, toiletries, etc, you bought and claim. If you're don't fly often, buy stuff with the assumption you won't get your claim. If you do fly frequently, then you can begin buying expensive items, and they don't complain.

🛩 If you're in the EU and something goes wrong with your flight, check this website to find out your rights.

🛩 Check your phone coverage abroad. Most big carriers have programs where you can pay by the day for international access (between like $2 and $10 depending on country) but international roaming fees are terrible if you forget to activate an international plan. Get a prepaid cellphone sim card if possible.

🛩 Make sure you call your bank/credit card company to authorize your cards for use abroad. Check what the international transaction fees are. Consider getting some cash in the currency of your destination before you go. Major banks will have it on hand, most others can order it for you.

At the Airport

🛩 Dress smartly, for example, a neat pair of jeans, white shirt, and well-cut blazer or cardigan. Don't dress like you're at the beach, in shorts and sandals. The air conditioning is often cranked up at airports and planes are usually cold because of the air vents, so you'll be chilly, and it's impractical if there's an emergency and you need to evacuate. Instead, wear layers. Not too many, as it's a pain taking them off when going through security, but it's good to wear a warm cardigan just in case you're freezing, which you can take off if the heating in the airport is too high (London Heathrow is always boiling hot in my experience). Avoid gym gear; it belongs in the gym (this applies to all situations, not just flying). If you're wearing sneakers, wear trim ones, not clunky running shoes. If you're lucky, dressing smartly might bump you up a class, and you'll never know when you might meet a person in a high position at the airport, or sat next to you in business class.

🛩 Go to the airport as early as you can. Sometimes, checking in very early can get you bumped up to spare seats in a higher class.

🛩 Once you go through security, you can't get out again (unless you want to go through security a second time). Don't leave the secure area (usually, if you're going in the direction of baggage claim, you're headed out).

🛩 If you get lost in the airport, don't hesitate to ask the staff for help.

🛩 If the airport is huge, you can generally use Google Maps on your phone if you don't know where to go.

🛩 Don't trust anyone who offers to carry your bags.

🛩 Be aware of your important belongings in the airport. They’re generally safe, but if your brain is in a million places at once it’s easy to misplace little impossible things (phone, wallet, passport, ticket, etc.).

🛩 When transferring flights, go to your next flight immediately. It may take you longer to get there than you expect.

🛩 If you miss your connecting flight, the airline will rebook you. There will be a line to wait in or a number to call for details if this happens.

🛩 Listen to the overhead announcements, as airlines might not always text if there's a change to your flight or a gate change.

🛩 If you have a long wait in the airport, get up and walk around every few hours. Or explore the city you're in if you feel comfortable.

🛩 Some airports have yoga rooms, art exhibits, etc. Make use of them if you have time.

🛩 Food is more expensive in airports, so if you're on a budget, try to eat before you go, or bring snacks. However, buying snacks in the airport is still less expensive than on the plane. On many airlines, if you fly business class, snacks and drinks are complimentary, so check ahead of time on the airline's meal policy.

🛩 If you have access to the lounge, you'll be able to shower, which can be very refreshing during a long day of running around.

[bookbookflightflight]

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[towardsway]

Section 1: Planning Your Budget Vacation

1.1 Setting a Budget

Establish a clear budget for your trip, factoring in transportation, lodging, meals, and activities. Use budgeting tools or apps to keep track of expenses and prioritize your spending.

1.2 Researching Destinations

Some destinations offer more value than others. Research places known for their affordability, such as Southeast Asia or Eastern Europe, and consider traveling during the off-peak season to save on costs.

1.3 Travel Tips

Utilize travel apps and websites to compare prices. Set alerts for flight deals and be flexible with your travel dates to take advantage of the best rates.

Section 2: Finding Affordable Accommodation

2.1 Types of Budget Accommodation

Explore a variety of budget options including hostels, motels, and guesthouses. Look into vacation rentals that can offer more space and amenities for families or groups.

2.2 Best Platforms for Booking

Platforms like Booking.com, Hostelworld, and Airbnb provide a range of options. Learn to navigate these sites effectively by using filters and sorting features to find the best deals.

2.3 Unique Stays on a Budget

Consider unique lodging options such as glamping sites, houseboats, or tiny homes. These can provide memorable experiences without a hefty price tag.

Section 3: Affordable Vacation Packages

3.1 Understanding Vacation Packages

Vacation packages often combine flights, hotels, and sometimes activities at a lower cost. Understand how these packages work to maximize your savings.

3.2 Where to Find Deals

Research travel agencies that specialize in budget trips, and don’t forget to check out last-minute deals on various travel websites.

3.3 Tips for Creating Your Own Package

Learn how to bundle flights and accommodations effectively. Use examples to demonstrate how to save by planning your own itineraries.

Section 4: Activities and Attractions on a Budget

4.1 Free and Low-Cost Activities

Highlight free activities available at your destination, such as hiking, city walking tours, and local markets.

4.2 Discounts and Passes

Promote the idea of city passes that offer discounts on attractions and public transport. Share tips on how to take advantage of student and senior discounts.

4.3 Making the Most of Your Destination

Encourage travelers to explore local cuisine through affordable street food options. Highlight the importance of connecting with locals for insider tips on budget-friendly activities.

Section 5: Travel Hacks for Saving Money

5.1 Transportation Tips

Provide tips for finding cheap flights, such as using budget airlines or flying during off-peak hours. Explain how to navigate public transportation in new cities.

5.2 Packing Smart

Offer advice on packing light to avoid baggage fees and the importance of bringing essential items like reusable water bottles and snacks.

5.3 Money-Saving Apps

List apps that help travelers save money, such as Skyscanner for flights, HotelTonight for last-minute hotel deals, and GasBuddy for road trips.

Section 6: Real-Life Success Stories

6.1 Case Studies of Affordable Trips

Share inspiring stories from travelers who managed to explore new destinations on a budget. Include their favorite tips and tricks.

go for more @towardsway.in

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[moonlightpirate]

Before I go to Facebook and ask there but I need to start thinking about booking my flight for my Mexico trip. I haven't booked a flight in years 😅 so I guess which sites are the better ones? I want to find a cheap flight but from a reliable site if that makes sense especially since it is close to the holidays and my car is currently getting a ton of money worth of repairs 😅