#constraints

[mostlysignssomeportents]

The specific process by which Google enshittified its search

I'm touring my new, nationally bestselling novel The Bezzle! Catch me SATURDAY (Apr 27) in MARIN COUNTY, then Winnipeg (May 2), Calgary (May 3), Vancouver (May 4), and beyond!

All digital businesses have the technical capacity to enshittify: the ability to change the underlying functions of the business from moment to moment and user to user, allowing for the rapid transfer of value between business customers, end users and shareholders:

https://pluralistic.net/2023/02/19/twiddler/

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

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

Which raises an important question: why do companies enshittify at a specific moment, after refraining from enshittifying before? After all, a company always has the potential to benefit by treating its business customers and end users worse, by giving them a worse deal. If you charge more for your product and pay your suppliers less, that leaves more money on the table for your investors.

Of course, it's not that simple. While cheating, price-gouging, and degrading your product can produce gains, these tactics also threaten losses. You might lose customers to a rival, or get punished by a regulator, or face mass resignations from your employees who really believe in your product.

Companies choose not to enshittify their products…until they choose to do so. One theory to explain this is that companies are engaged in a process of continuous assessment, gathering data about their competitive risks, their regulators' mettle, their employees' boldness. When these assessments indicate that the conditions are favorable to enshittification, the CEO walks over to the big "enshittification" lever on the wall and yanks it all the way to MAX.

Some companies have certainly done this – and paid the price. Think of Myspace or Yahoo: companies that made themselves worse by reducing quality and gouging on price (be it measured in dollars or attention – that is, ads) before sinking into obscure senescence. These companies made a bet that they could get richer while getting worse, and they were wrong, and they lost out.

But this model doesn't explain the Great Enshittening, in which all the tech companies are enshittifying at the same time. Maybe all these companies are subscribing to the same business newsletter (or, more likely, buying advice from the same management consultancy) (cough McKinsey cough) that is a kind of industry-wide starter pistol for enshittification.

I think it's something else. I think the main job of a CEO is to show up for work every morning and yank on the enshittification lever as hard as you can, in hopes that you can eke out some incremental gains in your company's cost-basis and/or income by shifting value away from your suppliers and customers to yourself.

We get good digital services when the enshittification lever doesn't budge – when it is constrained: by competition, by regulation, by interoperable mods and hacks that undo enshittification (like alternative clients and ad-blockers) and by workers who have bargaining power thanks to a tight labor market or a powerful union:

https://pluralistic.net/2023/11/09/lead-me-not-into-temptation/#chamberlain

When Google ordered its staff to build a secret Chinese search engine that would censor search results and rat out dissidents to the Chinese secret police, googlers revolted and refused, and the project died:

https://en.wikipedia.org/wiki/Dragonfly_(search_engine)

When Google tried to win a US government contract to build AI for drones used to target and murder civilians far from the battlefield, googlers revolted and refused, and the project died:

https://www.nytimes.com/2018/06/01/technology/google-pentagon-project-maven.html

What's happened since – what's behind all the tech companies enshittifying all at once – is that tech worker power has been smashed, especially at Google, where 12,000 workers were fired just months after a $80b stock buyback that would have paid their wages for the next 27 years. Likewise, competition has receded from tech bosses' worries, thanks to lax antitrust enforcement that saw most credible competitors merged into behemoths, or neutralized with predatory pricing schemes. Lax enforcement of other policies – privacy, labor and consumer protection – loosened up the enshittification lever even more. And the expansion of IP rights, which criminalize most kinds of reverse engineering and aftermarket modification, means that interoperability no longer applies friction to the enshittification lever.

Now that every tech boss has an enshittification lever that moves very freely, they can show up for work, yank the enshittification lever, and it goes all the way to MAX. When googlers protested the company's complicity in the genocide in Gaza, Google didn't kill the project – it mass-fired the workers:

https://medium.com/@notechforapartheid/statement-from-google-workers-with-the-no-tech-for-apartheid-campaign-on-googles-indiscriminate-28ba4c9b7ce8

Enshittification is a macroeconomic phenomenon, determined by the regulatory environment for competition, privacy, labor, consumer protection and IP. But enshittification is also a microeconomic phenomenon, the result of innumerable boardroom and product-planning fights within companies in which would-be enshittifiers try to do things that make the company's products and services shittier wrestle with rivals who want to keep things as they are, or make them better, whether out of principle or fear of the consequences.

Those microeconomic wrestling-matches are where we find enshittification's heroes and villains – the people who fight for the user or stand up for a fair deal, versus the people who want to cheat and wreck to make things better for the company and win bonuses and promotions for themselves:

https://locusmag.com/2023/11/commentary-by-cory-doctorow-dont-be-evil/

These microeconomic struggles are usually obscure, because companies are secretive institutions and our glimpses into their deliberations are normally limited to the odd leaked memo, whistleblower tell-all, or spectacular worker revolt. But when a company gets dragged into court, a new window opens into the company's internal operations. That's especially true when the plaintiff is the US government.

Which brings me back to Google, the poster-child for enshittification, a company that revolutionized the internet a quarter of a century ago with a search-engine that was so good that it felt like magic, which has decayed so badly and so rapidly that whole sections of the internet are disappearing from view for the 90% of users who rely on the search engine as their gateway to the internet.

Google is being sued by the DOJ's Antitrust Division, and that means we are getting a very deep look into the company, as its internal emails and memos come to light:

https://pluralistic.net/2023/10/03/not-feeling-lucky/#fundamental-laws-of-economics

Google is a tech company, and tech companies have literary cultures – they run on email and other forms of written communication, even for casual speech, which is more likely to take place in a chat program than at a water-cooler. This means that tech companies have giant databases full of confessions to every crime they've ever committed:

https://pluralistic.net/2023/09/03/big-tech-cant-stop-telling-on-itself/

Large pieces of Google's database-of-crimes are now on display – so much, in fact, that it's hard for anyone to parse through it all and understand what it means. But some people are trying, and coming up with gold. One of those successful prospectors is Ed Zitron, who has produced a staggering account of the precise moment at which Google search tipped over into enshittification, which names the executives at the very heart of the rot:

https://www.wheresyoured.at/the-men-who-killed-google/

Zitron tells the story of a boardroom struggle over search quality, in which Ben Gomes – a long-tenured googler who helped define the company during its best years – lost a fight with Prabhakar Raghavan, a computer scientist turned manager whose tactic for increasing the number of search queries (and thus the number of ads the company could show to searchers) was to decrease the quality of search. That way, searchers would have to spend more time on Google before they found what they were looking for.

Zitron contrasts the background of these two figures. Gomes, the hero, worked at Google for 19 years, solving fantastically hard technical scaling problems and eventually becoming the company's "search czar." Raghavan, the villain, "failed upwards" through his career, including a stint as Yahoo's head of search from 2005-12, a presiding over the collapse of Yahoo's search business. Under Raghavan's leadership, Yahoo's search market-share fell from 30.4% to 14%, and in the end, Yahoo jettisoned its search altogether and replaced it with Bing.

For Zitron, the memos show how Raghavan engineered the ouster of Gomes, with help from the company CEO, the ex-McKinseyite Sundar Pichai. It was a triumph for enshittification, a deliberate decision to make the product worse in order to make it more profitable, under the (correct) belief that the company's exclusivity deals to provide search everywhere from Iphones and Samsungs to Mozilla would mean that the business would face no consequences for doing so.

It a picture of a company that isn't just too big to fail – it's (as FTC Chair Lina Khan put it on The Daily Show) too big to care:

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

Zitron's done excellent sleuthing through the court exhibits here, and his writeup is incandescently brilliant. But there's one point I quibble with him on. Zitron writes that "It’s because the people running the tech industry are no longer those that built it."

I think that gets it backwards. I think that there were always enshittifiers in the C-suites of these companies. When Page and Brin brought in the war criminal Eric Schmidt to run the company, he surely started every day with a ritual, ferocious tug at that enshittification lever. The difference wasn't who was in the C-suite – the difference was how freely the lever moved.

On Saturday, I wrote:

The platforms used to treat us well and now treat us badly. That's not because they were setting a patient trap, luring us in with good treatment in the expectation of locking us in and turning on us. Tech bosses do not have the executive function to lie in wait for years and years.

https://pluralistic.net/2024/04/22/kargo-kult-kaptialism/#dont-buy-it

Someone on Hacker News called that "silly," adding that "tech bosses do in fact have the executive function to lie in wait for years and years. That's literally the business model of most startups":

https://news.ycombinator.com/item?id=40114339

That's not quite right, though. The business-model of the startup is to yank on the enshittification lever every day. Tech bosses don't lie in wait for the perfect moment to claw away all the value from their employees, users, business customers, and suppliers – they're always trying to get that value. It's only when they become too big to care that they succeed. That's the definition of being too big to care.

In antitrust circles, they sometimes say that "the process is the punishment." No matter what happens to the DOJ's case against Google, its internal workers have been made visible to the public. The secrecy surrounding the Google trial when it was underway meant that a lot of this stuff flew under the radar when it first appeared. But as Zitron's work shows, there is plenty of treasure to be found in that trove of documents that is now permanently in the public domain.

When future scholars study the enshittocene, they will look to accounts like Zitron's to mark the turning points from the old, good internet to the enshitternet. Let's hope those future scholars have a new, good internet on which to publish their findings.

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

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

[blackswaneuroparedux]

The writer must impose constraints. A painter who uses a canvas rather than a wall; a composer who opts for a given key - all establish a system of constraints. So do avant-garde artists, who try to avoid constraints - they simply construct others, unnoticed.

- Umberto Eco

[tenth-sentence]

Then – constrained by a will more powerful than his own – Cyan's gaze was wrenched away, coming to rest in resentment and anger upon the black-robed mage.

"DragonLance Chronicles: Dragons of Spring Dawning" - Margaret Weis and Tracy Hickman

[nightshadesmusings]

Missing Common (Important) Things

What if, at a point, you found That you lack a critical thing? What if you didn’t know That said thing is missing?

What if you didn’t know it was around? You had many doo-dads and it was working Folks call you unusual as you lack a particular gizmo And you unknowingly go along, ignoring loud hissing.

You accepted the pain and assumed this was life You thought you were broken; you’re just something else Like this poem, you’re better when you use all the letters, No matter who tells you to never use your “e.”

Constrained writing: Cannot use the letter “e” until the last verse

[elizabethminkel]

My lates piece for WIRED is live! On platform affordances and constraints, and the (different) things we need from the next phase of the web. (And featuring one of the things I find most interesting about the creation of Tumblr: David Karp's line about his fear of the "big empty text box.")

[tristealven]

We love constraint; I think that’s just an aspect of the human animal. We love rules, because then you can operate with infinite variation within them. The blank page can be really daunting and overwhelming, but given one or two good details, you can do whatever you want.

Carmen Maria Machado in “Tommy Pico and Carmen Maria Machado investigate horror as a reflection of the American psyche” by Camille Sojit Pejcha. Document Journal, January 10, 2023.     

[poligraf]

Form is not a mere lopping off of meaning that you don't have room to put into your poem; it is an aid to finding new meaning, a stimulus to condensing your meaning, to simplifying and purifying it, and to discovering on a more universal dimension the essence you wish to express.

— Rollo May

[howifeltabouthim]

She was ready to say that it was as hard on her as on him, and that she was helpless; but those strange particulars of their relation which neither of them could explicitly mention kept her always in dread of saying too much.

George Eliot, from Middlemarch

[atissi]

locked the fuck back in

[whats-in-a-sentence]

Right now, right next to you, right next to me, and right next to everyone else, there could be another spatial dimension – a dimension beyond left/right, back/forth, and up/down, a dimension that's curled up but still large enough to swallow something as thick as this page – that remains beyond our grasp.*

* There is even a proposal, from Lisa Randall, of Harvard, and Raman Sundrum, of Johns Hopkins, in which gravity can be trapped, not by a sticky brane, but by extra dimensions that curve in just the right way, relaxing even further the constraints on their size.

"The Fabric of the Cosmos" - Brian Greene

[prabhatdavian-blog]

Step by step guide on how to identify, tackle and reduce constraints affecting your processes

Since the launch of ChatGPT at the end of 2022, I have witnessed a tidal wave of companies clamoring to integrate artificial intelligence (AI) technology into their product suites. Many of these companies still have legacy systems in place across the business, so bolting an AI solution onto existing technologies is not wholly effective. What these companies need is a digital transformation.

A full-scale digital transformation is viewed by many executives as a risky and costly undertaking, requiring an upheaval of business processes, operations, and even revenue strategy. Poor or incomplete execution can cause vast amounts of damage without providing the promised return on investment. Implementing a bad infrastructure, choosing buggy software, or failing to provide adequate training can impact operations and lead to an unhappy workforce.

But the risks associated with not embarking on a digital transformation are worse, as illustrated by companies such as Myspace, BlackBerry, and Toys R Us: gradual stagnation, loss of market share, and even bankruptcy. Being unprepared to integrate emerging technologies also limits the access employees have to modern tools and platforms, harming engagement, skill development, productivity, and the ability to attract and retain talent.

Introduction to the Theory of Constraints (ToC)

In today’s fast-paced business environment, every company is constantly seeking methods to improve efficiency and productivity. One such methodology that has proven highly effective is the Theory of Constraints (ToC). But what exactly is ToC, and why is it so in demand?

The Theory of Constraints is a management philosophy aimed at identifying the most significant limiting factor (or constraint) in a process, which is preventing a company from achieving its goals. By addressing this bottleneck, businesses can dramatically improve performance and profitability.

History and Origins of the Theory of Constraints

The Theory of Constraints was introduced by Dr. Eliyahu M. Goldratt, an Israeli business management guru, in his 1984 book titled The Goal. Since then, ToC has gained global recognition as an essential tool in both manufacturing and service sectors. Goldratt’s contributions have reshaped how organizations approach their problem-solving efforts.

Understanding the Core Principles of ToC

The underlying philosophy of ToC is simple: "A chain is only as strong as its weakest link." This concept highlights the importance of finding and eliminating constraints to enhance overall system performance. The main ideas that drive the success of ToC are:

Every system has at least one constraint.

Focusing on and improving the constraint leads to greater output for the entire system.

Continuous improvement is key to success.

The Five Focusing Steps of ToC

Theory of Constraints, systematic approach known as the Five Focusing Steps. These steps guide organizations on how to continuously improve their processes:

Identify the constraint – The first step is recognizing the most critical bottleneck within the system.

Exploit the constraint – Maximize the performance of the constraint using existing resources.

Subordinate everything else – Ensure all other processes align with the needs of the constraint.

Elevate the constraint – Take actions to increase the capacity of the constraint.

Prevent inertia – Once the constraint is resolved, return to Step 1 and identify the next limiting factor.

The Importance of Identifying Constraints

Identifying constraints is crucial because ignoring them can lead to inefficiencies that impact a business's ability to meet its objectives. A constraint could be anything: a machine, a policy, or even a mindset. For example, in manufacturing, a slow machine may be the constraint; in a service industry, a shortage of skilled labor could limit throughput.

How ToC Drives Business Efficiency

When a constraint is identified and addressed, the ripple effect improves the entire process. Let’s say a manufacturer discovers a bottleneck in their assembly line. By focusing on resolving this, they can increase throughput, reduce downtime, and minimize costs.

Real-world examples, like Boeing’s use of ToC in their production lines, show how companies have improved efficiency by applying these principles.

The Role of ToC in Project Management

ToC plays a significant role in project management through the use of Critical Chain Project Management (CCPM). CCPM shifts the focus from task completion to resource management, which reduces delays and improves project delivery. By applying ToC in projects, teams can complete work faster while ensuring quality.

ToC in Manufacturing and Production

Manufacturing and production processes often benefit the most from ToC. Companies like Ford, General Motors, and Toyota have applied ToC to optimize their production lines, leading to significant improvements in both output and profitability.

ToC in Supply Chain Management

In supply chain management, ToC helps organizations reduce inefficiencies and streamline their processes. By focusing on the weakest link in the chain, businesses can ensure smoother logistics and better performance across the board. Retailers like Walmart have successfully implemented ToC to ensure product availability and minimize stockouts.

ToC in Service Industries

While ToC is widely known for its use in manufacturing, it has also proven effective in service industries. Hospitals use ToC to reduce patient wait times, while IT companies implement it to enhance software development processes. The methodology’s versatility allows it to adapt to various sectors, driving efficiency wherever it is applied.

Key Benefits of Implementing ToC

Implementing ToC comes with several key benefits:

Increased productivity – Addressing the bottleneck improves the entire system.

Enhanced profitability – Focusing on constraints leads to better utilization of resources.

Reduction in lead times and costs – By eliminating inefficiencies, businesses can meet customer demand faster.

Common Misconceptions About ToC

Some people think that ToC is too rigid or only works in manufacturing, but that’s far from the truth. ToC is adaptable and can work in any industry. Others mistakenly believe that fixing a single constraint solves all problems—ToC is an ongoing process.

ToC vs. Lean and Six Sigma

While Lean and Six Sigma also aim to improve efficiency, ToC is unique because it focuses on identifying and addressing the system’s constraint. Lean focuses on waste reduction, and Six Sigma seeks to minimize variability, but ToC directly addresses the process’s limiting factor.

Practical Tips for Successfully Implementing ToC

Engage your team – Ensure that everyone understands the value of focusing on constraints.

Start small – Begin with a pilot project to demonstrate ToC’s effectiveness.

Be patient – It takes time to identify and address constraints effectively.

Monitor progress – Continuous monitoring is essential to prevent backsliding.

Conclusion

The Theory of Constraints that can significantly boost a company's productivity, efficiency, and profitability. By identifying and addressing the limiting factor in a process, organizations can unlock their full potential. The growing demand for ToC makes it an essential tool for businesses looking to thrive in today’s competitive landscape.

FAQs

How does ToC differ from other management methodologies? ToC focuses specifically on the constraint that limits a system’s output, while other methodologies like Lean focus on waste reduction and Six Sigma targets process variability.

Can ToC be used alongside other methods like Agile? Yes, ToC complements other methodologies and can be used in conjunction with Agile, Lean, or Six Sigma for enhanced results.

What are the common mistakes to avoid when using ToC? Some common mistakes include failing to identify the true constraint or neglecting to continuously improve after addressing the constraint.

How long does it take to see results from ToC? Results can vary based on the complexity of the constraint, but some businesses see improvements in as little as a few weeks.

Is ToC suitable for small businesses? Absolutely! Small businesses can benefit greatly from ToC as it helps them make the most of their limited resources.

[tenth-sentence]

"V for Vendetta" - Alan Moore and David Lloyd

[nfllivescores]

Ten Hag's Future at Manchester United: Fans and Pundits React to the Big Decision

  United   As the winds of change continue to sweep across Manchester United, Erik ten Hag’s future at the helm has become the central point of discussion among fans and pundits alike. His tenure at the club has seen both triumph and turbulence, raising questions about whether he remains the right figure to guide United back to its former glory. The decision on his future is not just a matter of…

[yousun-forgot]

A good indoor hanging decoration.

一个很好的室内挂饰。

[0xjuro]

Two things to add:

Yes, absolutely this. 100% in spirit. And add to this that chances are the math in some of those studies is bullshit, even apart from the fact that the study is being applied to things it has nothing to do with. The more studies in the chain/group, the higher the chance is that one of them is done badly/wrongly, and then your whole house of cards breaks completely anyways (because it doesn't matter how great and osha-compliant every other level of your tower is: if one of them is made of paper mache, then the whole thing will fall. logic works the same way).

The one thing I can't sign is "And any one of these steps individually would be fine and totally unavoidable" Because no, they are not. If every single one of them were then the result would actually be fine. The problem with the 'steps' ist that all of them have something wrong with them: very specific circumstances/constraints, certain errors they are introducing, bc that 'step' only 'works kinda', etc, etc. And those things add up; worse: they're multiplicative. You end up in summary with a result that applies to spherical apple trees in a vacuum that are simultaneously on swiss and american soil, and the chance that even then the result is wrong (*) is, if you're very lucky, 95%, and otherwise 99.99999998%.

(*) this does not mean that the opposite is true, but that you cannot say anything either way

data about where carbon emissions are coming from is so frustrating cause there's all kinds of huge, sprawling, just fucking vast breakdowns of What Causes The Most Carbon Emissions Out Of All Everything In The Entire World, but those are aggregations of numerous smaller but still vast aggregations of data, which are processed and polished from various aggregations of crunched numbers, which are patched and pieced together from various studies, estimates and calculations, which are sieved out of numbers crunched from various measurements, estimates and records, which have been collected, estimated or otherwise conceived through an unspeakably huge variety of methodologies with unspeakably huge variety in limitations, reliability and margins of error.

Even if some of the data was very fine-grained at the beginning, it was filtered through some very coarse number-crunching techniques for the sake of the coarse data, so the results are only as good as the wrongest thing you did in any part of this process, but the plans of action are getting thought up from the top down, which makes the whole thing a hot fucking mess.

For example. And I just made this example up. Say you want to know whether apples or potatoes have a worse impact on climate change. So you look at one of these huge ass infographic things. And it says that potatoes are bad, whereas apples are REALLY good, the BEST crop actually. So it's better to eat apples than potatoes, you think to yourself. Actually we should find a way to replace potatoes with apples! We should fund genetic engineering of apples so they have more starch and can replace potatoes. Great idea. Time to get some investors to put $5 billion towards it.

But actually. Where'd they get that conclusion about apples? Well there's this review right here of the carbon footprint of all different fruits, seems legit. Where'd that data come from? Well it's citing this study right here saying that tree-grown crops are better because they sequester carbon, and this study right here about the distance that different fruits get transported, and this study right here where different fertilization systems are compared in terms of their carbon footprint, and this study over here that sampled 300 apple, peach, and orange farmers comparing their irrigation practices and rates of tree mortality, and this study...wow, okay, seems really reliable...

...what's the first study citing? oh, okay, here's a study about mycorrhizal networks in orchards in Oregon, saying that there's a super high density of fungal mycelium in the 16 orchards that they sampled. And here's a study about leaf litter decay rates in Switzerland under different pesticide regimes, and...okay...relationship of tree spacing to below ground vs. aboveground biomass...a review of above and below-ground biomass in semi-intensively managed orchard plots...

...That one cites "Relationship between biomass and CO2 requirements...carbon immobilization in soil of various tree species...mycorrhizal fungi impact on carbon storage...

...wait a second, none of these are talking about apples, they're about boreal forests...and orange trees...and peanut farms! They're just speculating on roughly applying the non-apple data to apples. You have to go backwards...

Yes! "A review of belowground carbon storage in orchard cropping systems!" Seems like overall the studies find potentially high carbon storage in orchard environments! Walnuts...pears...oranges... intercropping walnuts and wheat... intercropping apples and wheat... wait a second, what about orchards with only apples?

Time for you to go back again...

"New method of mulching in apple orchards can lower irrigation and pesticide needs..." okay but if it's new, most farmers aren't doing it. "Orchards with high density interplanted with annual crops show way more mycorrhizal fungus activity..." "Mycorrhizal associations with trees in the genus Malus..."

...And pretty soon you've spent Five Fucking Hours investigating apples and you've got yourself in this tangled web of citations that demonstrate that some orchard crops (not necessarily apples) store a lot of long-lasting biomass in their trunks and roots really well—and some apple orchards (not necessarily typical ones) have high amounts of mycorrhizal fungi—and some techniques of mulching in orchards (not necessarily the ones apple farmers use) experience less erosion—and some apple trees (not necessarily productive agricultural apples) have really deep root systems—

—and some environments with trees, compared with some conventional agricultural fields, store more carbon and experience less erosion, but not apple orchards because that data wasn't collected in apple orchards.

And you figure out eventually that there is no direct evidence anywhere in the inputs that singles out apples as The Best Crop For Fighting Climate Change, or suggests that conventional apple farming has a much smaller carbon footprint than anything else.

The data just spit out "apples" after an unholy writhing mass of Processes that involved 1) observing some tree-grown crops and deciding it applies closely enough to all tree grown crops 2) observing some apple orchards and deciding its applicable enough to all apple orchards 3) observing some tree-including environments and deciding its close enough to all tree-including environments 4) observing some farming methods and deciding it applies closely enough to all farming methods

And any one of these steps individually would be fine and totally unavoidable, but when strung together repeatedly they distort the original data into A Puddle of Goo.

And it wouldn't be that bad even to string them together, if trees didn't vary that much, and farming didn't vary that much, and soil didn't vary that much, and mycorrhizal networks didn't vary that much, and regions that grow apples didn't vary that much, and pre-conversion-to-apple-orchard states of apple orchards didn't vary that much, and economic incentives controlling apple farming didn't vary that much, but all of these things DO vary, a Fuck Ton, and if the full range of variation were taken into account—nay, intentionally optimized—the distinction between apples and potatoes might turn out to be be MEANINGLESS GOO.

anyway big size piles of data about Farming, In General, make me so bitchy

[poligraf]

When you write a poem, you discover that the very necessity of fitting your meaning into such and such a form requires you to search in your imagination for new meanings. You reject certain ways of saying it; you select others, always trying to form the poem again. In your forming, you arrive at new and more profound meanings than you had even dreamed of.

— Rollo May