Politics & Stuff

[cosmicway 1,333]

Trump has won the battle of taxes.
Taxes are always useful for the government, for national projects.
The army and the navy first and foremost, but also roads, parks, monuments inside parks and other things.

But their usefulness in the daily life of the citizens is limited as well as ambiguous.
For the common Joe Bloggs it means two weeks vacations instead of four.
The Greek socialist governments for instance brag about "tourism for the people".
Fine. You fancy a stay in the island of Tino in the month of December ? Waves ten meters high, torrential rains like in the tropics.
Of course the money goes into the pockets of socialist aparachicks but that's another story.
And it's not even Tino. What I think is available is the top of mount Kaimakchalan, where the Greeks had been fighting the Italians.

Socialist taxes are a nightmare.
First they are directed against rich and poor alike.
The big multinational corporations actually like this because it kills competition.
A little more tax on them does n't hurt. The hunt for undeclared swimming pools does n't hurt them because theirs are declared.
If you own one of the two big carpet galleries do you like the gypsy woman who used to sell carpets in the flea markets ?
Not so good those, but some people make do with them so you love to see them taxed out of business.

Also the big companies immediately pass the additional cost due to socialist taxes to the consumer.
So you go to the supermarketand the prices have gone up.
The answer ?
Eat peeled tomatoes stuffed with rice because it's cheap.

The socialists along with their communist cousins live in the 19th century world of Dostoyevski, the little girl with the matches.
They believe the lower economic classes are allf brick layers and dockyar dworkers.
So the various "capitalist wannabes" must be punished.
The communists in particular believe we are all factory workers ready to come out in the streets and start the revolution.
They don't realise even the basic fact that most factories are nowadays away in the suburbs, in the countryside and the workers
are transported with company buses. How am I going to march from somewhere near the airport to the centre and start the
revolution ?

Hence Trump wins.




 

Edited October 28, 2024 by cosmicway

[Vesper 30,224]

9 hours ago, cosmicway said:

Trump has won the battle of taxes.
Taxes are always useful for the government, for national projects.
The army and the navy first and foremost, but also roads, parks, monuments inside parks and other things.

But their usefulness in the daily life of the citizens is limited as well as ambiguous.
For the common Joe Bloggs it means two weeks vacations instead of four.
The Greek socialist governments for instance brag about "tourism for the people".
Fine. You fancy a stay in the island of Tino in the month of December ? Waves ten meters high, torrential rains like in the tropics.
Of course the money goes into the pockets of socialist aparachicks but that's another story.
And it's not even Tino. What I think is available is the top of mount Kaimakchalan, where the Greeks had been fighting the Italians.

Socialist taxes are a nightmare.
First they are directed against rich and poor alike.
The big multinational corporations actually like this because it kills competition.
A little more tax on them does n't hurt. The hunt for undeclared swimming pools does n't hurt them because theirs are declared.
If you own one of the two big carpet galleries do you like the gypsy woman who used to sell carpets in the flea markets ?
Not so good those, but some people make do with them so you love to see them taxed out of business.

Also the big companies immediately pass the additional cost due to socialist taxes to the consumer.
So you go to the supermarketand the prices have gone up.
The answer ?
Eat peeled tomatoes stuffed with rice because it's cheap.

The socialists along with their communist cousins live in the 19th century world of Dostoyevski, the little girl with the matches.
They believe the lower economic classes are allf brick layers and dockyar dworkers.
So the various "capitalist wannabes" must be punished.
The communists in particular believe we are all factory workers ready to come out in the streets and start the revolution.
They don't realise even the basic fact that most factories are nowadays away in the suburbs, in the countryside and the workers
are transported with company buses. How am I going to march from somewhere near the airport to the centre and start the
revolution ?

Hence Trump wins.

[Vesper 30,224]

Trump’s Tax Cuts Were a Disaster. Naturally, Republicans Want Even More.

Study up, because they’re about to try again.

July/August 2020 Issue

https://www.motherjones.com/politics/2020/06/trumps-tax-cuts-were-a-disaster-naturally-republicans-want-even-more/

In 1980 the federal deficit was soaring and Ronald Reagan campaigned on a singular promise: He planned to cut taxes on everyone, but especially the rich. He insisted that those benefits would quickly trickle down to everyone and supercharge the economy. Throw in some social safety net cuts, Republicans said, and the whole plan would pay for itself.

They were wrong. The rich got lower taxes all right, but the economy flatlined and the deficit skyrocketed. I should know: I graduated from college the same summer the tax cut passed, and I spent the next three years managing a Radio Shack waiting for the economy to get back on its feet. In 1982 Reagan was forced to raise taxes to make up for his cuts, and he continued raising them throughout his presidency.

In 1993 Bill Clinton passed a tax increase to reduce the deficit. Republicans insisted it would do no such thing. In fact, they said, it would cripple the economy.

They were wrong. The economy boomed, and for the first time since the Roaring ’20s the deficit turned into a surplus for four consecutive years.

In 2001—and again in 2003—George W. Bush passed a tax cut. Once again, Republicans said it would supercharge the economy and pay for itself.

They were wrong. All we got was a jobless recovery and a housing bubble that wrecked the economy. It produced the worst economic downturn since the Great Depression.

At the beginning of 2013, as part of the “fiscal cliff” negotiations, Barack Obama forced Republicans to accept a tax increase on high earners. But even though the bill passed with bipartisan support, some Republicans insisted it would kill the economy.

They were wrong. The deficit declined and Obama produced the longest economic recovery in American history—one that was still going strong until the coronavirus pandemic killed it.

Finally, in 2017, Republicans passed yet another tax cut. This one primarily benefited corporations and the rich, and once again Republicans insisted it would supercharge the economy and pay for itself.

They were wrong. No—scratch that. They lied. They knew the evidence of the past 40 years as well as anyone, but they sold the public a bill of goods anyway.

Every single economic indicator Republicans said would go up, didn’t.

Why? Because for all of Donald Trump’s bluster, this was the one thing he really, truly had to do. It’s the one thing the Republican Party’s big donors insist on. They don’t care about immigration or tariffs. Not much, anyway. But they care about lower taxes. As then-New York Rep. Chris Collins (since convicted of insider trading) told reporters shortly before the tax cut was signed into law, donors were telling him, “Get it done or don’t ever call me again.” So they got it done.

The 2017 tax cut had to be supported by a farrago of dishonesty for an obvious reason: The public would never support a tax cut aimed primarily at making the rich richer and swelling the coffers of large corporations—which also benefited the rich. Why would they? So Republicans had to lie. And this time they couldn’t rest with a single lie. Polls showed that voters were skeptical of their tax cut, so this time Repub­licans had to pile lie on top of lie.

Why does this matter? For two reasons—one, lies about tax cuts have determined the course of America’s economy, and the individual fortunes of millions of families including yours, for decades. Many of the inequities laid bare by the pandemic have been in the making since the Reagan era. And two, amid the coronavirus crisis, we’re about to have another debate over whether tax cuts can juice the economy. To evaluate those claims, it behooves us to look at what Republicans said about their 2017 tax cut—compared to what actually happened. Spoiler alert: Every single economic indicator Republicans said would go up, didn’t.

It all started with the initial justification for the tax cut: namely that American corporations paid the highest tax rates in the industrialized world, which put them at a huge competitive disadvantage. So at the end of 2017, while they still had full control of Congress, Republicans passed a $1.5 trillion tax cut—nearly the size of the gigantic coronavirus rescue bill passed in March. The 2017 bill contained cuts to both the personal tax rate—which mostly benefited the rich—and the corporate rate. But Republicans faced a cognitive dissonance problem: Weren’t American corporations actually doing pretty well? Why did they need a huge handout?

This is where the first lie came into play. It’s true that the United States had a high corporate tax rate, but few American corporations paid that official rate. In fact, if you look at actual corporate tax revenue, it turns out the United States has been pretty friendly toward big business. The real corporate tax rate is middling, and among the 20 richest developed countries, the US tied for dead last in how much of its GDP comes from such taxes.

This was no secret. So to justify cutting corporate tax rates even further, Republicans had to manufacture a laundry list of reasons it would be good for the economy. And that’s when the lies started piling up.

1. Business investment will skyrocket

The first and most fundamental logic behind the Republican predictions that a corporate tax cut would promote economic growth and higher tax revenues was a simple one. According to the academic language in a paper published by the White House Council of Economic Advisers, “A decrease in the tax rate on corporate profits…decreases the before-tax rate of return used to assess the profitability of an investment project.”

In plain English this means that corporations will only make investments that are likely to be profitable. Taxes are part of this, so if you decrease the tax rate on profits, more investments will go forward. In the words of Larry Kudlow, the lifelong supply-sider who became director of President Trump’s National Economic Council, corporate tax cuts produce an “investment boom.”

But Kudlow’s boom never came. Taxes may matter, but what matters a lot more is whether corporations have confidence that the economy will grow vigorously and produce more demand for their products and services. The Republican tax cut didn’t produce that confidence. Regardless of what they said in public, most CEOs knew perfectly well that a tax cut was just a temporary shot in the arm. It might modestly spur consumer demand for a short time, but in the long run it would do nothing—or maybe even produce a weaker economy.

Sure enough, business investment, which usually reflects decisions made in the past, grew on autopilot for a couple of quarters, but after that, steadily declined. In the last quarter of 2019, the level of business investment was lower than it was a year before.

You can also look at new orders for capital goods, which generally react quickly to changes in the economic outlook. But the growth rate of new orders began declining immediately after the tax cut was passed, reaching zero in late 2018 and falling into negative territory in mid-2019. (Charts are adjusted for inflation where relevant and run through the end of 2019, before the COVID-19 recession took hold.)

 

It’s been more than two years since the tax cut passed, and if an investment boom were going to happen, we would have seen it by now. We haven’t. Trump may like to brag about the “greatest economy in history” that he claims he built before the pandemic struck, but all we saw was an investment bust.

2. The economy will be supercharged

If an investment boom was the big lie that drove everything, the arguments made to the general public in support of the tax cut mostly revolved around a better-­known metric: economic growth. The usual way of measuring this is by looking at gross domestic product, the sum of all goods and services produced in the United States. In the decade since the end of the Great Recession, GDP growth has averaged 2.3 percent per year.

Republicans claimed that the investment growth spurred by the tax cut would drive GDP growth higher. Kudlow predicted growth rates of 3 to 4 percent. Treasury Secretary Steven Mnuchin went with a more modest 2.9 percent. Trump himself told reporters at his Cabinet meeting that he was holding out for 6 percent growth. These projections were mostly just spun out of thin air.

So how did we do? Since the investment boom never materialized, it’s hardly a shock to learn that GDP growth didn’t boom either. The growth rate increased modestly for two quarters and then dropped steadily. In the last quarter unaffected by the coronavirus crisis, it was barely above 2 percent. Not only didn’t the tax cut usher in the growth that Republicans predicted, but growth rates started dropping soon after.

3. The tax cut will pay for itself

It was an article of faith among Republicans that their tax cut wouldn’t just boost economic growth, but would actually generate more revenue than the old, higher tax rates. “Not only will this tax plan pay for itself, but it will pay down debt,” Mnuchin said. Kevin Hassett, then chair of the White House Council of Economic Advisers, agreed: “You don’t really need to have a big growth effect to have Secretary Mnuchin be correct.” Former Rep. Jeb Hensarling, chair of the House Finan­cial Services Committee, insisted that economic growth would be “more than enough” to make up for the lower tax rates.

That growth failed to materialize. Unsurprisingly, so have higher tax revenues. Corp­orate tax receipts plummeted from $240 billion to $140 billion in the first quarter after the tax cut passed, and have stayed at that level ever since.

So what happened to the federal deficit? Republicans lied about the effect of their cut on tax receipts and at the same time they also decided to stop worrying about keeping spending down. As a result, the federal deficit has gone up—and that’s not even accounting for the COVID-19 stimulus spending. This comes as no surprise to anyone who has heard the same Republican tax argu­ments for decades and now recognizes them for the fabrications they are.

 

4. Corporations will bring back profits stashed overseas

Republicans did their best to include as many corporate giveaways as possible in their tax cut, but spun them as a benefit to the greater economy. Take “repatriated earnings.” American multinational corporations like to keep their overseas profits away from the IRS, and the Republican tax plan aimed to change this by offering companies a temporary “tax holiday.” Earnings kept overseas would be subject to a one-time tax at a very low rate that could be paid over the course of eight years. President Trump promised that this would produce a flood of repatriated earnings amounting to $4–$5 trillion—nearly twice the amount that corporations were actually storing overseas.

This was just another lie, one that no serious economist believed for a moment. And indeed, after a brief boom in repatriated earnings after the tax cut passed, there was a bust. Repatriations to date have amounted to only $840 billion above normal, and the total amount of repatriations in the last quarter of 2019 is only $60 billion higher than it was before the tax cut passed. The total will never come anywhere close to $4–$5 trillion.

Why does this matter? The Republican theory was that companies would use their repatriated earnings to invest in new capacity, which in turn would boost the economy. This was an unusually feeble lie since American companies were already sitting on huge stockpiles of cash that they could have spent if they wanted to. The four biggest US tech companies alone—Apple, Amazon, Google, and Microsoft—had more than $340 billion in cash on their books. But companies don’t invest simply because they have spare money lying around; they only invest if they think the economy is going to grow. If they don’t believe that, they’ll take the extra cash and return it instead to stockholders—i.e., the rich. And that’s exactly what they’ve done.

But maybe foreign investors responded more positively to the tax cut than domestic investors did? Nope. Foreign investment increased briefly but then plunged. Apparently they didn’t take Republican promises any more seriously than Americans did.

 

5. Your wages will skyrocket

If all this weren’t enraging enough, just wait. You see, the White House also promised something else: that the wages of ordinary workers like you would go up. How much? The claims were all over the map. In a single CEA paper, administration economists predicted that average incomes would rise at least $3,000 and perhaps as much as $9,000 after the tax changes had been “fully absorbed by the economy.” This was on top of the normal income growth already baked into economic forecasts. So what actually happened?

Well, not only are we nowhere near the White House projections, we’re actually still on the trend that was predicted without the tax cut. The Republican tax cut did your wages no good at all.

But wait. What about bonuses? Lots of companies promised they’d pay out extra bonuses if the tax cut passed. AT&T promised $1,000 per employee. Comcast followed suit and Southwest and American Airlines joined in too. Walmart was less generous: It also announced a $1,000 bonus, but only for workers who’d been with the company for at least 20 years.

It made for great headlines. But once the klieg lights were off, bonuses nose-dived to less than they had been before the tax cut.

In the end, the Republican tax cut didn’t help your wages and it reduced your bonus. Are you mad yet?

6. Jobs, jobs, jobs!

Mnuchin declared that the Republican tax bill would be a boon for employment. “This is about jobs,” he said. “This is a jobs bill.”

But it wasn’t. If you look at the total share of the country with jobs—the “employment-to-population ratio”—nothing happened after the tax cut passed. It had been growing since the end of the Great Recession and it continued growing at the exact same rate after the tax cut was passed, until COVID-19 hit.

7. Tax cuts for all

Of course, the Republican tax act did more than just reduce the corporate tax rate. It also reduced individual income taxes for nearly everyone—partly by cutting tax rates and partly by adding a hodgepodge of other benefits. But for most of us, there’s less there than meets the eye.

In 2018, nearly everyone got a tax break, and after-tax incomes went up—although the income of the rich went up a lot more than the income of the middle class. By 2025, the tax break for the middle class will start to vanish. And by 2027, the reduction in income tax rates will disappear for everyone. However, the rich—and only the rich—will continue to benefit from other tax breaks.

Republicans claimed that ending the rate cuts in 2027 was nothing more than an accounting requirement to meet congressional budget rules. They’ll restore it later. But this is just a con job. If they were really sure they could eliminate tax cuts and restore them later, why not zero out their patchwork of tax cuts for the rich? The question answers itself.

8. But guess what? Corporate profits soared

To summarize: The economy didn’t boom, investment didn’t increase, employment didn’t go up, household earnings didn’t surge, and the middle-class tax cuts started out small and then disappeared completely. But there’s one thing that has worked—besides tax cuts for the rich, that is: corporate profits have fattened nicely. Check that out. Corporate profits jumped 8 percent immediately after the tax cut was passed, and they’ve stayed at their new, higher level ever since. It all goes to show that Republicans can accomplish their goals when they put their mind to it. You just have to know what their goals really are.

Now it’s time for a look into the near future. But first let’s zoom out a bit because there’s more to this than just tax cuts for the rich. Republicans have long been devoted to a strategy called “starve the beast,” which has a simple goal: (a) cut taxes, (b) watch revenues fall, and (c) insist that spending has to be cut to avoid big budget deficits. And while the rich may get the tax cuts, the spending cuts are inevitably aimed at the poor and middle class. This is especially effective at the state level because most states aren’t allowed to run budget deficits. If tax revenues fall, they have to cut spending.

And now we have to deal with a pandemic. If the holes in our eroding social safety net seemed patchable before, they don’t any longer. Unemployment insurance? Democrats did a good job of demanding a temporary funding increase, but not everyone benefits because many states have spent years deliberately making their systems hard to use and they’re unable to hold up under hundreds of thousands of new applicants.

When economists say “stimulus,” Republicans hear “tax cut.”

Food stamps? Republicans are trying to cut them back just as we need them more than ever. Medicaid? The federal government can still afford to pay its share, but can states? Their tax revenues have plummeted and Republicans have balked at helping them out.

Thanks to the pandemic, we’re about to get hammered by the business end of the starve-the-beast strategy. Tax revenues have already declined due to the Republican tax cut, and they’ll decline more because Republicans used the corona­virus rescue bills to quietly “fix” a few problems in their 2017 bill that turned out to be annoying to the rich. Beyond that, spending has exploded as the rescue bills create trillions in temporary new outlays to help people and businesses brought to their knees by lockdowns and closures. This is going to cause a massive increase in the federal deficit, and Republicans are already making noises about suddenly becoming deficit hawks again. In fact, within minutes of passing the April coronavirus bill, Senate Majority Leader Mitch McConnell was warning that “we can’t borrow enough money to solve the problem indefinitely.”

But even though Republicans may wish they could stop further rescue packages, as we come to grips with the scale of the wreckage, there will be demands for more. Epidemiologists think it’s likely we’ll have another surge of coronavirus cases in the fall, and that will produce more calls for large, broad-based stimulus bills to keep the economy afloat.

When economists say “stimulus,” Republicans hear “tax cut.” As it happens, there are actually good reasons to include certain kinds of tax cuts—those that help middle- and working-class people—in any stimulus package. They can be implemented quickly; they can be made as large as necessary; they put money directly in consumers’ pockets; and they can even be targeted to a certain degree, helping those who have suffered the biggest losses from the pandemic.

But they can also be targeted toward the rich. And that’s what Republicans are certain to propose. So here are some alternatives that Democrats would be well advised to look at.

The most obvious candidate is the Social Security payroll tax. You pay a flat tax of 6.2 percent—which makes it regressive to begin with—and it applies only to your first $137,700 of income. Everything above that is tax free, which is why millionaires pay an effective rate of less than 1 percent.

Suppose you reduce the worker’s share of the payroll tax by two percentage points. This barely affects the rich: A millionaire’s effective rate goes down from 0.9 percent to 0.6 percent. But everyone with less than $137,700 in income sees their rate go down from 6.2 percent to 4.2 percent. The nonrich benefit considerably while the rich barely even notice anything has happened.

But there’s a catch: Payroll tax cuts do nothing for you if you’re unemployed, or you’ve been laid off, or you’re paid under the table. This is why Democrats fought against a payroll tax cut in the first round of corona­virus rescue packages. But even more importantly, the payroll taxes fund Social Security, and if you reduce them, Social Security will be even more underfunded than it is now. The answer is to make sure that any loss of payroll tax revenue to Social Security is made good by infusions from the general fund. These would need to last as long as the stimulus bill is active.

Another candidate is an increase in tax credits. Unlike a deduction, tax credits are subtracted from your taxes owed. The higher the credit, the lower your taxes. Current examples include the child tax credit and the Earned Income Tax Credit.

Increasing credits is an attractive way to juice the economy because they often have fixed maximum amounts. If you lower the taxes of a millionaire by, say, $3,000, it’s a drop in the ocean. But for a middle-class family it’s real money. Democrats could propose increases in existing tax credits, or just a brand-new “pandemic tax credit.” Either way, it could cut taxes without shoveling money into the wallets of the rich.

Another subtler form of taxation that Democrats could target is tax expenditures. A tax expenditure is a deduction, exemption, or exclusion targeted at a specific activity. The most famous is the mortgage interest deduction, which is a straight-up subsidy to homeowners, but one that’s hidden in the tax system. There are more than 100 different expenditures adding up to well over $1 trillion—more than the revenue from Social Security taxes, corporate taxes, or excise taxes. (And not much less than we get from federal income taxes.)

Tax expenditures tend to favor the rich. For example, a middle-class homeowner might pay a 12 percent income tax rate and own a modest home that nets a deduction of $5,000. That’s a tax reduction of $600. And if they don’t have other expenditures to itemize, they might not get a reduction at all.

But a rich homeowner might pay an income tax rate of 37 percent and own an expensive home that nets a deduction of $50,000. That’s a tax reduction of $18,500.

If it’s a tax cut fight they want, Democrats can come armed with a slate of their own options.

The easiest way to make this fairer is to cap the amount of the deduction—as, in fact, we do with the mortgage interest deduction. But the better bet is to increase the deduction for nonrich families. Maybe we could just double the deduction for anyone with an income under $100,000. That would cut their taxes without also giving a windfall to the rich.

Finally, there’s another class of taxes entirely: state and local taxes. The sales tax is the obvious target here: It’s big and regressive. The catch is that it’s not controlled by the federal government, and Congress can’t lower it by fiat.

That doesn’t mean Congress is helpless: It could pass a federal rebate on state sales taxes. It could, for example, allow a federal tax credit based on an estimate of how much you paid in sales taxes. This would be calculated from your income and your state’s sales tax rate and would necessarily be approximate. But it would also be progressive.

And there’s one more big lever that could be used. A combination of these cuts could obviously send taxes below zero for some people. At that point, working- and middle-­class families would lose the benefit of the cut since taxes can’t be less than zero.

Except they can: If a tax credit is refundable, it means your income taxes can become negative and the federal government owes you money. In all cases where it’s possible, progressive tax cuts should be refundable. The point, after all, is to give as much money as possible to the kind of people who will spend it to boost the economy. That means working- and middle-class families, who tend to spend most of the money they earn, as opposed to rich families who end up saving or investing much of it.

Will Republicans agree to any of this? Almost certainly not. They understand perfectly well who benefits from different kinds of tax cuts, and as 2017 demonstrated, they don’t care about spurring the economy or creating jobs for the middle class. Nor do they care about reducing the deficit or raising your wages. That was all just bread and circuses to keep the rubes happy.

What they do care about is increasing the income of corporations and the rich, and that’s what they’ll fight for. But if it’s a tax cut fight they want, Democrats can come armed with a slate of their own options. Maybe they won’t get everything they want. Maybe they’ll have to accept some Republican cuts in return for some of their own. But they’ll have a story to tell, and leverage, to get at least something for the middle and working classes.

In the past, Democrats have mostly just tried to gin up opposition to Republican tax cuts by pointing out how unfair they are. It’s never worked, but the fiasco of the 2017 cut, which even the Republican rank and file was lukewarm about, gives Democrats an opportunity to fight back. Instead of just opposing cuts even if there’s a strong case that we need them to stimulate the economy, they can propose better, more equitable tax cuts than Republicans. That would be something new: a chance to educate the electorate by having a showdown over competing tax plans. In the red corner, tax cuts for millionaires. In the blue corner, tax cuts for everyone else. That’s a fight worth having.

 

[Vesper 30,224]

Trump Says Jack Smith Should Be Thrown Out of the Country, Suggesting He Believes You Can Deport American Citizens—and That in a Second Term, He’ll Try

He also called for the “mentally deranged” to be kicked out of the US.

 

https://www.vanityfair.com/news/story/trump-says-american-citizen-jack-smith-should-be-thrown-out-of-the-country

Donald Trump on Thursday gave voters a preview of what America would look like should he win a second term when he declared that Jack Smith, the prosecutor running two federal cases against him, should be be “throw[n]” out of the country.

“We should throw Jack Smith out with them, the mentally deranged people. Jack Smith should be considered mentally deranged, and he should be thrown out of the country,” Trump said during an interview with a conservative radio talk show.

Setting aside the idea that Trump apparently believes mental illness is a reason to kick people out of the US, he appears to also think that the US government can deport American citizens—and that, given the opportunity, he’d try. The ex-president’s comments re: Smith being thrown out of the country, came hours after he said in an interview that he would fire the special prosecutor “within two seconds.”

 

Earlier this month, Trump started warning about the need for using the military against the “enemy from within,” which he initially defined as Democratic lawmakers like California representative Adam Schiff, but later said referred to anyone who doesn’t support him.

 

In response to Trump’s latest comments, a spokesperson for Kamala Harris’s campaign said in a statement: “A second Trump term, where a more unstable and unhinged Trump has essentially no guardrails and is surrounded by loyalists who will enable his worst instincts, is guaranteed to be more dangerous. America can’t risk a second Trump term.” During a town hall with CNN on Wednesday, Harris said she believes Trump is a “fascist” and represents a “danger to the well-being and security of the United States of America.” The VP’s remarks followed a warning from John Kelly, a retired four-star general and Trump’s former chief of staff, that his ex-boss is an “authoritarian” who holds Adolph Hitler in high regard (a claim that Trump denied).

At this time, you might be wondering if Republicans have anything to say about about all of this. And the answer is, they do! Specifically, they think that Harris needs to “abandon the base and irresponsible rhetoric that endangers both American lives and institutions,” as GOP leaders Mitch McConnell and Mike Johnson wrote in the most shameless joint statement of all time, which they released on Friday. Did McConnell and Johnson have anything to say about Trump calling for the military to be used against people who don’t support him, or threatening to deport a US citizen? You probably already know the answer to that.

 

[Fulham Broadway 17,333]

CNN -''Welcome to Trumps rally, We are hearing scores of lies'' 🤣

 

[Vesper 30,224]

1 week to go (and NOT my final prediction).

Gun to my head (so I force myself to give PA and NV to Harris, and GA and NC to Trump instead of leavinbg them toss-ups, plus I am a wee bit more sure Harris wins MI and Trump wins AZ).

It comes down to one state:

Wisconsin

I spent 6 hours on a zoom call yesterday for my job with all this, with our team going full deep divey.

Wisconsin atm is truly too cose to call, including looking at trends across all levels.

Many of these may change by Monday (the 4th of November, the day before the election) when I give my final prediction.

[Vesper 30,224]

1 hour ago, Vesper said:

1 week to go (and NOT my final prediction).

Gun to my head (so I force myself to give PA and NV to Harris, and GA and NC to Trump instead of leavinbg them toss-ups, plus I am a wee bit more sure Harris wins MI and Trump wins AZ).

It comes down to one state:

Wisconsin

I spent 6 hours on a zoom call yesterday for my job with all this, with our team going full deep divey.

Wisconsin atm is truly too cose to call, including looking at trends across all levels.

Many of these may change by Monday (the 4th of November, the day before the election) when I give my final prediction.

The Crucifucks - Wisconsin (Full Album) 1987

Label: Alternative Tentacles – VIRUS 53

Format: Vinyl, LP, Album, Yellow Transparent

Country: UK

Released: 1987

Genre: Rock

Style: Alternative Rock, Punk

Edited October 29, 2024 by Vesper

[cosmicway 1,333]

13 hours ago, Vesper said:

 

 

[Vesper 30,224]

The nation’s birthrate has plummeted. How did we get here?

Women are having children at the lowest rate since records began, with consequences for us all

https://www.thetimes.com/uk/society/article/the-nations-birthrate-has-plummeted-how-did-we-get-here-30qtqddwn

After the Second World War came the “baby boomers” — when the fertility rate in England and Wales rose by almost 30 per cent in seven years. But the rate has now dropped to its lowest in at least 85 years.

Last year the fertility rate — the average number of children born to a woman over her lifetime — had fallen to 1.44 children per woman.

This is the lowest rate since records began in 1938:

Greg Ceely, from the Office for National Statistics, says the decline is “most dramatic” among women in their twenties.

So, how did we get here?

In 1938, just before the Second World War, the fertility rate stood at 1.84 children per woman. As the war ended more babies were being born, rising from 614,000 in 1939 to 821,000 in 1946. 

The number of women aged between 15 and 44, considered to be childbearing age, stayed at about ten million, according to the ONS, meaning the fertility rate rose from 1.73 in 1939 to 2.47 in 1946.

The generation born during this period — known as the “baby boomers” — were more likely to have children, and earlier in life, than any other since 1920.

Westminster Hospital, 1941

GEORGE HALES/FOX PHOTOS

The average age of first birth for women born in 1946 was 23 years. More than half, or 52 per cent, of women born in 1946 had a child before the age of 24, compared with 32 per cent among women born in 1920.

Fewer than one in ten women of this generation had no children at all, compared with about one in five among women born in 1920 or 1969, the ONS said.

By the early 1960s the number of births had been rising and, as fewer babies were born in the 1930s, there were also fewer women at this time of childbearing age. The result of more babies being born to a smaller group of women across a wider age range was that the fertility rate rose to a peak of 2.93 children per woman in 1964.

The introduction of the Abortion Act 1967 and increasing availability of oral contraception gave women greater access to birth control. This contributed to a decline in births and the fertility rate fell to 2.47 in 1969.

The first babies of the new year on January 1, 1968, at Marston Green Maternity Hospital in Birmingham

MIRRORPIX/GETTY IMAGES

In the UK, women would need to have 2.08 children on average to ensure the long-term natural replacement of the population, known as “replacement level” fertility.

By 1973 the total fertility rate had fallen beneath the replacement level for the first time since the 1940s and it has remained lower ever since.

In the 1960s and 1970s more women were entering the workforce.

By 1971 more than half of women aged 16 to 64 were employed, while by 1994 almost two thirds, 62 per cent, of working-age women were in employment.

Generation X, which came after the baby boomers, increasingly had their first child later as older traditions fell away.

Fewer than two thirds of women born in 1969 got married by the age of 30 and by the mid-1990s more than a third of children were born outside of marriage.

The number of births fell from about 700,000 a year in 1990 to just over 600,000 in 2000 and the fertility rate during this time fell from 1.84 to 1.65.

Only 20 per cent of women born in 1997 — on the cusp between millennials and Generation Z — had a child before the age of 25. That is lower than any earlier generation, continuing the trend towards later births.

For women born after the mid-1970s, age-specific fertility rates were highest among those in their thirties, marking a shift from earlier generations, who had more children in their twenties.

Women born since the mid-1990s have lower age-specific fertility rates in their twenties than any other generation since 1920, statisticians found.

There were 591,072 births in England and Wales last year, the lowest number since 1977 and only the 11th time in 172 years that the number has dipped below 600,000. The number of women of childbearing age is at its highest, however, with almost 11.9 million women aged between 15 and 44 in England and Wales in 2023.

This meant the total fertility rate in 2023 was the lowest recorded, at 1.44.

It decreased for all regions of England and Wales last year, compared with the previous year.

Wales and the northwest of England saw the largest decrease, while London, the northeast and the West Midlands saw the smallest decrease.

By 2015 more than half of young women were attending university and by 2022 more than 70 per cent of working-age women were in employment.

Research from the UCL Centre for Longitudinal Studies found that factors dissuading millennials from having children included not feeling ready, financial pressures and not finding the right partner. The cost-of-living crisis and high housing costs in Britain have also been cited as barriers to having children.

Meanwhile, the falling fertility rate has been mirrored in other countries. The global total fertility rate was 2.3 children per woman in 2022, less than half the rate in 1963.

In the European Union the fertility rate in 2022 was 1.5.

In England and Wales, the ONS said that the fertility rate would continue to be influenced by the structure of the population and the number and timing of births, as well as by socio-economic and cultural factors.

Paul Morland, 59, a demographer and author of the book No One Left: Why the World Needs More Children, said he expected the UK’s fertility rate to drop further. He said it could even plunge to levels seen in South Korea, which has a 0.78 fertility rate.

Morland said: “I think the Generation Zs, who are coming into the childbearing cohort, are very non-natal. Having children is a very low priority for them.

“The more traditional values, when I was in my twenties and thirties, that you got married and had children have gone.

“I think it’s something deeply embedded in the culture. People want to live all kinds of lifestyles … then they get to 35 and it’s very difficult to have children.”

Morland said that in addition to making it more affordable to have children, society needed to be reorganised so that “people can start to have children when they want to”.

Edited October 29, 2024 by Vesper

[Vesper 30,224]

Computer in command

Do the consequences of Algorithmic Management for workers require EU policy action?

https://feps-europe.eu/event/computer-in-command/

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The European Economic and Social Committee, Rue Belliard 99/101, 1040 Bruss

On October 16, we were at the European Economic and Social Committee, for an engaging debate on the impact of artificial intelligence and algorithmic management at work, organised by FEPS and the EESC.

The renowned speakers included Nicolas Schmit, European commissioner for jobs and social rights; Brando Benifei, Socialists and Democrats MEP; Lucie Studničná, president of the EESC Workers’ Group, and Isabelle Schömann, deputy general secretary of the European Trade Union Confederation, among many others.

We presented key findings from two pan-Nordic policy studies from the “Digital Research Programme: Algorithms in the Workplace”:

• ‘Computer in command: Consequences of algorithmic management for workers’, based on a survey of over 6,000 union members in Denmark, Sweden, Norway and Finland
• “Algorithmic management in traditional workplaces“, based on interviews with Nordic workers in traditional sectors including retail and hospitality.

We also examined EU legal provisions on AI in the workplace, identifying critical areas that require a reassessment of its application, the potential actions trade unions can take and necessary legislative interventions.

*******************

76% of workers within sectors like warehousing and telemarketing experience one or more forms of Algorithmic Management (AM) in the workplace. They report having less autonomy in their jobs, a greater workload, feeling more stressed, and greater concern among employees about their job security.

These are the findings from the transnational survey Computer in command: Consequences of algorithmic management for workers conducted by FEPS and Nordic think tanks among over 6,000 union members in Denmark, Sweden, Norway, and Finland.

Algorithmic management, the use of algorithms and artificial intelligence to direct and control workers, is increasingly reshaping the modern workplace. These technologies are touted as pathways to greater efficiency, productivity, and streamlined operations. However, the reality is far more complex. While digital tools have the potential to revolutionise work, they often lead to heightened pressures, reduced autonomy, and increased precarity for workers.

At this event, we explored these impacts, extrapolating its focus from the unique labour environments of the Nordic countries—Finland, Sweden, and Norway— where long-standing traditions of labour organisation intersect with rapidly advancing technologies to their implications over EU policy making.

[Vesper 30,224]

https://www.vanityfair.com/news/story/trumps-msg-rally-was-a-preview-of-his-second-term

New York, New York - October 27: Former president Donald Trump speaks at a rally on Oct. 27 at Madison Square Garden in New York. (Photo by Peter W. Stevenson /The Washington Post via Getty Images)The Washington Post/Getty Images.

If Donald Trump wins the 2024 election and returns to the White House for a second term, one thing people will absolutely not be able to say is “I didn’t think it would be so bad.” First, because Trump has been literally telling us exactly how bad things will get should he win another round in office, and second, because it was truly all on display last night at Madison Square Garden.

Trump’s Manhattan rally, held just over a week before Election Day, can and should be viewed as his closing message to voters. The message? That he and his associates believe,* among other things, that:

This is an acceptable way to talk about Latinos, a.k.a. Americans

 

That Puerto Rico, a.k.a. home to millions of US citizens, is a “floating island of garbage”**

 

That Kamala Harris has “pimp handlers,” the takeaway seemingly being that the female nominee for president is a prostitute

 

That this is an acceptable way to talk about Palestinians and Jews

 

That Hillary Clinton is a “sick bastard”

 

That “America is for Americans and Americans only,” a line the man who uttered it on Sunday will have absolutely known had disturbing historical parallels

 

That Americans who don’t support him are the “enemy from within”—a claim he has made numerous times over the last month

 

In addition to previewing the groups he can be expected to go after in a second term—possibly with military force—Trump also suggested he’s got a plan to make it back to the White House in the event the votes don’t go his way. “We can take the Senate pretty easily, and I think with our little secret we’re gonna do really well with the House, right?” Trump said, speaking to House Speaker Mike Johnson, who was in the audience. “Our little secret is having a big impact. He and I have a secret—we’ll tell you what it is when the race is over.”

 

Anyway, yeah, this as as clear a warning as we’re going to get.

 

*It’s important to note that after he took the stage on Sunday, Trump did not disavow any of the remarks that people had made before him, which he of course could have.

As of Monday afternoon, the campaign had only spoken out against the line about Puerto Rico. A spokesperson for the Trump campaign said, of the “floating island of garbage” line, that “This joke does not reflect the views of President Trump or the campaign.”

That claim would be more believable if Trump (1) hadn’t treated Puerto Rico as an inconvenience when he was president (2) hadn’t reportedly tried to trade Puerto Rico for Greenland and (3) didn’t himself speak using the same dehumanizing language.

[Vesper 30,224]

https://www.thetimes.com/uk/environment/article/climate-change-action-worse-after-emissions-hit-record-high-n8pcprg75

The United Nations has warned that progress on tackling climate change is in a “worse position” than it was a year ago after emissions jumped to a record high in 2023.

Global carbon emissions rose faster than average last year and countries have failed to upgrade their national climate plans despite calls from campaigners, businesses and António Guterres, the UN secretary-general.

“As this report rightly puts it, people and planet cannot afford more hot air,” said Guterres. “There is a direct link between increasing emissions and increasingly frequent and intense climate disasters. Around the world, people are paying a terrible price.”

The direction of travel has left earth on track for what the UN Environment Programme (Unep) called a “catastrophic” 2.8C of global warming by the end of the century. That is far off the Paris Agreement goal, pledged by the UK and nearly 200 other countries, of limiting temperature rises to 1.5C or “well below” 2C.

In a wide-ranging report, Unep found inadequate action last year and a 1.3 per cent increase in emissions to 57 billion tonnes of carbon dioxide meant the 1.5C goal “will soon be dead”.

“Every year of insufficient action puts us in a worse position. We only have six years to cut global emissions by 42 per cent to hit 1.5C. But there has been non-measurable global progress in ambition and action, and the growth in emissions last year even surpassed the average annual growth rate of the decade preceding covid-19,” said Anne Olhoff, the report’s chief scientific editor.

The assessment found that China is no longer only the world’s biggest carbon polluter today, but also one of the largest of all time. The country’s historical emissions are now on a par with the European Union, at 12 per cent of carbon dioxide released since 1850, though still dwarfed by the US on 20 per cent.

Environmental groups often cite the historical emissions of nations as a reason for them to pay climate finance to smaller emitters.

The Unep team said that one glimmer of hope, of predictions last year that 2024 could be a landmark moment when global emissions peak, was now looking less likely. “While renewables continue to break records, surging energy demand means that it is less likely that emissions fall in 2024 than before,” said Neil Grant, an author of the report.

The findings come less than three weeks before the UK and nearly 200 other countries meet for the Cop29 climate summit in Azerbaijan. Top of the agenda will be how much money rich nations such as the UK will pledge to give poorer, more vulnerable countries to tackle and adapt to climate change.

Unep said the bulk of future emissions cuts need to come from the G20, which was responsible for nearly four fifths of carbon pollution in 2023. By comparison, the 47 least developed countries, such as Afghanistan, Chad and Haiti, account for only 3 per cent.

 

Ed Miliband, the energy secretary, is heading to Cop29, and is expected to announce soon how strong the UK’s carbon target should be for 2035, before a UN deadline of February. Unep found that the G20 as a whole should cut its emissions 78 per cent by 2035.

“We need global mobilisation on a scale and pace never seen before — starting right now, before the next round of climate pledges — or the 1.5C goal will soon be dead and well below 2C will take its place in the intensive care unit,” said Inger Andersen, executive director at Unep.

Britain’s existing UN goal for 2030 is for a 68 per cent reduction. On Friday the government’s advisers, the Climate Change Committee, will issue their advice on how steep the cut should be.

[Vesper 30,224]

Minimum wage to rise by more than 6% in budget

https://www.thetimes.com/uk/politics/article/minimum-wage-to-rise-6-percent-uk-budget-dnj87k0wz

Ministers promised to “raise the floor” on wages and ultimately want parity for 18 to 20-year-olds

MONKEY BUSINESS IMAGES/GETTY IMAGES

 

More than a million low-paid workers will get a pay rise of more than 6 per cent next year as the minimum wage is increased at the budget.

Rachel Reeves, the chancellor, is due to announce an increase that is well above inflation and even higher than predicted last month.

Younger workers will get an even bigger increase as ministers say that 18 to 20-year-olds should eventually be paid the same as older workers.

While ministers are expected to herald good news for “working people”, businesses have warned of the impact of a rise that is expected to be announced alongside an increase in the national insurance contributions they must pay on wages.

About 1.6 million people receive the “national living wage” of £11.44 an hour, the minimum wage for over-21s. It will rise to more than £12.12 after ministers promised to “raise the floor” on wages.

Ministers have told the Low Pay Commission that the national living wage must not drop below two thirds of median earnings. This was a target set by the Conservatives and achieved this year after almost a decade of above-inflation increases, but ministers have signalled they want to go further to “boost low earnings”.

Last month the commission said that it expected to recommend an increase of 5.8 per cent, taking the living wage from age 21 to £12.10, but said it strong earnings growth could lead to a higher recommendation.

A government source said that the final figure was now more than 6 per cent, suggesting a new rate closer to £12.20.

Workers aged 18 to 20 can legally be paid a lower rate of £8.60 an hour but ministers want a “single adult rate” and Reeves is expected to announce a bigger increase for younger staff to get closer to the over-21 rate.

Angela Rayner, the deputy prime minister, has also told the commission to recommend an increase that “takes into account the cost of living”, but at a time when inflation has fallen close to 2 per cent, analysts do not expect that to significantly impact its recommendations this year.

Nye Cominetti, the principal economist at the Resolution Foundation, said: “Millions of low earners are set for good news in the budget when the chancellor announces the latest rise in the minimum wage”.

He said that government plans to were “actually less ambitious than the previous government’s record” after years where the minimum wage has increased by up to 10 per cent, saying “business should be used to the minimum wage rising at least in line with median pay, which is what we expect to happen.”

But Cominetti added: “A bigger surprise is the expected increase in employer national insurance contributions. As a result of the two together, some businesses will legitimately say that their wage costs have gone up quite a bit as a result of this budget.”

Tina McKenzie of the Federation of Small Businesses said: “It is businesses that pay people’s wages, plus all the tax government charges on top, which must be factored in when deciding on the Living Wage rate.”

She said an increase “must be accompanied with powerful government measures to help small businesses create and sustain jobs”, calling for more generous tax breaks for small employers facing “difficult choices” to cope with rising staff costs.

But Paul Nowak, general secretary of the TUC, said that experts on the commission “clearly believe that employers can absorb the rise”, and added: “At a time when the cost of living is still very high the lowest paid would really benefit from a decent increase in the minimum wage. We know that low-paid workers spend more of their cash in their local economies. So any increase in their spending power will benefit local firms too.”

He added: “Every time the minimum wage goes up there are some voices who predict this will drive up unemployment. Every time they are wrong.”

Edited October 29, 2024 by Vesper

[Vesper 30,224]

 

The Trends I’m Watching During Election Week (Part 1)

Examining the factors that will tell the story of this election.

https://www.liberalpatriot.com/p/the-trends-im-watching-during-election

One week from today, we could very well know who the next president of the United States will be, though the final result may not be known for a few days. In the weeks that follow, pundits, operatives, and analysts alike will be pouring over the data to discern what the “story” of the election was. More partisan types will likely be looking for ways to spin the outcome in their favor, especially those on the winning side.

To help better focus these conversations on relevant considerations, I want to share some questions I’ll be seeking to answer as the results become clearer and historical trends I’ll be comparing this year’s results against. Fair warning: there are many! So below I’ll offer the first bunch, and next Monday, before Election Day, we’ll post the second half of them. After we have results and other election data, I will come back to these questions and see if we can answer them.

The gender gap among young voters

Democrats have long held an advantage among voters aged 18–29. They have won these voters in presidential elections by at least nine points all but once since 19921 and by at least 20 points since 2008. What’s more: in contrast to other age groups, both young women and young men have supported Democratic candidates. In 2020, 18–29-year-old men were the only male age cohort to support Joe Biden, doing so by an 11-point margin, 52–41 (young women, meanwhile, supported Biden by a much larger 35 points, 67–32).

There are some signs that this dynamic could be changing. According New York Times/Siena College polling, Donald Trump now leads Harris among young men, and it’s not particularly close: 58–37. But Harris’s lead among young women is even wider: 67–28 (this is also wider than Biden’s advantage was four years ago). If this polling is accurate, it’s unclear how a growing divide like this might impact the final results, but suffice it to say that it’s a wild card.

However, it’s not clear that Republicans do have an advantage among young men. The latest Harvard IOP poll of young voters found that in fact Harris continues leading with this cohort by 10 points. Moreover, the younger men who support Trump also appeared to be less certain that they would vote, while Harris held a 17-point lead among likely voters.

Key questions:

• Which survey do the early exit polls suggest was more accurate: polling from the Times’ or Harvard?

• Does the data show both young men and women moving further from their 2020 baselines or only one of those groups?

• Does a potential growing gender gap extend to other age brackets as well?

Racial depolarization

A trend we at TLP have been watching for some time has been the rightward movement of nonwhite voters. For example, between 2016 and 2020, Hispanic, a Democratic-leaning group, swung toward Trump by 12 points. This cycle, Hispanics as well as black Americans appear to be moving even further rightward. The latest polling crosstab averages from both the Cook Political Report and Democratic pollster Adam Carlson show that Harris’s advantage with black voters is roughly 19–20 points below Biden’s, and with Hispanics she is 8–11 points behind. These swings could make a big difference in battleground states where the final margin is only a point or two.

Meanwhile, though, there have been signs that Harris is making up ground among white Americans, who have traditionally voted more Republican than Democratic and constitute an outsized share of the electorate (72 percent in 2020). This includes white non-college voters, who are overrepresented in swing states like Michigan, Wisconsin, and Pennsylvania as well as their college-educated peers. If Harris outperforms Biden with white voters, it will mark the second straight election in which the Democratic nominee has done better than their predecessor.

One thing to watch is whether the nonwhite voters moving in Trump’s direction are are among those who are slightly less likely to vote. As the Times’ Cohn has observed previously, Trump’s support with these voters may be coming from those who are less politically engaged. Extensive reporting has also indicated that Trump’s ground game and turnout operation are wanting, which means he may have trouble turning his poll support into actual votes. So it’s unclear whether the extent to which his gains with these groups will ultimately materialize—or the impact it will have if they do.

Key questions:

• Do the polls showing Trump’s substantial gains with nonwhite voters square with the final results?

• If Trump does make further gains with nonwhite voters relative to 2020, do they make the difference in any state?

• If Harris loses ground with black or Hispanic voters but improves with white voters, is that enough to offset the former losses?

The growing class divide

Another topic we have covered extensively is how the rise of educational polarization has come to reshape the two parties’ coalitions, with Democrats increasingly becoming the party of the college-educated class while the Republicans earn more votes from working-class voters. After Obama won non-college voters by four points in 2012, they swung to Trump in 2016, backing him by six. They did so again by roughly the same margin in 2020. College-educated voters have moved in the opposite direction, voting Democratic at the presidential level by margins of four (2012), 15 (2016), and 18 (2020) points. This cycle, both college- and non-college-educated voters have moved rightward relative to four years ago by roughly 2–3 points, a sign that this gap isn’t likely to shrink much, if at all.

There appear to be similar movements happening when looking at household income. Between 2012 and 2020, voters whose median earnings below $50,000 annually swung rightward by 12 points, going from backing Obama by 22 to supporting Biden by just 10. At the same time, the wealthiest Americans (those earning at least $100,000) have moved toward Democrats, going from a Romney +10 group to narrowly breaking for Democrats by two points in each of the previous two elections. The latest polling averages show Harris doing about the same as Biden among high income earners but underperforming among low-income households by 10–12 points.2

Finally, one other constituency whose performance may offer more context to the picture of class in America is union households. For decades, union voters have been strongly Democratic, but since 1992, that support (and the group’s vote share) have steadily declined. After Bill Clinton won them by around 30 points, they backed Obama by roughly 19. Hillary Clinton then carried them by only nine before Biden, who regularly touted his support for organized labor, bounced back, taking them by 15 points. The picture this cycle is a little murky, with little pre-election polling on this group. But the party’s struggles with this core constituency are undeniable.

If these trends hold on Election Day, it may be bad news for the Democrats. Working-class and union voters are overrepresented in several pivotal states, while, college-educated and higher-income voters both represent small (though reliable) shares of the electorate.

Key questions:

• Will recent class trends continue to change the makeup of the two parties’ coalitions, or will one or both claw back ground they have lost?

• Does Harris hold the line with union voters, or was the Teamsters’ internal polling a canary in the coal mine for further rightward drift?

• Is there a racial component to the class divide? (E.g., Do white working-class voters swing left but non-white ones swing right, or not?)

The impact of geography

In addition to educational attainment, the other growing fault line in American politics has been the politics of place—namely, whether you live in an urban, rural, or suburban area. These communities tend to be deeply Democratic, deeply Republican, and a mix of both, respectively. However, what’s become more interesting in the last few elections is the directions in which each one is trending.

Though urban areas across America are reliably Democratic, almost without exception, the party has seen some erosion of support in these places. As I wrote in my inaugural TLP piece last year, major cities in key swing states have experienced a decline in voter turnout as well as Democratic support. To be sure, they continue to vote blue by huge margins, but even these small losses matter. For example, in 2016, had Hillary Clinton simply matched Obama’s vote totals in Detroit and Milwaukee, she would have carried Michigan and Wisconsin. The latest polling averages indicate that Democrats may be losing further ground in urban America, with Harris underperforming Biden by nearly 12 points.

Meanwhile, much of rural America has become extremely hostile territory for Democrats over the previous decade. In 2008, John McCain only won rural counties by about eight points. By 2020, Trump carried them by 23. Democrats’ image in this part of the country is a longstanding problem. However, recent polling averages indicate that the party might be bouncing back.3 Carlson’s tracker has shown Harris over-performing Biden’s 2020 margins every month, usually by around seven or eight points. If her urban losses do materialize, gains in rural America could help her stay competitive.

Finally, suburban areas are likely where this election will be won or lost, just as they have in most elections. Since at least 2008, suburban voters have composed a whopping 55 percent of the electorate, and as they have gone, so too has the election. The latest polling averages show Harris narrowly winning them this time around by about three points. Though this might sound like good news for her, it represents a six-point decline from Biden’s 2020 performance.

Key questions:

• Are the polling crosstab averages showing Trump gaining in urban areas accurate? And if he eats into Harris’s margins in places like Detroit or Milwaukee, does she make up ground elsewhere?

• Does Harris do better than Biden in rural communities? If so, is there anything we can glean from the ones where she achieves this? (E.g., have they grown in population since the COVID pandemic?)

• If Harris carries the suburbs but by a lower margin than Biden did, is that enough to win?

 

1

The lone exception was the 2000 election, when Democrats only won them by two.

2

Averages for middle income earners are not readily available, though this is historically a Republican-leaning group.

3

Interestingly, this improvement began while Biden was still in the race, which may serve to counter claims that picking Tim Walz as her running mate helped Harris bounce back.

 

Edited October 29, 2024 by Vesper

[cosmicway 1,333]

I wonder if all those opinion polls are based on the swing theory or not.
The swing theory is essentially a variance reduction technique.
What is it ?
It is we ask the participants not only which way they are going to vote but also which way they voted last time.
Then we work with ratios instead of sums.
So if the accuracy without swing measurement is ±2%, now it becomes ±1.5% or ±1%.
Are they doing that ?
You could n't apply swing theory in the brexit referendum - difficult. But in general elections we can.

 

[Vesper 30,224]

The forces of chance

Social scientists cling to simple models of reality – with disastrous results. Instead they must embrace chaos theory

https://aeon.co/essays/without-chaos-theory-social-science-will-never-understand-the-world

Bockscar en route to Nagasaki, 9 August 1945. US Air Force photo

The social world doesn’t work how we pretend it does. Too often, we are led to believe it is a structured, ordered system defined by clear rules and patterns. The economy, apparently, runs on supply-and-demand curves. Politics is a science. Even human beliefs can be charted, plotted, graphed. And using the right regression we can tame even the most baffling elements of the human condition. Within this dominant, hubristic paradigm of social science, our world is treated as one that can be understood, controlled and bent to our whims. It can’t.

Our history has been an endless but futile struggle to impose order, certainty and rationality onto a Universe defined by disorder, chance and chaos. And, in the 21st century, this tendency seems to be only increasing as calamities in the social world become more unpredictable. From 9/11 to the financial crisis, the Arab Spring to the rise of populism, and from a global pandemic to devastating wars, our modern world feels more prone to disastrous ‘shocks’ than ever before. Though we’ve got mountains of data and sophisticated models, we haven’t gotten much better at figuring out what looms around the corner. Social science has utterly failed to anticipate these bolts from the blue. In fact, most rigorous attempts to understand the social world simply ignore its chaotic quality – writing it off as ‘noise’ – so we can cram our complex reality into neater, tidier models. But when you peer closer at the underlying nature of causality, it becomes impossible to ignore the role of flukes and chance events. Shouldn’t our social models take chaos more seriously?

The problem is that social scientists don’t seem to know how to incorporate the nonlinearity of chaos. For how can disciplines such as psychology, sociology, economics and political science anticipate the world-changing effects of something as small as one consequential day of sightseeing or as ephemeral as passing clouds?

 

On 30 October 1926, Henry and Mabel Stimson stepped off a steam train in Kyoto, Japan and set in motion an unbroken chain of events that, two decades later, led to the deaths of 140,000 people in a city more than 300 km away.

The American couple began their short holiday in Japan’s former imperial capital by walking from the railway yard to their room at the nearby Miyako Hotel. It was autumn. The maples had turned crimson, and the ginkgo trees had burst into a golden shade of yellow. Henry chronicled a ‘beautiful day devoted to sightseeing’ in his diary.

Nineteen years later, he had become the Unites States Secretary of War, the chief civilian overseeing military operations in the Second World War, and would soon join a clandestine committee of soldiers and scientists tasked with deciding how to use the first atomic bomb. One Japanese city ticked several boxes: the former imperial capital. The Target Committee agreed that Kyoto must be destroyed. They drew up a tactical bombing map and decided to aim for the city’s railway yard, just around the corner from the Miyako Hotel where the Stimsons had stayed in 1926.

Stimson pleaded with the president Harry Truman not to bomb Kyoto. He sent cables in protest. The generals began referring to Kyoto as Stimson’s ‘pet city’. Eventually, Truman acquiesced, removing Kyoto from the list of targets. On 6 August 1945, Hiroshima was bombed instead.

If such random events could lead to so many deaths, how are we to predict the fates of human society?

The next atomic bomb was intended for Kokura, a city at the tip of Japan’s southern island of Kyushu. On the morning of 9 August, three days after Hiroshima was destroyed, six US B-29 bombers were launched, including the strike plane Bockscar. Around 10:45am, Bockscar prepared to release its payload. But, according to the flight log, the target ‘was obscured by heavy ground haze and smoke’. The crew decided not to risk accidentally dropping the atomic bomb in the wrong place.

Bockscar then headed for the secondary target, Nagasaki. But it, too, was obscured. Running low on fuel, the plane prepared to return to base, but a momentary break in the clouds gave the bombardier a clear view of the city. Unbeknown to anyone below, Nagasaki was bombed due to passing clouds over Kokura. To this day, the Japanese refer to ‘Kokura’s luck’ when one unknowingly escapes disaster.

Roughly 200,000 people died in the attacks on Hiroshima and Nagasaki – and not Kyoto and Kokura – largely due to one couple’s vacation two decades earlier and some passing clouds. But if such random events could lead to so many deaths and change the direction of a globally destructive war, how are we to understand or predict the fates of human society? Where, in the models of social change, are we supposed to chart the variables for travel itineraries and clouds?

In the 1970s, the British mathematician George Box quipped that ‘all models are wrong, but some are useful’. But today, many of the models we use to describe our social world are neither right nor useful. There is a better way. And it doesn’t entail a futile search for regular patterns in the maddening complexity of life. Instead, it involves learning to navigate the chaos of our social worlds.

Before the scientific revolution, humans had few ways of understanding why things happened to them. ‘Why did that storm sink our fleet?’ was a question that could be answered only with reference to gods or, later, to God. Then, in the 17th century, Isaac Newton introduced a framework where such events could be explained through natural laws. With the discovery of gravity, science turned the previously mysterious workings of the physical Universe – the changing of the tides, celestial movements, falling objects – into problems that could be investigated. Newtonian physics helped push human ideas about causality from the unknowable into the merely unknown. A world ruled by gods is fundamentally unknowable to mere mortals, but, with Newton’s equations, it became possible to imagine that our ignorance was temporary. Uncertainty could be slain with intellectual ingenuity. In 1814, for example, the French scholar Pierre-Simon Laplace published an essay that imagined the possible implications of Newton’s ideas on the limits of knowledge. Laplace used the concept of an all-knowing demon, a hypothetical entity who always knew the positions and velocities of every particle in Newton’s deterministic universe. Using this power, Laplace’s demon could process the full enormity of reality and see the future as clearly as the past.

These ideas changed how we conceived of the fundamental nature of our world. If we are the playthings of gods, then the world is fundamentally and unavoidably unruly, swayed by unseen machinations, the whims of trickster deities and their seemingly random shocks unleashed like bolts of lightning from above. But if equations are our true lords, then the world is defined by an elegant, albeit elusive, order. Unlocking the secrets of those equations would be the key to taming what only seemed unruly due to our human ignorance. And in that world of equations, reality would inevitably converge toward a series of general laws. As scientific progress advanced in the 19th and 20th centuries, Laplace’s demon became increasingly plausible. Better equations, perhaps, could lead to godlike foresight.

‘Small differences in the initial conditions produce very great ones in the final phenomena’

The search for patterns, rules and laws wasn’t limited only to the realm of physics. In biology, Darwinian principles provided a novel guide to the rise and fall of species: evolution by natural selection acted like an ordered guardrail for all life. And as the successes of the natural sciences spread, scholars who studied the dynamics of culture began to believe that the rules of biology and physics could also be used to describe the patterns of human behaviour. If there was a theoretical law for something as mysterious as gravity, perhaps there were similar rules that could be applied to the mysteries of human behaviour, too? One scholar who put such an idea in motion was the French social theorist Henri de Saint-Simon. Believing that scientific laws underpinned social behaviour, Saint-Simon proposed a more systematic, scientific approach to social organisation and governance. Social reform, he believed, would flow inexorably from scientific research. The French philosopher Auguste Comte, a contemporary of Saint-Simon and founder of the discipline of sociology, even referred to the study of human societies as ‘social physics’. It was only a matter of time, it seemed, for the French Revolution to be understood as plainly as the revolutions of the planets.

But there were wrinkles in this world of measurement and prediction, which the French mathematician Henri Poincaré anticipated in 1908: ‘it may happen that small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter.’

The first of those wrinkles was discovered by the US mathematician and meteorologist Edward Norton Lorenz. Born in 1917, Lorenz was fascinated by the weather as a young boy, but he left that interest behind in the mid-1930s when he began studying mathematics at Harvard University. During these studies, the Second World War broke out and Lorenz spotted a flyer recruiting for a weather forecasting unit. He jumped at the chance to return to his childhood fascination. As the war neared its end in 1945, Lorenz began forecasting cloud cover for bombing runs over Japan. Through this work, he started to understand the severe limitations of weather prediction – forecasting was not an exact science. And so, after the war, he returned to his mathematical studies, working on predictive weather models in the hope of giving humanity a means of more accurately glimpsing the future.

One day in 1961, while modelling the weather using a small set of variables on a simple, premodern computer, Lorenz decided to save time by restarting a simulation that had been stopped halfway through. The same simulation had been run previously, and Lorenz was running it again as part of his research. He printed the variables out, then programmed the numbers back into the machine and waited for the simulation to unfold as it had before.

The control panel on an LGP-30 computer, similar to that used by Edward Norton Lorenz. Courtesy Wikipedia

At first, everything looked identical, but over time the weather patterns began to diverge dramatically. He assumed there must have been an error with the computer. After much chin-scratching and scowling over the data, Lorenz made a discovery that forever upended our understanding of systemic change. He realised that the computer printouts he had used to run the simulation were truncating the values after three decimal points: a value of 0.506127 would be printed as 0.506. His astonishing revelation was that the tiniest measurement differences – seemingly infinitesimal, meaningless rounding errors – could radically change how a weather system evolved over time. Tempests could emerge from the sixth decimal point. If Laplace’s demon were to exist, his measurements couldn’t just be nearly perfect; they would need to be flawless. Any error, even a trillionth of a percentage point off on any part of the system, would eventually make any predictions about the future futile. Lorenz had discovered chaos theory.

 

The Lorenz attractor is the iconic representation of chaos theory. Courtesy Wikipedia

The core principle of the theory is this: chaotic systems are highly sensitive to initial conditions. That means these systems are fully deterministic but also utterly unpredictable. As Poincaré had anticipated in 1908, small changes in conditions can produce enormous errors. By demonstrating this sensitivity, Lorenz proved Poincaré right.

Chaos theory, to this day, explains why our weather forecasts remain useless beyond a week or two. To predict meteorological changes accurately, we, like Laplace’s demon, would have to be perfect in our understanding of weather systems, and – no matter how advanced our supercomputers may seem – we never will be. Confidence in a predictable future, therefore, is the province of charlatans and fools; or, as the US theologian Pema Chödrön put it: ‘If you’re invested in security and certainty, you are on the wrong planet.’

Most of the genomic tweaks driving evolution are fundamentally arbitrary, even accidental

The second wrinkle in our conception of an ordered, certain world came from the discoveries of quantum mechanics that began in the early 20th century. Seemingly irreducible randomness was discovered in bewildering quantum equations, shifting the dominant scientific conception of our world from determinism to indeterminism (though some interpretations of quantum physics arguably remain compatible with a deterministic universe, such as the ‘many-worlds’ interpretation, Bohmian mechanics, also known as the ‘pilot-wave’ model, and the less prominent theory of superdeterminism). Scientific breakthroughs in quantum physics showed that the unruly nature of the Universe could not be fully explained by either gods or Newtonian physics. The world may be defined, at least in part, by equations that yield inexplicable randomness. And it is not just a partly random world, either. It is startlingly arbitrary.

Consider, for example, the seemingly ordered progression of Darwinian evolution. Alfred Russel Wallace, who discovered evolution around the same time as Charles Darwin, believed that the principles of life had a structured purpose – they were teleological. Darwin was more sceptical. But neither thinker could anticipate just how arbitrary much of evolutionary change would turn out to be.

In the 1960s, the Japanese evolutionary biologist Motoo Kimura discovered that most of the genomic tweaks driving evolution at the molecular level are neither helpful nor harmful. They are fundamentally arbitrary, even accidental. Kimura called this the ‘neutral theory of molecular evolution’. Other scientists noticed it, too, whether they were studying viruses, fruit flies, blind mole rats, or mice. Evidence began to accumulate that many evolutionary changes in species weren’t driven by structured or ordered selection pressures. They were driven by the forces of chance.

The US biologist Richard Lenski’s elegant long-term evolution experiment, which has been running since 1988, demonstrated that important adaptations that help a species (such as E coli) thrive can emerge after a chain of broadly meaningless mutations. If any one of those haphazard and seemingly ‘useless’ tweaks hadn’t occurred, the later beneficial adaptation wouldn’t have been possible. Sometimes, there’s no clear reason, no clear pattern. Sometimes, things just happen.

E coli populations from Richard Lenski’s long-term evolution experiment, 25 June 2008. Courtesy Wikipedia

Kimura’s own life was an illustration of the arbitrary forces that govern our world. In 1944, he enrolled at Kyoto University, hoping to continue his intellectual pursuits while avoiding conscription into the Japanese military. If Henry Stimson had chosen a different destination for his sightseeing vacation in 1926, Kimura and his fellow students would likely have been incinerated in a blinding flash of atomic light.

How can we make sense of social change when consequential shifts often arise from chaos? This is the untameable bane of social science, a field that tries to detect patterns and assert control over the most unruly, chaotic system that exists in the known Universe: 8 billion interacting human brains embedded in a constantly changing world. While we search for order and patterns, we spend less time focused on an obvious but consequential truth. Flukes matter.

Though some scholars in the 19th century, such as the English philosopher John Stuart Mill and his intellectual descendants, believed there were laws governing human behaviour, social science was swiftly disabused of the notion that a straightforward social physics was possible. Instead, most social scientists have aimed toward what the US sociologist Robert K Merton called ‘middle-range theory’, in which researchers hope to identify regularities and patterns in certain smaller realms that can perhaps later be stitched together to derive the broader theoretical underpinnings of human society. Though some social scientists are sceptical that such broader theoretical underpinnings exist, the most common approach to social science is to use empirical data from the past to tease out ordered patterns that point to stable relationships between causes and effects. Which variables best correlate with the onset of civil wars? Which economic indicators offer the most accurate early warning signs of recessions? What causes democracy?

Social science became dominated by one computational tool above all others: linear regressions

In the mid-20th century, researchers no longer sought the social equivalent of a physical law (like gravity), but they still looked for ways of deriving clear-cut patterns within the social world. What limited this ability was technology. Just as Lorenz was constrained by the available technology when forecasting weather in the Pacific theatre of the Second World War, so too were social scientists constrained by a lack of computing power. This changed in the 1980s and ’90s, when cheap and sophisticated computers became new tools for understanding social worlds. Suddenly, social scientists – sociologists, economists, psychologists or political scientists – could take a large number of variables and plug them into statistical software packages such as SPSS and Stata, or programming languages such as R. Complex equations would then process these data points, finding the ‘line of best fit’ using a ‘linear regression’, to help explain how groups of humans change over time. A quantitative revolution was born.

By the 2000s, area studies specialists who had previously done their research by trekking across the globe and embedding themselves in specific cultures were largely supplanted by office-bound data junkies who could manipulate numbers and offer evidence of hidden relationships that were obscured prior to the rise of sophisticated numerical analysis. In the process, social science became dominated by one computational tool above all others: linear regressions. To help explain social change, this tool uses past data to try to understand the relationships between variables. A regression produces a simplified equation that tries to fit the cluster of real-world datapoints, while ‘controlling’ for potential confounders, in the hopes of identifying which variables drive change. Using this tool, researchers can feed a model with a seemingly endless string of data as they attempt to answer difficult questions. Does oil hinder democracy? How much does poverty affect political violence? What are the social determinants of crime? With the right data and a linear regression, researchers can plausibly identify patterns with defensible, data-driven equations. This is how much of our knowledge about social systems is currently produced. There is just one glaring problem: our social world isn’t linear. It’s chaotic.

Linear regressions rely on several assumptions about human society that are obviously incorrect. In a linear equation, the size of a cause is proportionate to the size of its effect. That’s not how social change works. Consider, for example, that the assassination of one man, Archduke Franz Ferdinand, triggered the First World War, causing roughly 40 million casualties. Or think of the single vegetable vendor who lit himself on fire in central Tunisia in late 2010, sparking events that led to the Syrian civil war, resulting in hundreds of thousands of deaths and the fall of several authoritarian regimes. More recently, a bullet narrowly missed killing Donald Trump in Pennsylvania: if the tiniest gust of wind or a single bodily twitch had altered its trajectory, the 21st century would have been set on a different path. This exemplifies chaos theory in the social world, where tiny changes in initial conditions can transform countless human fates.

Another glaring problem is that most linear regressions assume that a cause-and-effect relationship is stable across time. But our social world is constantly in flux. While baking soda and vinegar will always produce a fizz, no matter where or when you mix them together, a vegetable vendor lighting himself on fire will rarely produce regional upheaval. Likewise, many archdukes have died – only one has ever triggered a world war.

Timing matters, too. Even if the exact same mutation in the exact same coronavirus had broken out in the exact same place, the economic effects and social implications of the ensuing pandemic would have been drastically different if it had struck in 1990 instead of 2020. How would millions of people have worked from home without the internet? Pandemics, like many complex social phenomena, are not uniformly governed by stable, ordered patterns. This is a principle of social reality known to economists as ‘nonstationarity’: causal dynamics can change as they are being measured. Social models often deal with this problem by ignoring it.

Most linear regressions are also ineffective at modelling two fundamental facets of our world: sequencing, the critical order in which events take place; and space, the specific physical geography in which those events occur. The overarching explanations offered by linear regression ignore the order in which things happen, and though that approach can sometimes work, at other times the order of events is crucial. Try adding flour after you bake a cake and see what happens. Similarly, linear regressions cannot easily incorporate complex features of our physical geography or capture the ways that humans navigate through space. Social models tend to conceptualise changes at the macro level, through economic output figures or democracy scores, rather than seeing diverse, adaptive individuals who are constantly interacting on specific terrain. Life looks very different for people living in Antarctica compared with people living in downtown Mumbai or the Andes or outback Australia.

We produce too many models that are often wrong and rarely useful. But there is a better way

By smoothing over near-infinite complexity, linear regressions make our nonlinear world appear to follow the comforting progression of a single ordered line. This is a conjuring trick. And to complete it successfully, scientists need to purge whatever doesn’t fit. They need to detect the ‘signal’ and delete the ‘noise’. But in chaotic systems, the noise matters. Do we really care that 99.8 per cent of the Titanic’s voyage went off without a hitch, or that Abraham Lincoln enjoyed most of the play before he was shot?

The deeply flawed assumptions of social modelling do not persist because economists and political scientists are idiots, but rather because the dominant tool for answering social questions has not been meaningfully updated for decades. It is true that some significant improvements have been made since the 1990s. We now have more careful data analysis, better accounting for systematic bias, and more sophisticated methods for inferring causality, as well as new approaches, such as experiments that use randomised control trials. However, these approaches can’t solve many of the lingering problems of tackling complexity and chaos. For example, how would you ethically run an experiment to determine which factors definitively provoke civil wars? And how do you know that an experiment in one place and time would produce a similar result a year later in a different part of the world?

These drawbacks have meant that, despite tremendous innovations in technology, linear regressions remain the outdated king of social research. As the US economist J Doyne Farmer puts it in his book Making Sense of Chaos (2024): ‘The core assumptions of mainstream economics don’t match reality, and the methods based on them don’t scale well from small problems to big problems.’ For Farmer, these methods are primarily limited by technology. They have been, he writes, ‘unable to take full advantage of the huge advances in data and technology.’

The drawbacks also mean that social research often has poor predictive power. And, as a result, social science doesn’t even really try to make predictions. In 2022, Mark Verhagen, a research fellow at the University of Oxford, examined a decade of articles in the top academic journals in a variety of disciplines. Only 12 articles out of 2,414 tried to make predictions in the American Economic Review. For the top political science journal, American Political Science Review, the figure was 4 out of 743. And in the American Journal of Sociology, not a single article made a concrete prediction. This has yielded the bizarre dynamic that many social science models can never be definitively falsified, so some deeply flawed theories linger on indefinitely as zombie ideas that refuse to die.

A core purpose of social science research is to prevent avoidable problems and improve human prosperity. Surely that requires more researchers to make predictions about the world at some point – even if chaos theory shows that those claims are likely to be inaccurate.

We produce too many models that are often wrong and rarely useful. But there is a better way. And it will come from synthesising lessons from fields that social scientists have mostly ignored.

Chaos theory emerged in the 1960s and, in the following decades, mathematical physicists such as David Ruelle and Philip Anderson recognised the significance of Lorenz’s insights for our understanding of real-world dynamical systems. As these ideas spread, misfit thinkers from an array of disciplines began to coalesce around a new way of thinking that was at odds with the mainstream conventions in their own fields. They called it ‘complexity’ or ‘complex systems’ research. For these early thinkers, Mecca was the Santa Fe Institute in New Mexico, not far from the sagebrush-dotted hills where the atomic bomb was born. But unlike Mecca, the Santa Fe Institute did not become the hub of a global movement.

Public interest in chaos and complexity surged in the 1980s and ’90s with the publication of James Gleick’s popular science book Chaos (1987), and a prominent reference from Jeff Goldblum’s character in the film Jurassic Park (1993). ‘The shorthand is the butterfly effect,’ he says, when asked to explain chaos theory. ‘A butterfly can flap its wings in Peking and in Central Park you get rain instead of sunshine.’ But aside from a few fringe thinkers who broke free of disciplinary silos, social science responded to the complexity craze mostly with a shrug. This was a profound error, which has contributed to our flawed understanding of some of the most basic questions about society. Taking chaos and complexity seriously requires a fresh approach.

One alternative to linear regressions is agent-based modelling, a kind of virtual experiment in which computers simulate the behaviour of individual people within a society. This tool allows researchers to see how individual actions, with their own motivations, come together to create larger social patterns. Agent-based modelling has been effective at solving problems that involve relatively straightforward decision-making, such as flows of car traffic or the spread of disease during a pandemic. As these models improve, with advances in computational power, they will inevitably continue to yield actionable insights for more complex social domains. Crucially, agent-based models can capture nonlinear dynamics and emergent phenomena, and reveal unexpected bottlenecks or tipping points that would otherwise go unnoticed. They might allow us to better imagine possible worlds, not just measure patterns from the past. They offer a powerful but underused tool in future-oriented social research involving complex systems.

The study of resilience in nonlinear systems would drastically improve our ability to avert avoidable catastrophes

Additionally, social scientists could incorporate chaotic dynamics by acknowledging the limits of seeking regularities and patterns. Instead, they might try to anticipate and identify systems on the brink, near a consequential tipping point – systems that could be set off by a disgruntled vegetable vendor or triggered by a murdered archduke. The study of ‘self-organised criticality’ in physics and complexity science could help social scientists make sense of this kind of fragility. Proposed by the physicists Per Bak, Chao Tang and Kurt Wiesenfeld, the concept offers a useful analogy for social systems that may disastrously collapse. When a system organises itself toward a critical state, a single fluke could cause the system to change abruptly. By analogy, modern trade networks race toward an optimised but fragile state: a single gust of wind can twist one boat sideways and cause billions of dollars in economic damage, as happened in 2021 when a ship blocked the Suez Canal.

The theory of self-organised criticality was based on the sandpile model, which could be used to evaluate how and why cascades or avalanches occur within systems. If you add grains of sand, one at a time, to a sandpile, eventually, a single grain of sand can cause an avalanche. But that collapse becomes more likely as the sandpile soars to its limit. A social sandpile model could provide a useful intellectual framework for analysing the resilience of complex social systems. Someone lighting themselves on fire, God forbid, in Norway is unlikely to spark a civil war or regime collapse. That is because the Norwegian sandpile is lower, less stretched to its limit, and therefore less prone to unexpected cascades and tipping points than the towering sandpile that led to the Arab Spring.

There are other lessons for social research to be learned from nonlinear evaluations of ecological breakdown. In biology, for instance, the theory of ‘critical slowing down’ predicts that systems near a tipping point – like a struggling coral reef that is being overrun with algae – will take longer to recover from small disturbances. This response seems to act as an early warning system for ecosystems on the brink of collapse.

Social scientists should be drawing on these innovations from complex systems and related fields of research rather than ignoring them. Better efforts to study resilience and fragility in nonlinear systems would drastically improve our ability to avert avoidable catastrophes. And yet, so much social research still chases the outdated dream of distilling the chaotic complexity of our world into a straightforward equation, a simple, ordered representation of a fundamentally disordered world.

When we try to explain our social world, we foolishly ignore the flukes. We imagine that the levers of social change and the gears of history are constrained, not chaotic. We cling to a stripped-down, storybook version of reality, hoping to discover stable patterns. When given the choice between complex uncertainty and comforting – but wrong – certainty, we too often choose comfort.

In truth, we live in an unruly world often governed by chaos. And in that world, the trajectory of our lives, our societies and our histories can forever be diverted by something as small as stepping off a steam train for a beautiful day of sightseeing, or as ephemeral as passing clouds.

Parts of this essay were adapted from Fluke: Chance, Chaos, and Why Everything We Do Matters (2024) by Brian Klaas.

 

[cosmicway 1,333]

In prediction theory there is a magic number.
The Shannon number - representing the total information count.
So your mulitparametric system is manipulated so as to maximize the Shannon number of the pre-posterior observations.
That's how it works.
Other models are unstable.
With many parameters computations become tediously slow - even with the fastest computers.

Edited October 29, 2024 by cosmicway

[Vesper 30,224]

8 minutes ago, cosmicway said:

I wonder if all those opinion polls are based on the swing theory or not.
The swing theory is essentially a variance reduction technique.
What is it ?
It is we ask the participants not only which way they are going to vote but also which way they voted last time.
Then we work with ratios instead of sums.
So if the accuracy without swing measurement is ±2%, now it becomes ±1.5% or ±1%.
Are they doing that ?
You could n't apply swing theory in the brexit referendum - difficult. But in general elections we can.

 

By introducing a secondary independent variable (and this goes for the common random numbers (CRN) variance reduction technique as well) you can potentially set up a negative correlation, thus increasing variation (dispersion) and the decreasing predictive accuracy of the data set.

[cosmicway 1,333]

51 minutes ago, Vesper said:

By introducing a secondary independent variable (and this goes for the common random numbers (CRN) variance reduction technique as well) you can potentially set up a negative correlation, thus increasing variation (dispersion) and the decreasing predictive accuracy of the data set.

It is not independent.
Independent is toothpaste Colgate versus republicanism.
Swing theory reduces the variance.
Someone I know made huge money with brexit. What he observed was the Newcastle result, the first to be announced.
Newcastle voted remain but by a lot less than was expected in a preponderantly Labour constituenct.
I could n't follow because betfair is not allowed in Greece.

Also the late lamented Greek minister Akis Tsohatzopoulos (n.b. accused of economic crimes) was an expert in mathematical statistics
and by using swing theory he always predicted the exact result.

Edited October 29, 2024 by cosmicway

[Vesper 30,224]

Here is a partial list of RW, Republican push pollsters that flood the zone with bullshit polls, thus skewing agregator averages towards Trump and other Republican candidates (US House, US Senate, state Governor races, etc)

they VASTLY outnumber Democratic dodgy pollster (this election probably 25 to 50 to one)

the top 15  or so, especially the top 10 listed, are just relentless with deluge of RW skewed polls

    
Trafalgar Group

ActiVote

Redfield & Wilton Strategies   

Fabrizio, Lee & Associates

AtlasIntel

InsiderAdvantage

OnMessage

Patriot Polling

Remington Research Group

Cherry Communications

HarrisX

HighGround

RMG Research

Cygnal

McLaughlin & Associates    

Victory Insights

Targoz Market Research

The Tyson Group 

P2 Insights

SoCal Strategies

TIPP Insights

Spry Strategies

Peak Insights

Iron Light

Echelon Insights

Moore Information Group

Ascend Action

Clout Research

Normington, Petts & Associates

FM3 Research

Repass

Global Strategy Group

North Star Opinion Research

Fabrizio Ward