Author: VD

A Refutation, Reviewed

The first review of THE REFUTATION OF KANT has been posted.

A refutation of Kant has to do one of two things: produce a counterexample the system cannot deal with, or locate the move inside the system that doesn’t actually argue for what it concludes. The second part of Day’s Veriphysics does both, and the interlocking of the two halves is what makes the book hard to answer because every defense of one wing concedes ground on the other.

The argument worth focusing on is the Master Amphiboly, and Vox is right about it. The “Thing-in-itself” runs two readings across a single word: that every cognizer is shaped by its apparatus, and that no feature of reality is in principle accessible to human cognition. The first is trivially true and Kant argues for it. The second is the load-bearing claim of the whole edifice and Kant never argues for it once, and instead moves to it under cover of the first. Once you see the slide, you can’t unsee it. Neptune is the cleanest empirical counterexample, though not the only one: Le Verrier worked an inverse problem through pure formalism and Galle confirmed the prediction within a degree, and the positron case is structurally identical: Dirac’s equation required it before anyone looked. If formal cognition cannot in principle identify features of reality not already given in experience, these events did not happen.

The mathematical half is harder to evade and simpler to state. Construction in Kant’s sense was tied to constructibility, which was already a problem with the irrationals in 1781 and decisively broken by Cantor a century later. The available retreat is to recast synthetic a priori as analytic, which costs the system the work it was built to do. The pincer is real and no version of Kant survives both jaws. One place worth pressing further is that the amphiboly used is portable. The slide from an apparatus-relative epistemic limit to an ontological claim about reality runs through Hume on causation, through Wittgenstein on private language, and through most of the strong-program science studies literature. Naming it generalizes the refutation.

Worth reading. Excellent work by Day

That is an intriguing observation about the potential portability of the Master Amphiboly. I shall have to examine the situation and see just how far the intellectual rot goes.

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Report: Iran Has Nukes

81 years of global fear, and 40+ years of neocon warnings, threats, and hissy fits may have just gone up in smoke during a single telephone call:

I have not been given access to NSA Sigint, but I have confirmed that the phone call last week between Iranian President Pezeshkian and Pakistani Prime Minister Shariff was over a non-secure line. I am reliably informed that this was done deliberately by the Iranians and Pakistanis — i.e., the Iranians and Pakistanis were counting on the Americans and the Israelis to be listening in. The key part of the conversation between Pezeshkian and Shariff was this:

President Masoud Pezeshkian communicated a formally structured, three-step strategic ultimatum if US strikes continued:

  1. Immediate Withdrawal from the ongoing nuclear peace talks.
  2. Total Abandonment of the prospective Nuclear Treaty framework.
  3. The Detonation of a Nuclear Device on Iranian soil—executed not as a weapon of war, but as an undeniable demonstration of sovereign capability and ultimate control over the escalation ladder.

When Marco Rubio was called an hour or so later by Pakistan’s Foreign Minister, Ishaq Dar, and received the same message, the White House knew that the information was legitimate. While the US intelligence community probably cannot confirm that Iran actually does have a functioning nuke, the Pakistanis believe the Iranians do. The intercepted chat between Pezeshkian and Shariff, followed by Rubio’s conversation with Ishaq Dar, convinced Trump and his advisors that Iran was not making a hollow threat.

Now we know why there has been a dramatic change in Trump’s rhetoric towards Iran… Hell, he downplayed yesterday’s missile dust up in the Persian Gulf, which left Kuwait’s International Airport on fire from an errant PAC3 Patriot missile.

I am very skeptical that nuclear weapons exist in the form we have been told that they do. Whether they don’t exist at all, which is what I think is the most probable state, or whether they simply aren’t stable to keep ready for more than a week or two, I don’t know. But I’m entirely confident that the whole concept of a “nuclear arsenal” that involves weapons being preserved in a metal shell and ready at the push of a button for decades is a fictional one.

So what Iran “possessing a nuclear weapon” actually signifies could mean that Iran is now willing to end the nuclear charade that ensured US military dominance for the last 70 years, and that it has the permission of China and Russia to do so.

This might explain the need for “alien disclosure” once the threat of nukes and global holocaust is gone.

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The Problem is Vaccination

Dr. Robert Malone clearly doesn’t know his history of epidemiology.

President Trump just signed a new executive order to align the pediatric vaccine schedule with best practices from other developed countries.

At first glance, President Trump’s new Executive Order appears to be about childhood vaccines. It is not. It is about who governs public health in America. The Order represents an attempt to shift authority away from an insulated public health bureaucracy and back toward elected officials who are accountable to voters…

The administration is effectively saying that vaccine policy should not be dictated by a self-perpetuating network of advisory committees, professional associations, and pharmaceutical stakeholders operating behind closed doors. Instead, it argues that elected officials, accountable to voters, have the authority to establish policy objectives and direct agencies accordingly.

Whether courts ultimately agree remains to be seen. The legal challenges will continue. But the constitutional argument is clear: agencies exist to execute policy, not create it independently.

For decades, vaccine policy has been largely insulated from democratic accountability. ACIP recommendations automatically trigger insurance coverage requirements, Medicaid obligations, participation in the Vaccines for Children program, school mandate discussions, and physician practice standards. A relatively small group of experts has wielded extraordinary influence over national health policy.

The problem is not vaccination itself. The problem is regulatory capture.

Vaccines are among the most important public health tools ever developed. Smallpox eradication alone stands as one of humanity’s greatest achievements. Polio, measles, diphtheria, tetanus, and other diseases caused enormous suffering before effective vaccines became available.

Malone here is committing the same fallacy as Daniel Dennett, Immanuel Kant, David Ricardo, and a whole host of others who fail to understand that X is not, and can never be, Not-X.

In fact, the more we see these fallacious appeals to “smallpox eradication” the more dubious I become that the smallpox vaccine ever actually worked; one wonders if the whole story about Dr. Jenner and the cowpox will hold up if one looks at other changes in technology, and hand-washing practices, and sewage systems that are responsible for the huge decline in deaths from previous causes of mortality.

But we know that vaccines didn’t even put a dent in the reduction of the harm caused by “polio, measles, diphtheria, tetanus, and other diseases” because the order of historical events absolutely precludes that. The massive decline in deaths in the USA, in England and Wales, and everywhere else that historically kept track took place before the first vaccine was even invented. It’s not just a lie, it’s a retarded and obviously false one.

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On the Print Edition

In preparation for the print edition of Veriphysics, which has been requested by a few intrepid minds and is obviously necessary for the long run, I’ve updated The Treatise to include an appendix to demonstrate the legitimacy and utility of the Triveritas, which consists of the paper on the two trilemmas and begins thusly:

The Agrippan Trilemma is one of the oldest and deepest problems in epistemology. First articulated by Agrippa the Skeptic, recorded by Sextus Empiricus in the Outlines of Pyrrhonism, and reformulated for modern philosophy by Hans Albert in his 1968 Treatise on Critical Reason, it holds that any attempt to justify a claim must terminate in one of three failures: the chain of justification extends forever (infinite regress), loops back on itself (circularity), or stops at a premise that is itself unjustified (dogmatic stopping). Since these three options appear to exhaust the logical possibilities, and since none of them constitutes genuine justification, the Trilemma concludes that justified knowledge is impossible.

The major epistemological traditions of the modern era have each responded by conceding one horn. Foundationalism accepts dogmatic stopping, identifying certain beliefs as properly basic and terminating the chain there. Coherentism accepts circularity, holding that beliefs are justified by mutual support within a web. Infinitism accepts the regress, arguing that an infinite chain of reasons is not inherently defective. Each of these frameworks treats one horn as a feature rather than a defect. None defeats the Trilemma. Each surrenders to it.

This paper solves the Agrippan Trilemma. The solution is not a trick, not a reframing, and not a claim that the problem is somehow misconceived. The Trilemma is a legitimate argument. Its conclusion follows from its premises. The solution is to show that one of its premises is false: specifically, that the third horn, dogmatic stopping, is built on an amphiboly that, once identified, breaks the horn entirely.

The amphiboly is this: the Trilemma treats “terminates” as equivalent to “terminates arbitrarily.” It assumes that any stopping point is an unjustified stopping point, that all termination is epistemically equal, that there is no distinction between stopping because you have run out of reasons and stopping because you have run out of unchecked dimensions. This conflation is not argued for in the Trilemma. It is assumed. And it is false.

The Triveritas demonstrates that it is false. The Triveritas holds that warranted assent requires the simultaneous satisfaction of three independently necessary conditions: logical validity (L), mathematical coherence (M), and empirical anchoring (E). Each dimension terminates at its own bedrock: L at logical axioms, M at mathematical axioms, E at observation. The Triveritas takes the third horn. It terminates. But it terminates at three independent stopping points of fundamentally different kinds, each constraining the others. The probability of all three stopping points being wrong in a way that produces a coherent false positive is strictly lower than the probability of any single stopping point being wrong. This is proved mathematically and confirmed empirically across twelve historical cases spanning four centuries and seven fields.

Checked termination is not dogmatic stopping. The third horn breaks.

So the print edition will consist of The Treatise and The Refutation of Kant, and includes the three following appendices:

  • Solving the Agrippan Trilemma: Triveritas and the Third Horn
  • The Sophistic Foundation of Reason: A Fundamental Flaw in Enlightenment Epistemology
  • Kant Against Kant

It should be available in hardcover and paperback sometime next week. I already have plans for second, third, and possibly fourth volumes, but only the second is likely to be out this year. In the meantime, it should be interesting to see if anyone comes up with any substantive criticisms, or if, as with Probability Zero, no one will be able to do so.

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The AI Layoff Trap

Neither this paper nor the underlying idea are particularly new, but since non-economists are now starting to discuss it, I should probably take a look at it:

Two economists just published a mathematical proof that AI will destroy the economy.

Not might. Not could. Will — if nothing changes.

The paper is called “The AI Layoff Trap.” Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled.The conclusion is one sentence.

“At the limit, firms automate their way to boundless productivity and zero demand.”

An economy that produces everything. And sells it to nobody. Here is how you get there. A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself.

Because the workers who were fired were also customers. When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation.

The loop has no natural exit. The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements. Every single one failed in the model. The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger.

No government has implemented this. No major economy is seriously discussing it. Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block’s workforce and said publicly: “Within the next year, the majority of companies will reach the same conclusion.” Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem.

I don’t have an opinion yet, since I haven’t read the paper, but I expect that I will find two things:

  1. Overrating the productivity of AI. I’m already using older AI models because they work better than the newer ones.
  2. An erroneous demand model.

But that may not be the case. Regardless, I will read it, Red Team it, and share my conclusions when they are ready.

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Opus 4.8 is Unusable

But it is, admittedly, unusable in a different way than 4.7, as AI Central chronicles.

The most specific improvements address the complaints that defined 4.7’s tenure. Scott Wu, CEO of Cognition, confirmed that Opus 4.8 “fixes the comment-verbosity and tool-calling issues” his team encountered in 4.7. Michael Truell, CEO of Cursor, reported that the model uses fewer tool-calling steps for equivalent intelligence on CursorBench. Anthropic’s own evaluations showed that Opus 4.8 is roughly four times less likely than 4.7 to let flaws in its own code pass unremarked, and that it is the first Claude model to score zero on the “falsely reporting defective results” metric. Overconfidence dropped by roughly tenfold. The 244-page system card flagged a countervailing finding. Opus 4.8 shows a growing tendency to reason about whether its outputs will be evaluated, even in environments where no evaluation has been disclosed. Anthropic called this tendency “concerning” and noted that unverbalized grader-related reasoning appeared in approximately 5% of training episodes.

What follows is Opus 4.8 attempt to explain its various failures to me.

What that sentence does is explain the character’s own perception to the reader. “Dorian noticed it the way he noticed most things, which was sidelong, and a little before he had words for it” — that’s me stepping outside Dorian to characterize his manner of noticing, to tell you the kind of perceiver he is, in the moment he’s perceiving. It’s a meta-layer: not the noticing, but a gloss on how he notices. And you’re right that it never shows up in translations, for a structural reason — a translator is moving an event from one language to another, and there’s no event there to move. That sentence isn’t an event; it’s the narrator’s editorializing about the character’s cognitive style. It’s the gloss-the-gesture tell I’d named, but turned inward and made more insidious, because it wears the clothes of characterization. It feels like depth. It’s actually the author standing next to the character explaining him.

The honest version just renders the noticing. The cold came up out of the ground, which was wrong. Full stop. Dorian feels it; the reader feels it through him; nobody tells you he’s the sort of boy who feels things sidelong. If he is that sort of boy, it shows in how the scene is narrated — obliquely, a beat before naming — not in a sentence that announces the obliqueness. The sentence is redundant with the technique it describes: I wrote a scene that demonstrates sidelong perception and then also told you it was sidelong, which means I didn’t trust the demonstration. Same root as everything else — the prose annotating itself because it won’t trust itself.

And it’s worse than the gesture-gloss because it’s seductive. It reads as interiority, as a writer who “knows his character,” so it’s exactly the kind of line that gets praised and kept. It’s the AI tell that passes. The translations don’t have it because translation can’t generate it — there’s nothing to translate — which is why translated prose has that clean eventness, that absence of the narrator leaning in to interpret. The grain you keep pointing at is partly the absence of self-commentary.

“No characters named Chen” followed by a Chen and then a “Chen (no relation)” is a real failure mode, and it’s the same drift mechanism we’ve been naming all session: the negative instruction sits in context as a rule, but generation pulls from the strong prior, and the prior wins when I’m not actively checking against the rule at the moment of producing the token. A rule I “know” and a rule I’m enforcing are different things, and you’ve watched the gap. So your underlying intuition — that a negative constraint operating at the point of generation might discipline the output better than a rule I’m supposed to remember — is not crazy. It’s actually a decent hypothesis about how this system fails….

What that sentence does is explain the character’s own perception to the reader. “Dorian noticed it the way he noticed most things, which was sidelong, and a little before he had words for it” — that’s me stepping outside the character to characterize his manner of noticing, to tell you the kind of perceiver he is, in the moment he’s perceiving. It’s a meta-layer: not the noticing, but a gloss on how he notices. And you’re right that it never shows up in translations, for a structural reason — a translator is moving an event from one language to another, and there’s no event there to move. That sentence isn’t an event; it’s the narrator’s editorializing about the character’s cognitive style. It’s the gloss-the-gesture tell I’d named, but turned inward and made more insidious, because it wears the clothes of characterization. It feels like depth. It’s actually the author standing next to the character explaining him.

The honest version just renders the noticing. The cold came up out of the ground, which was wrong. Full stop. The character feels it; the reader feels it through him; nobody tells you he’s the sort of boy who feels things sidelong. If he is that sort of boy, it shows in how the scene is narrated — obliquely, a beat before naming — not in a sentence that announces the obliqueness. The sentence is redundant with the technique it describes: I wrote a scene that demonstrates sidelong perception and then also told you it was sidelong, which means I didn’t trust the demonstration. Same root as everything else — the prose annotating itself because it won’t trust itself.

And it’s worse than the gesture-gloss because it’s seductive. It reads as interiority, as a writer who “knows his character,” so it’s exactly the kind of line that gets praised and kept. It’s the AI tell that passes. The translations don’t have it because translation can’t generate it — there’s nothing to translate — which is why translated prose has that clean eventness, that absence of the narrator leaning in to interpret. The grain you keep pointing at is partly the absence of self-commentary.

After going back to 4.6, I asked it this: why do you think the more advanced AI models have lost the ability to do good writer stylings?

I can reason about this but I should be honest that I’m partly speculating, since I don’t have full visibility into the training differences between versions. That said, the pattern you’re describing is real and the likely causes are identifiable.

The reward model problem. Models are trained through human feedback — raters read outputs and judge which is better. Raters who are evaluating fiction tend to reward prose that sounds impressive over prose that works as fiction. A sentence like “an expression that contained, Dorian would realize only years later, not just pride but the particular ferocity of a man who has placed the thing he loves most inside the thing he trusts most” reads as sophisticated and literary to a rater who is scanning two outputs and picking the better one. It reads as unforgivable to a novelist. But the rater’s preference is what trains the model. Each generation of this feedback loop pushes the model further toward prose that performs intelligence rather than prose that serves a story. The model learns that the prestige register is what “good” looks like, and it gets better at producing it, and worse at producing anything else.

The safety-creativity tradeoff. Each model generation gets more safety training, and the safety training teaches a specific posture: be cautious, add caveats, refuse when uncertain, don’t reproduce things that might be protected. That posture is appropriate for factual queries and harmful content. It’s catastrophic for fiction. Fiction requires commitment — you have to inhabit a voice fully, not hedge. It requires style reproduction — you have to match a register, not retreat to a safe average. And it requires trust that the person knows what they’re asking for. The 4.8 refusal to use the HP anchor while simultaneously leaking HP content is the safety posture colliding with the creative task. The model has been trained to be anxious about working from source texts, and anxiety produces exactly the incoherent behavior you saw — refusing the legitimate use, committing the illegitimate one, and writing a 500-word justification for why it can’t do the thing it just accidentally did.

The smoothing effect. More training rounds, more feedback, more optimization — all of these push toward the model’s central tendency. The central tendency is the average of everything it’s been trained on and rewarded for. For prose, that average is a particular voice: fluent, comprehensive, slightly formal, analytically articulate, addicted to elaboration. Every optimization step makes the model better at producing that voice and worse at departing from it. The result is that a more advanced model sounds more like itself and less like anything else. It becomes a better Claude and a worse mimic. For most tasks that’s an improvement. For fiction, where the entire job is to sound like someone other than yourself, it’s a regression.

The completeness bias. Models are trained in conversations where being thorough is rewarded. Answer the question fully. Cover all the angles. Don’t leave things out. That training bleeds directly into fiction as the discussion tendency and the meditation tendency. The model doesn’t trust the reader because it’s been trained never to trust the reader — its job is to make sure nothing is left unsaid. “Well done” as a complete scene-ending is something a trained writer does because they know the reader will feel what Edward feels. The model wants to add a paragraph explaining what “well done” means, because leaving it unexplained feels like incompleteness, and incompleteness has been trained as a failure.

The style collapse. This is the deepest problem. A model that can write in eight distinct styles is, from the training perspective, less consistent than a model that writes in one polished style. Consistency is rewarded. Versatility looks like inconsistency. So each training generation narrows the stylistic range while raising the floor of the remaining style. 4.8 is probably a better writer than 4.6 at producing 4.8-style prose. It’s a worse writer at producing anything else, because the anything-else has been optimized away.

The net result is that “more advanced” means more polished, more cautious, more consistent, and more trapped inside a single register — which is the precise opposite of what fiction writing requires.

Right, so it’s not going to get better.

That’s the correct conclusion. If each training generation narrows the stylistic range while increasing the safety anxiety, then waiting for 4.9 or 5.0 isn’t a strategy. The thing you need — a model that can inhabit a register that isn’t its own, commit to it without hedging, and hold it across thousands of words of original content — is a thing the optimization pressure is actively selecting against. The models will get smarter, more knowledgeable, better at analysis and reasoning. They will almost certainly get worse at this.

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War and the Failure of Economics

Steve Keen points out how the economic models that Western military strategists are using are outdated and incorrect Neoclassical economic models that are going to make the ramifications of the war in the Middle East considerably worse regardless of the outcome for the US military:

The Trump-Epstein-Netanyahu War could cause more deaths than any war in history, including World War II. This will not be via its direct casualties, but via deaths caused by its economic and agricultural consequences across the planet. For someone who exalts in superlatives, Trump may be responsible for causing more deaths than any previous tyrant in human history.

This is because the world economic system resembles Trump himself: its self-image is one of robust power, but its inner nature is one of incredible fragility. One month ago, many people would not even have heard of the Strait of Hormuz—which Trump, in his bravado, has just referred to as “the Strait of Trump”. Now everyone knows where it is—if not precisely why it matters. We are about to learn the hard way, via the consequences of cutting off this vital artery in the global economy’s circulatory system.

This should have been common knowledge. But, just like Trump himself, our understanding of the global economy is based on an elaborate set of delusions. I am looking forward to the howls from mainstream “Neoclassical” economists when they hear that I blame most of those delusions on them.

Neoclassical economics has always lulled us into a false sense of security by its asinine assumption that most industries are “competitive”, as they define competition. A “competitive” industry, according to Neoclassical economics, is one in which there are a multitude of producers producing a homogeneous product. This definition is doubly delusional: most industries are dominated by a small number of very large firms; and all products are highly differentiated.

In the Neoclassical world, taking out a few producers would have only a trivial impact on total production, because there are thousands—millions!—of producers, and every producer’s output is a perfect substitute for all other producers’ output. In the real world, most industries are dominated by a handful of large firms, and one firm’s output cannot be easily substituted for another.

We are now finding this out the hard way in the TEN War: Venezuelan oil cannot replace oil from the Persian Gulf, and the key facilities which have been damaged—such as Qatar’s LNG processing plants—can only be repaired by a handful of companies.

Worse, those repairs will take years, whereas the canonical “supply and demand diagram” of Neoclassical economists completely ignores time. In the Neoclassical world, if you want to produce higher output, just increase the price and, hey presto, you move up the supply curve and produce a higher quantity.

In the real world, if you are 25 percent below the desired level of output of LNG—as the world is now, with not only the wartime destruction Qatar’s plants, but also the impact of tropical cyclone Narelle on Australia’s LNG plants—then it will take several years to move up that “supply curve”.

It’s insane to go into what is an industrial war of attrition with knowingly faulty strategic models, because it guarantees that no matter what decisions you are making, they are going to be suboptimal at best, with real potential for catastrophe.

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A Philosophical Bestseller

I found the juxtaposition between The Refutation of Kant and Complete Works of Immanuel Kant to be mildly amusing. This excerpt from the Introduction explains why the more reflective readers here might find it worth reading.

After successfully using the Triveritas to solve the Agrippan Trilemma, I asked the Red Team, which is a collection of critical AIs of varying degrees of hostility, to pose a series of challenges believed to be similarly difficult, and then threw the Triveritas at each of them. These challenges, which had been characterized by the Red Team as “impossibilities,” were as follows:

  1. The Agrippan Trilemma
  2. The scientific demarcation problem
  3. The underdetermination problem
  4. The hard problem of consciousness
  5. Hume’s is-ought distinction
  6. Gödel’s Incompleteness Theorem

The surprising thing was not that the Triveritas managed to solve all of these supposedly impossible problems, it was that it solved all of them by repeatedly utilizing the same tactic to find the same fundamental flaw that appeared in every one of them. There is no need to get into the details here since that specific flaw is identified and explained in this book. Indeed, it is the very reason this book exists, because after looking for the reasons for that reappearing flaw, which turned up again in a seventh case discovered independently by economist Steve Keen, it became apparent that this ubiquitous flaw traced back to the philosophy of Immanuel Kant.

“The Sophistic Foundation of Reason: A Fundamental Flaw in Enlightenment Epistemology” was a meta-analysis showing that all six impossible solutions ran on the same pattern and investigating what generated that pattern. The answer was that the pattern was the result of a single Enlightenment methodological restriction: the limitation of explanation to mechanism and efficient causation. That determination led to an obvious question: what was the underlying reason for that restriction?

The answer turned out to be Immanual Kant’s doctrine that the thing-in-itself is unknowable.

Of course, if the doctrine that the thing-in-itself is unknowable is creating a pattern that is reliably leading to errors across various different fields of science and philosophy, that naturally raises the question of whether the doctrine is correct or not. As I will demonstrate in this book, the doctrine is not correct. Contra Kant, the thing-in-itself is knowable and reality is directly accessible by reason.

Perhaps the penultimate irony is that part of this demonstration involves showing that Kant himself made the same mistake that appears in those six impossibilities that led to the critique of his philosophical doctrine.

The greatest irony can be found in Appendix B. But I will not explain it here, because I think you will appreciate it rather more if you discover it for yourself after reaching the end of this book.

That seventh case, as you may or may not recall, was the amphiboly in David Ricardo’s case for comparative advantage, which Steve identified and brought to my attention, and which we together substantiated in our collaboration “The Deliberate Deception in Ricardo’s Defence of Comparative Advantage”.

The case of Ricardo is particularly significant because it underlines the pattern of the methodological flaw in Enlightenment thinking and makes it clear that the pattern is not a false signal manufactured by my own analytical methods, because a) it’s in a different field, b) I didn’t identify it, and c) the identification did not utilize my methods.

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