the codex loves science

So, across my Thoughts, you may see me bite science a bit. Let’s first get one thing clear: I am fundamentally pro-science.

I believe in evidence-based reasoning. I believe in logic. I believe in curiosity. I believe in data. And I trust humanity’s collective brain.

So why do I bite science?

Well, because science has some problems. Serious ones. In fact, when I was thinking about it in Codex terms, I realised that parts of the modern scientific institution can behave in a remarkably Evil way.

Big red alert button!

This is not Christian evil. Codex Evil means something that refuses to self-reflect and dedicates itself to keeping itself powerful at the cost of others. That distinction matters here, because I am not claiming that scientists are evil people, or that the scientific method is Evil. I am talking about what can happen when a human institution becomes large, prestigious, expensive, competitive, and convinced that its own systems are synonymous with Truth.

When I bite science, I am rarely biting the basic method. I am biting the structures that have accumulated around it: funding systems, publishing systems, prestige systems, career incentives, and all the little Crimson games humans inevitably begin playing around something valuable.

Let me explain with a bit of mapping.

Science Is Not a Block

First, science is not one thing. It is an extremely high-resolution phenomenon built from thousands upon thousands of scientists, students, technicians, institutions, journals, laboratories, funders, traditions, and disagreements across centuries.

Sometimes the media portrays science as one giant block.

“Science says this...”

As if all scientists agree.

There is no monthly smart-people meeting where we decide which green agenda to push next.

Mathematics is not biology. Biology is not astronomy. A theoretical physicist, a field ecologist, a clinical researcher, and an archaeologist may all be called scientists while working with completely different objects, standards, tools, uncertainties, and cultures. A single scientific field can already be its own little world before you even reach the individual people inside it.

I do admit it is easy to put academics in one box; academics tend to be a bit boring. But that stereotype holds only as far as you believe all construction workers are the same.

So when I map “science” below, I am deliberately mapping the broad institution and its dominant tendencies. I don't claim that every discipline, laboratory, journal, or scientist behaves identically.

Mapping Science

In Crystal terms, science maps strongest to the Dust–Eye-3 junction.

Science is Dust (E10) because it follows strict rules and standards to build an Order of knowledge out of information. Observations do not simply float into the scientific record and become Truth. They are measured, classified, compared, standardised, tested, placed into systems, and connected to what is already known.

Science loves protocols. Science loves categories. Science loves methods sections, taxonomies, reference systems, statistical thresholds, institutional hierarchies, controlled vocabularies, and little numbers telling you exactly where everything belongs.

It has tests, hierarchy, and a little bit of a status problem — typical Dust.

Earth mediates this Dust-building. Dust is built through refinement, logical chains, classification, repeated structure, and the patient ordering of information into something stable enough to stand.

This is one of science’s great strengths. One person’s observation can be placed beside another person’s observation. A result can be checked against a method. Knowledge can accumulate rather than constantly restarting from zero.

But science is also Eye-3 (E11).

Once scientists have a good grip on the ordered system, they try to look beyond it. This is the innovative side of science: the moment somebody notices that the existing map is incomplete, that the accepted model is failing somewhere, or that there is something just outside the current frame that nobody has properly seen yet.

This is the kind of vibe you get from watching CSI people stare through microscopes while blue reagents glow dramatically in the background.

In truth, science’s Eye-3 is usually less exciting. Most discoveries arrive after enormous amounts of Dust: years of training, boring measurements, failed experiments, calibration, reading, repetition, and trying to understand why one stupid machine is making that noise again.

But the principle is beautiful.

Dust builds the Order. Eye-3 looks beyond the Order.

Science constructs a map precisely so that somebody can eventually discover where the map is wrong.

And this is where the problem begins.

Because a genuine Eye-3 discovery is not always comfortable for Dust. The stronger and more prestigious the existing Order becomes, the more disruptive it can feel when somebody finds a crack in it.

Science is at its best when Dust says, “Good. Show me the crack.”

Science gets into trouble when Dust says, “Do you know how long we spent building this?”

When Crimson Enters the Laboratory

And then Crimson City reached science too.

What should have been primarily an E10 and E11 system — building Order and looking beyond it — becomes overlaid with an E5 game.

Knowledge becomes competition. Discovery becomes career capital. Papers become trophies. Citations become numbers to display. Grants become victories. Jobs become prizes. A scientist can sincerely love Truth while still being trapped inside a system that rewards visibility, novelty, status, and winning.

This distinction matters. You do not need corrupt scientists to get distorted science. You only need normal humans responding rationally to distorted incentives.

And once the Crimson game becomes strong enough, the system starts selecting not only for good science, but for people who are good at surviving the game around science.

Two places make this especially visible: grants and publishing.

Money, Money, Money

First, let’s start with the grant givers.

Science needs money. A lot of it.

Laboratories need equipment, technicians, materials, computing power, travel, storage, salaries, buildings, animals, field work, databases, and an endless supply of strangely expensive tiny plastic objects.

And no, Crimson, sadly most scientific knowledge will never return neatly back into money.

It is not always an investment in the standard economic sense. Sometimes a society spends money and what it gets back is knowledge. That knowledge might become useful next year, fifty years from now, or never in a way that can be placed on an invoice.

It is a little like buying a sofa. The sofa does not return your money once you buy it. You wanted the sofa.

Sometimes humanity should want to know something.

That makes science difficult for Crimson. Crimson likes Stone to come back carrying more Stone.

So what happens when scientific questions enter a system where money is scarce? Competition.

A huge amount of research depends on grants. Scientists or research groups propose a question, explain why it matters, describe how they would investigate it, prove that they have the people and infrastructure to do it, and then compete against many other proposals for a limited pool of money.

In principle, this is reasonable. There is never enough money to fund everything, so somebody has to choose.

The problem is that “choose the best science” sounds much easier than it is.

What is the best idea? The safest project? The most innovative? The most useful? The one most likely to succeed? The one most likely to transform a field? The one led by the researcher with the strongest track record? The one from the institution with the equipment to actually finish it?

Even responsible grant systems struggle with these questions. Prestige can easily contaminate the assessment of the work itself: a famous researcher, a famous institution, an impressive CV, or a fashionable topic can start carrying weight that does not belong to the scientific question.

This is why I do not think the solution is to sneer at grant reviewers and declare them stupid. Allocating limited research money is genuinely difficult.

But there is a difference between unavoidable judgement and allowing irrelevant status games to take over the judgement.

Once grants become central to careers, scientists need new skills.

Instead of only doing research, you also need to do politics.

“Look how smart I am.”

“Look how many prizes I won.”

“Look how many important people already believe in me.”

“Look how many times I did a PowerPoint presentation.”

As you can imagine, it turns ugly fast.

There is another distortion: some scientific problems sit closer to money than others.

Take neglected diseases. A disease can be medically important and scientifically interesting while still attracting far less commercial research because the people suffering from it do not represent enough purchasing power. The scientific importance of the disease and the profitability of solving it are two completely different measurements.

This is the more precise version of what I meant when I said cancer can be easier to fund than some diseases concentrated in poorer parts of the world. Cancer is obviously important. Fund cancer research! But a disease does not become scientifically less worthy because its victims have less Stone.

Yet Crimson can make it economically less interesting.

Yeay, Crimson!

The point is not that grant funding never supports obscure, unprofitable, or foundational work. It absolutely does. The point is that research priorities are never shaped by scientific curiosity alone. Money, politics, prestige, institutional priorities, commercial opportunity, and social attention all lean on the steering wheel.

Sometimes that steering is necessary.

Sometimes it quietly changes where the River of knowledge is allowed to flow.

Do You Want to Read Me, Please?

Then, the publishers...

I will keep this short and simplified, because academic publishing is its own strange little kingdom.

Scientists need to tell other scientists what they found. That part is non-negotiable. If you discover something and nobody can inspect the method, the data, the reasoning, or the result, it cannot properly enter the shared Order.

Historically, journals solved a real problem: they collected work, distributed it, organised it, edited it, and helped scientific communities keep track of what had been done.

In the 1800s, they used magazines with boring images.

Now most of the magazines are digital.

But the prestige machinery survived the printing press.

Some journals are “better” because... Well... We decided that they are, and then everybody began behaving as though that decision were an objective property of the Universe.

Prestige becomes circular. Scientists want prestigious journals because prestigious journals are where prestigious scientists publish, which makes the journals prestigious, which makes scientists want to publish there.

Metrics then try to turn that prestige into numbers. One famous example is the Journal Impact Factor, which roughly describes how often recent papers in a journal are cited. It can tell you something about a journal, but it cannot tell you whether one particular paper is good simply because that paper appeared there. A journal-level number can become a shortcut for judging work that should have been judged on its own contents.

The problem is not that journals have reputations. Reputation can contain useful information. The problem begins when the container becomes more important than the thing inside it.

Then the question subtly changes from:

“Is this careful, useful science?”

to:

“Is this exciting enough for this journal?”

Those are not the same question.

If you study naked mole rats, perhaps you need a really genius breakthrough to get into the fanciest paper.

More seriously, this produces one of science’s ugliest little problems: publication bias.

A dramatic positive result is easier to sell than “we tested the idea carefully and found nothing”. But a negative result can be extremely important. If ten careful laboratories test an effect and only the one positive experiment enters the literature, a future reader does not see the evidence. They see a selected version of the evidence.

This is not a hypothetical worry. Publication bias is a known scientific problem: if positive, surprising, or fashionable results are easier to publish than negative or boring ones, then the published literature can become a distorted sample of the research that was actually done.

And that is exactly the kind of self-reflection I want more of.

Peer Review Is Good — So Why Is It So Weird?

Then there is peer review.

You have probably heard about it when someone snapped at you:

“But that is not peer-reviewed evidence.”

Peer review is much less mystical than people sometimes imagine. You write a scientific paper. You send it to a journal. An editor decides whether it is worth sending onward. If it is, other scientists with relevant expertise read it and criticise the work. They may find errors, demand clearer methods, challenge interpretations, ask for more analyses, or decide the work is not strong enough.

The authors answer. The paper may change. Eventually it is accepted or rejected.

That is peer review.

It is not a Truth machine.

A peer-reviewed paper is not automatically correct. It means the work passed through a particular process of expert scrutiny. That is valuable, because having a title does not make everything you say true.

In principle, peer review is profoundly scientific. You make a claim and expose it to people qualified to attack it.

Nothing wrong with that.

The weirdness comes from the implementation.

Scientists have little time. Reviewing is often one task piled on top of research, teaching, supervision, administration, grant writing, and trying to remember whether they have eaten today.

Reviewers also differ. One is brilliant. One nitpicks every comma. One barely cares. One hates your theoretical school. One is your intellectual rival. One gives you the exact criticism that saves the paper.

Traditional peer review can also be remarkably opaque. The reviewer may be anonymous. The reports may remain private. The editorial discussions are usually private. The reader sees the polished paper at the end, but not necessarily the messy process that shaped it.

That creates a strange contrast.

Science values transparency in the experiment while sometimes tolerating opacity in the machinery that decides whether the experiment gets seen.

To be fair, science is already experimenting with more open models: publishing review reports, showing author responses, making revisions visible, and allowing scientific discussion to remain attached to the work instead of disappearing behind editorial doors.

Good. More of that. The alternative is not science fiction; it is mostly a question of what kind of scientific culture we decide to build.

This is closer to what I want.

I do not think we need the traditional publisher as an invisible priest deciding what may enter the cathedral.

I want open scientific platforms where researchers’ credentials are checked, methods and data can be inspected where appropriate, peer review is transparent, criticism stays attached to the work, revisions remain visible, and scientifically serious work is allowed to enter the record even when the result is boring, negative, unfashionable, or inconvenient.

Review should help us judge how strong the work is.

It should not determine whether the work is allowed to have existed.

Cathedral of Science

My last objection to modern science is scientism.

Scientism is basically holding science as a religion.

More precisely: science is a family of disciplined methods for investigating the world. Scientism begins when people turn the success of those methods into the claim that scientific inquiry is the only legitimate lens for every kind of Truth.

When people make a Dusty Order, they are prone to adoring it like a Madonna.

Scientists are humans too, even when some act as though a title has elevated them above the masses.

This annoys me because, in my opinion, it misunderstands the beauty of science itself.

Science was never meant to become a completed Cathedral of Truth. Its greatness lies in the opposite: its Order is provisional. The model stands because it currently survives the evidence. Tomorrow, better evidence may force us to rebuild part of it.

Eye-3 is supposed to remain alive inside the Dust.

Scientism forgets Eye-3.

It looks at the Pyramid and says: “We have arrived.”

There is also a very Western heroic myth that science defeated religion, dragged humanity out of the Dark Ages, and finally taught everybody how to think.

History is much messier than that.

Without medieval monks copying books, monastic schools teaching generations of scholars, later medieval universities organising study, and centuries of intellectual exchange across religious and cultural worlds, modern science would not have appeared from empty space. Medieval Europe was not one long intellectual power outage waiting for a laboratory coat. The chain is much longer than the heroic story.

Science did not emerge by defeating every previous way of knowing.

It emerged from humanity’s much older habit of observing, remembering, measuring, comparing, wondering, teaching, and trying again.

And science is incredibly powerful within the kinds of questions it can answer.

What happens?

How often?

Under what conditions?

Which explanation best survives the evidence?

Wonderful. Please keep doing that forever.

But there are other questions.

What should I love?

What makes a beautiful Life?

What should I create?

What meaning should I give suffering?

What kind of person should I become?

You can use scientific knowledge while answering those questions, obviously. But the questions themselves are not reducible to measurements in the same way that the boiling point of water is.

Using science as the only lens for Truth is therefore narrow in my view. Not because science is weak, but because a powerful lens remains a lens.

Humans lived, loved, built, healed, navigated, created Artifacts, formed moral systems, made music, and accumulated knowledge for an immense span of Time before the modern scientific institution existed.

We have developed modern science over only a few centuries, and meanwhile we may be standing at the precipice of our own extinction.

Scientific power is not the same as wisdom.

A civilisation can know how to split an atom before it knows what it should do with one.

Does Science Love Itself?

So, no, I do not hate science at all.

I bite science because I like science.

If I thought it were worthless, I would not bother.

What worries me is that Crimson took something beautiful — an Order built specifically to inspect reality and correct itself — and taught parts of it to confuse prestige with Truth, funding with value, publication with quality, novelty with importance, and institutional survival with scientific progress.

The irony is painful.

Science builds an Order so it can look beyond the Order.

The moment preserving the Order becomes more important than looking beyond it, science begins betraying its own design.

And yet, there is hope precisely because scientists already study these problems. Reproducibility research exists. Open-science movements exist. Funding agencies alter review systems. Journals experiment with transparent review. Scientific organisations criticise the misuse of journal metrics. The Eye-3 is not dead.

It is just fighting a lot of Dust and Crimson.

So the question is not whether science can self-correct. Self-correction is one of the reasons I love it.

The question is whether science likes itself enough to apply that self-correction to its own institutions.

Love does not mean endlessly praising something. Love can look directly at an imperfection without needing to destroy the whole.

Building an Order of Truth requires Peace and Love — especially enough self-love to admit when your Order has begun serving something other than Truth.

I think science needs a little Love.

Sapphire would suit it so well...

But those are Thoughts for tomorrow.