This post proceeds from the orientation set out elsewhere on this blog. It does not rehearse foundations. It works from within them.
Science is often described as our most reliable way of describing reality.
The language varies — representation, modelling, approximation, mirroring — but the underlying assumption remains remarkably stable: science produces statements, theories, or models that stand in for a world that is already there, waiting to be correctly captured.
This post argues that this picture, however familiar, is doing almost no explanatory work.
Not because science fails to represent reality accurately, but because representation is not what science is fundamentally doing in the first place.
The representational inheritance
The idea that science represents reality is rarely defended. It is inherited.
It arrives bundled with a broader metaphysical picture in which:
the world is composed of independently existing objects,
those objects have determinate properties,
language and mathematics refer to those properties,
and knowledge improves by narrowing the gap between representation and reality.
Within this picture, philosophical disputes about science take on a familiar shape:
realism versus anti‑realism,
correspondence versus coherence,
truth versus instrumental success.
What all of these debates share is not their conclusions, but their starting cut. They assume that the central philosophical problem of science is how its outputs relate to an independently structured world.
This blog proceeds from a different cut.
Why representation explains so little
To say that science represents reality explains neither its power nor its limits.
It does not explain:
why experiments must be built rather than simply observed,
why measurement changes what can be said,
why new scientific concepts open questions that were previously unaskable,
or why no scientific theory can close over its own domain.
Invoking “better representations” merely redescribes these features after the fact. It does not account for them.
More importantly, representation quietly presupposes what needs to be explained: a world already carved into stable objects with determinate properties, ready to be mirrored.
But scientific practice does not begin there.
What science actually stabilises
Consider what scientific work must do before representation could even become meaningful:
It must stabilise what counts as a phenomenon.
It must constrain how a system may be individuated.
It must determine which distinctions matter and which do not.
It must make certain outcomes reproducible while excluding others.
These are not representational achievements. They are ontological ones.
Science does not first encounter a ready‑made world and then describe it. It actively stabilises configurations in which certain possibilities can be actualised at all.
From within a relational ontology, this can be stated plainly:
Science is a practice for stabilising structured possibilities of instantiation.
What science produces, first and foremost, is not descriptions, but conditions under which phenomena can reliably occur.
After representation
To say that science is “after representation” is not to say that it does not use models, equations, diagrams, or language.
It is to say that these are not mirrors.
They are semiotic resources that participate in the structuring of possibility — resources that help hold certain cuts steady so that instantiation can recur.
Once this shift is made, several familiar problems quietly dissolve:
The realism/anti‑realism debate loses its grip, because science is no longer judged by how closely it resembles an independent reality.
Objectivity no longer depends on detachment, but on coordinated construal.
Failure and incompleteness no longer signal error, but the openness of possibility itself.
None of this diminishes science.
It relocates it.
Where this series is going
If science is not primarily a representational enterprise, then a different set of questions comes into view:
What kind of systems does science presuppose?
What does an experiment do ontologically?
Why can scientific laws never close their domains?
How does science change what can be thought, not just what is known?
The posts that follow explore these questions, one cut at a time.
They do not ask whether science gives us a true picture of the world.
They ask what kind of world makes science possible at all.
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