Every measurement you make is also a decision about what to ignore. This is not a technical limitation — it's the central philosophical act of doing science. Charles Sanders Peirce, the 19th-century logician who essentially invented the modern theory of experimental inquiry, argued that scientific progress doesn't hinge on gathering more data but on the quality of the distinctions we choose to make: what gets counted as the same, what gets counted as different. His term for this was 'abduction' — the creative leap of deciding which features of a situation are worth attending to before you've even formed a hypothesis. Buddhist epistemology, particularly in the Dignāga school, independently reached a strikingly similar conclusion: perception is always already selective, and the categories we use to carve up experience shape what we can possibly find. Together, they suggest something uncomfortable — that the moment you design a measurement, you're not just observing the world, you're partially constructing what it's possible to discover. The practical implication is this: before you run the next experiment or analyze the next dataset, ask whether your categories are inherited from convention or chosen with genuine intention.

What would you measure differently if you had to justify why your current categories exist at all?

Drawing from Pragmatism / Buddhist Epistemology — Charles Sanders Peirce