DST — Domain and Scale Taxonomy

A structured way to classify human achievement and influence along two independent axes: what someone does, and how far it reaches.

Most attempts to rank people collapse everything onto a single number — net worth, follower count, a list position — which flattens a physicist, a novelist, and a footballer onto one line and pretends the comparison means something. DST keeps the dimensions apart. It does not ask how important is this person; it asks two cleaner questions and keeps the answers separate.

The two axes

Domain — what field someone operates in

Eight main domains, each divided into eight sub-domains (64 cells in total). Every entry is tagged with exactly one main domain and one sub-domain, giving a two-level fix on their work without forcing them into a single bucket.

Each domain carries a consistent colour and symbol throughout the system, so the colour alone places someone roughly before you read a word.

The full domain and sub-domain reference — names, codes, symbols and colours — lives in docs/spec.md.

Scale — how far the impact reaches

A four-step scale, independent of domain:

Code	Scale	Meaning
S1	Field / Local	Influential within a specific field or locality
S2	National / Regional	Recognised across a country or region
S3	International	Known and influential across borders
S4	Civilizational / Global	Impact at the scale of the whole culture

Scale is deliberately independent of domain. A scientist whose work reshapes a discipline can be S4 while remaining unknown to the public; a television personality can be S3 in reach without that saying anything about the domain they occupy. S4 carries amber throughout the system so civilizational figures are easy to pick out at a glance.

First dataset: the 1964 UK cohort

A taxonomy with empty cells proves nothing, so DST was pressure-tested against a real cohort: people born in the United Kingdom in 1964. That year sits at roughly the peak of the post-war baby boom, which means a large enough population to find genuine examples for every domain and every scale rather than reaching for whoever comes to mind. A bigger pool lets the cells fill themselves.

The result is 62 people spanning politics, the arts, the sciences, sport, business and more — enough coverage to expose where the taxonomy holds and where it strains.

The dataset lives in data/uk-1964.json and drives the interactive explorer in explorer/.

Repository layout

.
├── README.md            This file
├── docs/
│   ├── spec.md          Full taxonomy: domains, sub-domains, symbols, colours, scales
│   └── method.md        Selection method, rationale, and limitations
├── data/
│   └── uk-1964.json     The 1964 UK cohort (single source of truth)
└── explorer/
    └── index.html       Self-contained, sortable/filterable cohort explorer

Data is kept separate from presentation on purpose: the same data/*.json feeds the standalone explorer here and any future component embedded elsewhere.

Status

Early and experimental. One cohort run complete (UK, 1964). The framework began as a tri-axis idea; the middle axis was dropped during development, leaving the two axes above, which already provide strong classification power on their own.

Planned next: additional cohorts (other years, other countries) and a tightened spec so others can apply DST to their own datasets.

License