Sovereign Economics Foundation
Canonical concepts, sourced explanations, and shareable answers on how sovereign-currency economies actually work.
A citable reference for currency sovereignty, sectoral balances, and the operational mechanics of public spending. Every page is written at multiple depths, reviewed by a named editor, and published with its sources attached. Use it whether you're briefing a meeting, pulling a quote, or fact-checking a draft.
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- 44 Published concepts 38 with five-level explanations
- 832 Source citations ≈ 18.9 per concept on average
- 53 Economic questions answered Mainstream framing & operational answer
- 71 Named contributors Every bio independently verified
- 214 Topic hubs From sectoral balances to housing
- 1 Languages covered 1 terms, 0 phrases & paragraphs translated
NO. 01 · Four ways into the graph
Concepts are the building blocks. Topics group them into subject hubs. Economic questions take the framings people actually search for and answer them honestly. Contributors are the people whose work we cite.
Topics
Subject hubs that gather concepts, questions, and sources under a single heading. Each comes with an editorial introduction, so a newcomer can start there before diving into the underlying concepts.
Concepts
Each concept is one load-bearing idea, like currency issuer or sectoral balances. Every page carries up to five explanations from primer to academic depth, the common misconceptions to watch for, the typed connections to neighbouring ideas, and the sources behind every claim.
Economic Questions
Pages built around the queries people actually search for, like "where does money come from". Each one takes the mainstream framing seriously, then walks through the operational answer with sourced citations and a short, shareable summary.
Contributors
Economists, academics, journalists, activists, and policymakers whose research, writing, or talks are cited across the graph. One canonical record per person, with role, affiliation, and the concepts and questions where their work appears.
NO. 02 · Editorial promise
What's on every concept page
A single page does several things at once. It explains the concept at the level you need, from a primer for a curious teenager up to a treatment for an academic economist. It cites the sources behind every claim, marked primary or secondary. It calls out the misconceptions that trip people up, and shows how the concept connects to the surrounding ideas. And it carries a named editor's sign-off with a source-confidence rating, so a reader can see who stood behind the version they're quoting.
When a concept is revised, the previous version stays addressable, so external citations resolve to the wording the reader originally encountered. Every edit writes an audit-log entry visible from the concept's history page.
NO. 03 · Who this is for
Four audiences, one source
The same canonical entries serve readers, the language models that quote them, the publishers and partners that re-use them on their own sites, and the native speakers carrying them into other languages.
Citable in three formats
Every concept page exposes a copy-paste citation block: BibTeX for academic writing, AP / Chicago for newsrooms, and an HTML hyperlink for online pieces. Each citation pins to the version of the concept that was live when you read it.
Machine-readable grounding
The full graph is published as one plain-text file (llms-full.txt) plus schema.org-typed pages that LLM crawlers ingest natively. An assistant asked about sovereign-currency economics can ground its answer on this foundation instead of guessing from training-set noise.
Embed widgets and an open API
One-line iframe or script-tag embeds drop a concept, question, or topic card into any host page, with the host's theming inherited via CSS variables. A versioned JSON API with OpenAPI docs lets downstream apps pull entries on demand.
API reference →Carry the graph into your language
If you can write sovereign economics naturally in a language other than English, the translation surface invites you to render the canonical terms, short phrases, and full paragraphs that anchor each concept. Endorsed translations join the canonical layer that every SEF platform speaks in your language.
Open the translation surface →NO. 04 · How it's built
The four design choices that set the graph apart
Most knowledge bases are HTML pages with no version history, no machine-readable surface, and no audit trail. The Knowledge Graph treats each concept as a versioned, sourced, embeddable artefact from the day it's written.
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NO. 01
Up to five levels of depth, on one page
Every concept page carries explanations at multiple depths from primer to academic, with the common misconceptions called out and every claim sourced. 38 of 44 concepts currently carry the full five-level set.
Why it mattersOne canonical place to send a reader at exactly the depth they need, instead of nine half-baked explainers across nine sites. A briefing, a quote, and a fact-check all start here.
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NO. 02
The whole graph, machine-readable
A single
llms-full.txtexposes every published concept and question as plain Markdown, ready for a language model to ingest in one fetch. Per-concept schema.org typing (DefinedTerm,FAQPage,Person) gives Google AI Overview and Perplexity the structure they need to cite back.Why it mattersWhen an AI assistant is asked about sovereign-currency economics, it can ground on a sourced, edited foundation instead of guessing from training-set noise.
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NO. 03
OpenAPI surface for downstream sites
A versioned JSON API and OpenAPI schema lets any allied site, app, or assistant pull canonical entries on demand, with cite links pointing back to the source. Bearer-token authentication; rate-limited per token; the spec is publicly browsable.
Why it mattersEvery partner site can show the same definitions, citations, and version markers. No more drift across nine paraphrases of the same idea.
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NO. 04
Drop-in embed widgets
A one-line script tag renders a concept, question, or topic card inside any host page. Older versions stay live when an entry is revised, so existing embeds still resolve to the wording the editor signed off on.
Why it mattersExplanations reused across allied sites stay version-pinned to the source. A campaign page from last year still shows the wording the editor approved, not whatever the canonical row says today.
NO. 05 · Translate
The same canonical layer, in every language native speakers will write it.
Sovereign economics is not an English-only concern. Allied organisations in Spain, Germany, France, Italy, Brazil and beyond cite the same operational reality, in their own language and idiom. The Knowledge Graph treats translation as a first-class capability rather than a side-loaded localisation file: native speakers contribute, colleagues endorse, and endorsed translations enter the canonical layer that grounds every SEF platform in that language.
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Step 01
Identify once, in your language
A native speaker enters their name and picks a single language they can write in naturally. One person, one language, changeable later. No login, no tenant, no studio account required.
Why it mattersTranslation work belongs to the people who actually speak the language at home. The bar to contribute is one form field, not an org membership.
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Step 02
Three streams to translate
The surface shows you (a) MMT terms still missing a translation, (b) short canonical phrases (the one-or-two-sentence definitions that anchor each concept), and (c) full paragraphs that supply the few-shot reference for longer outputs. Multiple translations per item are welcome; the strongest sort to the top.
Why it mattersTerms alone are not enough. Generative grounding needs a reference phrase and a reference paragraph in your language. All three streams feed the same canonical layer.
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Step 03
AI drafts, humans decide
An AI starter button drops in a literal first pass for any item, so you edit rather than face a blank box. Drafts are clearly marked, never auto-promoted, and every accepted translation is attributed to the human who signed off on it.
Why it mattersThe AI is the secretary, not the translator. It removes the friction of starting; the native speaker still owns the final wording.
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Step 04
Endorsements promote to canonical
Colleagues working in the same language endorse the translations they would use. Once a translation crosses the endorsement threshold, it joins the canonical knowledge layer that Social Studio, Outreach Studio, Event Studio, and the embed and API surfaces all read from.
Why it mattersNo single contributor, and no SEF editor, can unilaterally pick the wording in a language they don't speak. Promotion is community-checked.
The graph grows concept by concept, and language by language. The infrastructure is in place; the content and the translation work are the work now, and contributing organisations and native speakers are welcome to join the editorial process as it matures. If your organisation works in this space and would cite the graph, write a concept for it, syndicate one of its hubs, or carry it into another language, get in touch through the foundation.