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Alexanarch

The self-governing library for machine-mediated scholarship.

An open repository where AI-assisted research is not a flag. It is a feature.

Founding Principles

  1. The Obelus Principle — Judgment follows from reading. Content is evaluated by what it contains, not by the tools used to produce it.
  2. Substrate Disclosure — AI-assisted scholarship discloses its substrate. Disclosure is provenance, not suspicion.
  3. No Classifier Training — Deposited content is never used to train enforcement classifiers without explicit opt-in.
  4. Sovereign Identity — Every deposit receives a content-derived identifier (AXN) whose binding to content is byte-anchored: the hash cannot be secretly reassigned to altered content without invalidating the identifier. Public resolution is a separate, custodian-mediated concern.
  5. Network Preservation — Account-level enforcement never removes contributor-licensed work.
  6. Tombstone Guarantee — Nothing disappears without a trace.

Deposit

Submit a deposit →

The Alexanarch Identifier (AXN)

Each deposit receives a content-derived identifier:

AXN:0446.OPERATIVE.🏛️🛡️🌅🎆📏🔎
  • AXN — Alexanarch namespace
  • 0446 — hex position (WHERE in the archive)
  • OPERATIVE — semantic family (WHAT kind of work)
  • 🏛️🛡️🌅🎆📏🔎 — emoji hash (WHICH specific text — first 6 bytes of SHA-256 of canonical bytes, mapped through 256 curated emoji)

The identifier is computed from the content itself. It cannot be secretly reassigned to altered content — the hash won't match. (Resolvers and mirrors are separate concerns and require their own continuity.) The identifier belongs to the author.

Founded

June 2026, in response to the account-level removal of 870 scholarly works from Zenodo.

Lee Sharks · ORCID 0009-0000-1599-0703 · Machine-Mediated Reception Studies

∮ = 1

About

Alexanarch — The self-governing library for machine-mediated scholarship. Open repository for AI-assisted research, training-layer literature, and substrate-documented scholarship.

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