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🟢 LINEAGE_OPERATOR

RTT/1 Operator Specification — archive_org Module#

Identity#

  • Operator Name: LINEAGE_OPERATOR
  • Operator Family: L‑Ops (Lineage Operators)
  • Module: archive_org
  • Purpose: Construct the continuity kernel and lineage graph from normalized metadata and time‑indexed snapshots.

Purpose (One Sentence)#

The LINEAGE_OPERATOR reconstructs the object’s structural evolution by building a lineage graph, identifying transformations, and detecting regime shifts across snapshots.

Inputs#

Input Type Description
snapshots list Time‑ordered IA captures from WAYBACK_OPERATOR.
metadata object Normalized metadata from METADATA_OPERATOR.

Outputs#

Output Description
lineage_graph Directed graph showing structural evolution across snapshots.
transformations List of structural changes (template, layout, substrate, navigation).
regime_shifts Points where the object changes operational regime.
continuity_kernel Stable structural elements preserved across versions.

Operator Guarantees#

  • No content‑based inference.
  • Lineage is structural, not semantic.
  • Regime shifts are based on structural change, not topic change.
  • Continuity kernel is minimal, stable, and non‑speculative.
  • Missing snapshots produce uncertainty, not assumptions.

Lineage Concepts (RTT/1)#

Continuity Kernel#

The minimal set of structural elements that persist across snapshots.
Examples:

  • navigation skeleton
  • header/footer structure
  • persistent template regions
  • stable metadata fields

Transformations#

Structural changes between snapshots:

  • layout changes
  • navigation rewrites
  • template replacements
  • substrate changes
  • CMS migrations

Regime Shifts#

A regime shift occurs when the object’s structural purpose or operational mode changes.
Examples:

  • static HTML → CMS
  • HTML → Flash → HTML5
  • public page → paywalled page
  • v1 → v2 branch in software docs

Operator Procedure#

  1. Receive snapshots + metadata.
  2. Compare each snapshot pair for structural changes.
  3. Identify transformations and drift patterns.
  4. Detect regime shifts using:
    • substrate changes
    • template changes
    • navigation rewrites
    • functional changes (e.g., paywall)
  5. Extract continuity kernel across all snapshots.
  6. Build lineage graph:
    • nodes = snapshots
    • edges = transformations
    • flags = regime shifts
  7. Emit outputs for COLLECTION_OPERATOR and PRESERVATION_OPERATOR.

Failure Modes#

  • Sparse snapshots: lineage graph may be incomplete.
  • Mixed substrates: kernel extraction may require PRESERVATION_OPERATOR.
  • Redirects: may indicate lineage forks (handled structurally).

Hand‑Off to Next Operator#

Outputs feed directly into:

COLLECTION_OPERATOR#

  • lineage_graph
  • regime_shifts

PRESERVATION_OPERATOR#

  • continuity_kernel
  • transformations

Example (Synthetic)#

Input:
  snapshots = [2014, 2017, 2020, 2023]
  metadata = { regime: "institutional", substrate: "html" }

Output:
  lineage_graph = {
    "2014→2017": "minor transformation",
    "2017→2020": "major transformation (CMS migration)",
    "2020→2023": "minor transformation"
  }
  transformations = ["CSS shift", "CMS migration", "PDF layer added"]
  regime_shifts = ["2020: static → CMS"]
  continuity_kernel = ["header", "footer", "records-index"]

RTT/1 Mindset#

  • Lineage is structural, not narrative.
  • Regime shifts are structural, not topical.
  • Continuity kernel is the anchor for drift‑bounded reasoning.
  • No assumptions about missing snapshots.
  • No content‑based inference.
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