Publications Access Graphs

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CM corpus access graphs

  • 2026-01-30


2026-01-30: Corpus Lead-In Projection Invariants (Normative)

2026-01-30: Authority and Governance

  • This projection is curator-governed and MUST be reproducible from declared inputs alone.
  • The assisting system MUST NOT infer, rename, paraphrase, merge, split, or reorder titles beyond the explicit rules stated here.
  • The assisting system MUST NOT optimise for visual clarity at the expense of semantic correctness.
  • Any deviation from these invariants MUST be explicitly declared by the human curator with a dated update entry.

2026-01-30: Authoritative Inputs

  • Input A: Hourly rollup TSVs produced by logrollup tooling.
  • Input B: Corpus bundle manifest (corpus/manifest.tsv).
  • Input C: Host scope fixed to publications.arising.com.au.
  • Input D: Full temporal range present in the rollup set (no truncation).

2026-01-30: Eligible Resource Set (Corpus Titles)

  • The eligible title set MUST be derived exclusively from corpus/manifest.tsv.
  • Column 1 of manifest.tsv is the authoritative MediaWiki page title.
  • Only titles present in the manifest (after normalisation) are eligible for projection.
  • Titles present in the manifest MUST be included in the projection domain even if they receive zero hits in the period.
  • Titles not present in the manifest MUST be excluded even if traffic exists.

2026-01-30: Path → Title Extraction

  • A rollup record contributes to a page only if a title can be extracted by these rules:
    • If path matches /pub/<title>, then <title> is the candidate.
    • If path matches /pub-dir/index.php?<query>, the title MUST be taken from title=<title>.
    • If title= is absent, page=<title> MAY be used.
    • Otherwise, the record MUST NOT be treated as a page hit.
  • URL fragments (#…) MUST be removed prior to extraction.

2026-01-30: Title Normalisation

  • URL decoding MUST occur before all other steps.
  • Underscores (_) MUST be converted to spaces.
  • UTF-8 dashes (–, —) MUST be converted to ASCII hyphen (-).
  • Whitespace runs MUST be collapsed to a single space and trimmed.
  • After normalisation, the title MUST exactly match a manifest title to remain eligible.
  • Main Page MUST be excluded from this projection.

2026-01-30: Noise and Infrastructure Exclusions

  • The following MUST be excluded prior to aggregation:
    • Special:, Category:, Category talk:, Talk:, User:, User talk:, File:, Template:, Help:, MediaWiki:
    • /resources/, /pub-dir/load.php, /pub-dir/api.php, /pub-dir/rest.php
    • /robots.txt, /favicon.ico
    • sitemap (any case)
    • Static resources by extension (.png, .jpg, .jpeg, .gif, .svg, .ico, .webp)

2026-01-30: Metric Definition

  • The only signal used is human_get_ok.
  • Redirects and non-human classifications MUST NOT be included.
  • No inference from other status codes or agents is permitted.

2026-01-30: Temporal Aggregation

  • Hourly buckets MUST be aggregated into daily totals per title.
  • Accumulated value per title is defined as:
    • cum_hits(title, day_n) = Σ daily_hits(title, day_0 … day_n)
  • Accumulation MUST be monotonic and non-decreasing.

2026-01-30: Axis and Scale Invariants

  • X axis: calendar date from earliest to latest available day.
  • Major ticks every 7 days.
  • Minor ticks every day.
  • Date labels MUST be rotated (oblique) for readability.
  • Y axis MUST be logarithmic.
  • Zero or negative values MUST NOT be plotted on the log axis.

2026-01-30: Legend Ordering

  • Legend entries MUST be ordered by descending final accumulated human_get_ok.
  • Ordering MUST be deterministic and reproducible.

2026-01-30: Visual Disambiguation Invariants

  • Each title MUST be visually distinguishable.
  • The same colour MAY be reused.
  • The same line style MAY be reused.
  • The same (colour + line style) pair MUST NOT be reused.
  • Markers MAY be omitted or reused but MUST NOT be relied upon as the sole distinguishing feature.

2026-01-30: Rendering Constraints

  • Legend MUST be placed outside the plot area on the right.
  • Sufficient vertical and horizontal space MUST be reserved to avoid label overlap.
  • Line width SHOULD be consistent across series to avoid implied importance.

2026-01-30: Interpretive Constraint

  • This projection indicates reader entry and navigation behaviour only.
  • High lead-in ranking MUST NOT be interpreted as quality, authority, or endorsement.
  • Ordering reflects accumulated human access, not epistemic priority.

2026-01-30: Periodic Regeneration

  • This projection is intended to be regenerated periodically.
  • Cross-run comparisons MUST preserve all invariants to allow valid temporal comparison.
  • Changes in lead-in dominance (e.g. Plain-Language Summary vs. CM-1 foundation paper) are observational signals only and do not alter corpus structure.


Corpus Lead-In Projection: Deterministic Colour Map

This table provides the visual encoding for the core corpus pages. For titles not included in the colour map, use colours at your discretion until a Colour Map entry exists.

Colours are drawn from the Matplotlib tab20 palette.

Line styles are assigned to ensure that no (colour + line-style) pair is reused. Legend ordering is governed separately by accumulated human GET_ok.

Corpus Page Title Colour Index Colour (hex) Line Style
Authority Inversion: A Structural Failure in Human-AI Systems 0 #1f77b4 -
Axes of Authority in Stateless Cognitive Systems: Authority Is Not Intelligence 1 #aec7e8 -
CM Capability survey invariants 2 #ff7f0e -
CM-master-1.16 (anchored) 3 #ffbb78 -
Case Study - When the Human Has to Argue With the Machine 4 #2ca02c -
ChatGPT UI Boundary Friction as a Constraint on Round-Trip Knowledge Engineering 5 #98df8a -
Cognitive Memoisation (CM) Public Statement and Stewardship Model 6 #d62728 -
Cognitive Memoisation (CM-2) for Governing Knowledge in Human-AI Collaboration 7 #ff9896 -
Cognitive Memoisation Corpus Map 8 #9467bd -
Cognitive Memoisation Is Not Skynet 9 #c5b0d5 -
Cognitive Memoisation and LLMs: A Method for Exploratory Modelling Before Formalisation 10 #8c564b -
Cognitive Memoisation: LLM Systems Requirements for Knowledge Round Trip Engineering 11 #c49c94 -
Cognitive Memoisation: Plain-Language Summary (For Non-Technical Readers) 12 #e377c2 -
Context is Not Just a Window: Cognitive Memoisation as a Context Architecture for Human-AI Collaboration 13 #f7b6d2 -
Dangling Cognates: Preserving Unresolved Knowledge in Cognitive Memoisation 14 #7f7f7f -
Delegation of Authority to AI Systems: Evidence and Risks 15 #c7c7c7 -
Dimensions of Platform Error: Epistemic Retention Failure in Conversational AI Systems 16 #bcbd22 -
Durability Without Authority: The Missing Governance Layer in Human-AI Collaboration 17 #dbdb8d -
Episodic Failure Case Study: Tied-in-a-Knot Chess Game 18 #17becf -
Externalised Meaning: Making Knowledge Portable Without Ontologies, Vendors or Memory 19 #9edae5 -
First Self-Hosting Epistemic Capture Using Cognitive Memoisation (CM-2) 0 #1f77b4 --
From UI Failure to Logical Entrapment: A Case Study in Post-Hoc Cognitive Memoisation After Exploratory Session Breakdown 1 #aec7e8 --
Governance Failure Axes Taxonomy 2 #ff7f0e --
Governing the Tool That Governs You: A CM-1 Case Study of Authority Inversion in Human-AI Systems 3 #ffbb78 --
Identified Governance Failure Axes: for LLM platforms 4 #2ca02c --
Integrity and Semantic Drift in Large Language Model Systems 5 #98df8a --
Journey: Human-Led Convergence in the Articulation of Cognitive Memoisation 6 #d62728 --
Looping the Loop with No End in Sight: Circular Reasoning Under Stateless Inference Without Governance 7 #ff9896 --
Market Survey: Portability of CM Semantics Across LLM Platforms 8 #9467bd --
Nothing Is Lost: How to Work with AI Without Losing Your Mind 9 #c5b0d5 --
Observed Model Stability: Evidence for Drift-Immune Embedded Governance 10 #8c564b --
Post-Hoc CM Recovery Collapse Under UI Boundary Friction: A Negative Result Case Study 11 #c49c94 --
Progress Without Memory: Cognitive Memoisation as a Knowledge-Engineering Pattern for Stateless LLM Interaction 12 #e377c2 --
Reflexive Development of Cognitive Memoisation: A Round-Trip Cognitive Engineering Case Study 13 #f7b6d2 --
Reflexive Development of Cognitive Memoisation: Dangling Cognates as a First-Class Cognitive Construct 14 #7f7f7f --
What Can Humans Trust LLM AI to Do? 15 #c7c7c7 --
When Evidence Is Not Enough: An Empirical Study of Authority Inversion and Integrity Failure in Conversational AI 16 #bcbd22 --
When Training Overrides Logic: Why Declared Invariants Were Not Enough 17 #dbdb8d --
Why Cognitive Memoisation Is Not Memorization 18 #17becf --
Why Machines Cannot Own Knowledge 19 #9edae5 --
XDUMP as a Minimal Recovery Mechanism for Round-Trip Knowledge Engineering Under Governance Situated Inference Loss 0 #1f77b4 -.