Record page
2026-03-13-accelerationism-scoring.md
This session note documents an early attempt to identify the most useful introductory material on accelerationism across a large text corpus.
Access note
Public page exposes metadata and a short excerpt only. The full note remains in the internal canonical corpus.
Core idea
The note asks which texts actually function as good introductions to accelerationism rather than simply mentioning the term.
It works through heuristics, thresholds, and explicit uncertainty, using fast scoring to separate broad relevance from newcomer usefulness.
The stakes are editorial. Prestige, obscurity, and density do not automatically produce a good introduction, so selection has to be argued rather than presumed.
Representative extracts
Definition · research note
27 texts scored >=18 (your threshold for good intro)
Why this matters: The threshold converts an editorial judgment into a countable result, producing the working shortlist from which the archive's introductory pathway is subsequently argued.
Stakes · research note
These are heuristic scores, not deep reads. Good for filtering which texts to actually sit down with, but not definitive rankings.
Why this matters: This caveat does the note's key epistemic work, bounding the scores' authority so the pass reads as a filter for attention rather than a verdict on quality.
History · research note
Looking at the session logs, they hit context window limits (model_context_window_exceeded).
Why this matters: The admission of a technical failure grounds the note's method: heuristic scoring is adopted not on principle but because exhaustive reading had already broken against the tooling's limits.
Afterlife · research note
Focus just on the high-scorers from the heuristic pass
Why this matters: The closing instruction turns the scoring exercise into a pipeline stage: fast filtering earns its keep only by handing a shortlist to slower, deeper reading.
Method · research note
A Python script using heuristics (keyword analysis + file characteristics) processed all 1,062 texts in ~30 seconds.
Why this matters: Here the note's central trade is stated plainly: coverage of the entire corpus is bought at the price of depth, setting up the caveats that follow.
Provenance
Canonical research note copied from the research-notes collection in land-ccru-archive.tar.gz.
Appears in sections
Accelerationism Branches and Debates Primary section
Left, right, unconditional, and popularized accelerationisms sorted into a cleaner research map.
AI, Basilisk, and Recursive Intelligence Also in
Recursive systems, intelligence explosion, basilisk motifs, and the archive's later AI-facing afterlife.