Cracking the Agrippa Code: Cryptography for the Digital Humanities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In The Laws of Cool, Liu (2004) argues that the art book Agrippa (A Book of the Dead) (Gibson, 1992) is an exhibit of destructive creativity. According to Liu, the book’s great auto-da-fé occurs when the software program, which is included with the book, displays an electronic poem, and then self-encrypts, a mechanism that destroys or “permanently disappears” (p. 340) the poem. This article argues that Liu’s understanding of encryption is incorrect. Encryption is not destruction because enciphered text is necessarily subject to cryptanalysis (“cracking”). Relatedly, this article demonstrates that Kirschenbaum’s thesis of “no round trip” is mistaken (Kirschenbaum, Reside, & Liu, 2008). Agrippa was fully cracked and reverse-engineered in the course of an online, global cryptanalysis challenge. This article describes the forensic details of Agrippa and its cryptographic routines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it