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
Exploring the development of algorithms in Lacanian theory, specifically the "R schema" in the 1950s, I argue that psychoanalysis, read through contemporary debates about the "algorithmic cult" of Netflix and other avatars of popular culture, can be said to reveal the inhuman, machinic essence of subjectivity. The etiology of algorithms, mathemes, and other formulae and diagrams in Lacan’s oeuvre has been under-studied, in part because for some readers they are not as attractive as his more bravura flourishes of word play as exegetical excess, and in part because they derive largely from the ‘hard’ structuralist moment of his work in the 1950s, largely eclipsed in Lacan studies by interests in the ‘Late Lacan’ period of the Sinthome, the knots, jouissance and the semblant. Here I extend (and refine) arguments I began in Does the Internet Have An Unconscious, determining that algorithms in Lacanian theory help us understand the split subjectivity of internet discourse.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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