Bibliographic record
Abstract
How might one read a collection of transcriptions—such as The Beast and the Sovereign, Volume 1—that exemplifies how to read other texts deconstructively? In the spirit of Derrida’s text, a response to this question remains radically undecided; however, it certainly does not imply the absence of exegesis through the course of a particular reading. On the contrary, the event of a reading fixes itself out of specific interpretative horizons and traces of past understandings. In what follows, my exegesis is contoured by past readings that have engaged diverse phenomenological and existential perspectives declining commonsense invitations to relay fixed, singular meanings that align with the purportedly real meanings and/or intentions of the author. Following a partial suspension of that familiar angle, I propose an epoche of sorts. Provoked by Derrida’s text, I shall reorder words into new assemblies that appear on the following pages, and that surface from my situated readings of Derrida’s deconstructive renderings of other writings.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.062 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".