Bibliographic record
Abstract
My purpose in this final chapter is twofold: on one hand, to discuss critically the academic left’s fantasy of the communist revolution in order to argue that it discourages revolutionary action rather than stimulating it. This discussion is relevant to the extent that academic discourses interact with and influence anti-capitalist political acts outside the academe. And on the other hand, to contribute to the on-going discussion of anti-capitalist tactics based on awareness raising, on protestor, which amounts to almost the same, on pointing out the adversary’s shortcomings, of which the occupation of public spaces is a recent example. This discussion aims to question the implicit attachment that these ‘politics of spectacle’ have to the figure of fatherly authority and to the political-libidinal framework imposed by liberal-capitalism. Both discussions connect anti-bourgeois politics with the theme of a population profoundly devoted to its framework of jouissance, in this case to liberal-capitalism, and with the hypothesis, introduced in the previous chapter, that the task of anti-bourgeois politics is to ‘turn its back’ on this framework that serves so well the adversary’s goals and to develop tactics and strategies that do not need to recognition or support of the master’s gaze in order to function. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".