Bibliographic record
Abstract
The global financial crisis beginning in 2008 has encouraged the revitalization of a wide spectrum of leftist theorizing, but arguably the most audacious is that of ‘accelerationism’. Left-accelerationism sees the intensification of certain tendencies in late capitalist society as a way to escape its gravitational orbit and ‘repurpose’ the very material infrastructure of capitalism itself, to universally emancipatory ends. The central task here is to engage accelerationism with a thinker of the post-Autonomist tradition, Franco ‘Bifo’ Berardi. Contrary to Williams and Srnicek, co-authors of the #Accelerate manifesto, Bifo asserts that acceleration per se only augments the power and dynamism of capital, and posits instead a ‘post-politics’ of ironic detachment, aesthetic cultivation, and ‘therapy’. Contrasting Bifo and accelerationism clarifies each of their assumptions and core arguments, and points the way to a more nuanced perspective on these issues, in a contemporaneous moment marked in equal measure by inestimable threat and liberatory promise.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".