Bibliographic record
Abstract
The inspiration for this volume of essays, drawn from the pro-ceedings of the Nietz sche Workshop @ Western (held at West-ern University, London on, and the Center for Transformative Media at The New School, New York ny),1 comes from the hy-pothesis that Nietz sche’s thinking is pertinent to a phenomenon which can be described as the planetary propensity toward the digitization and networking of information. Moreover, “Nietz-sche-Thought” — to lift a phrase from philosopher François Laruelle2 — provides unique insights about the complexities of our contemporary network-centric condition, especially in relation to the all-important notion of “information,” which has been conceptualized primarily in terms that are protoco-logical and computational, hence almost exclusively Apollonian(or as Gilles Deleuze and Félix Guattari would say, “striated”), rather than Dionysian (or as Deleuze and Guattari would say, “smooth”) terms. As Manav Guha argues in his contribution to this volume, the current military understanding of net-centric-ity is “a project of extreme striation involving the harnessing of Dionysian energies of the yet-to-be-processed with the Apollon-ian reigns of the processor.”
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".