Bibliographic record
Abstract
‘Diluted manifesto’ is the result of a collaborative, constraint based writing project. The three authors tasked themselves to write three separate yet related pieces, of 300 words, 600 words, and 1,200 words in which they were to propose two contradictory ideas followed by a declaration of a third position which is the ‘becoming’ of the first two. The writing process was overseen by Walt Whitman and Roland Barthes, amongst others. Do I contradict myself? Very well, then I contradict myself, I am large, I contain multitudes. A contrast between the Neutral and the tiresome pressure to take a position on questions that are admittedly important. The nine sections were then assembled in an alternating form determined by a chance process in order to generate a collective and multiple enunciation. This structure partly echoes John Cage’s composition Inlets, and the idea of a piece “settling down,” or moving from short to long sections. Like Inlets, the live reading of the piece (by the authors at Performing Publics - the Performance Studies international conference in Toronto in June 2010) was interrupted with a long sustained drone just past the centre point. It ended with the recorded voice of ‘Hoover the Talking Seal’.
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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.022 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".