Bibliographic record
Abstract
In an epoch driven by hyper-consumption and marvelously destructive futility, and in the context of a hegemonic utilitarianism where one goes to university to work rather than to “develop a meaningful philosophy of life,” the concept of the useful is perhaps one most in need of interrogation. Taunting the Useful seeks to unsettle notions of usefulness and uselessness, not merely by deconstructing these terms, but by sidetracking them. It doesn’t reverse things by saying that what is useless is useful. Rather, taunting is teasing, heckling, tickling, scratching the useful. By elaborating a notion of the “virtual useless,” Taunting the Useful seeks to tease the dimensions of wonder, use, and play, through modalities, contingencies, and potentialities of the useless-useful. An experimental book, it (un)does what it tells, and is as much an object taunting and taunted as it is a description of taunting the useful. Includes bonus chapters!
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 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".