Bibliographic record
Abstract
2016 World Book Night collaborative book and video. Our set book this year was chosen by the artist John Bently, who also wrote and performed a tribute ‘sermon’ on the night. Forty artists read 'The Handmaid’s Tale' by Margaret Atwood, and then designed rubber stamp artwork for us to print as the 'Serena Joy' artist’s book/folio. 43 rubber stamps were sent in to us from: Denmark, France, Germany, Norway, Poland, Sweden and all over the UK. \nSixteen of us travelled to Halifax, where we printed the 43 artworks, each in an edition of 50 and assembled them into ‘Serena Joy’ boxes and made a short film in the evening. \nThe stampers present were: Helen Allsebrook, Janet Allsebrook, Mette-Sofie D. Ambeck, John Bently, Kate Bernstein, Sarah Bodman, Angie Butler, Si Butler, Nancy Campbell, Jeremy Dixon, Stephen Fowler, Mike Nicholson, Kathy Round, Gwen Simpson, Simon Smith and Linda Williams. A full ist of contributors and their artworks can be viewed at: http://www.bookarts.uwe.ac.uk/events/wbn2016.html
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.568 | 0.318 |
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".