Bibliographic record
Abstract
The Book of Revenge in the title is the author's award winning memoir, published by Random House Canada in 2006. As an editor of culture and art sections in several underground magazines in Belgrade in the years leading to and during the war in Yugoslavia, the author was in a unique position to observe and analyse the deep currents in arts and public life that started working with the first shots fired. There are numerous parts strewn throughout the book that deal with the relationship between art and war (this idea is in the very centre of the book). Now, almost two decades after the war, some of the artists mentioned in the book have gone into external or internal exile, some have profited and added to their body of work, and some have disappeared from the scene—all this as a result of their political engagement. This is the core of the performance presented at the Conference ‘I too remember dust’ - Peacebuilding, Politics and the Arts, at the University of Winchester. On the intertextual level the performance was a ritual of reconciliation (the wars had ended, the fog of war was gone, making the narratives clearer and the art involved sharper). The performance was not a chapter added to the original text, but an exploration of the ways the politics interfere with arts and, in return, of the influence arts have on significant social events involving large masses, such as war.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".