Conflicting Narratives In and Out of the Archive: Anthony Burgess and the Italian Blooms of Dublin
Bibliographic record
Abstract
Drawing on a variety of archival sources, this paper aims to explore the dissonant and conflicting narratives that emerge from the surviving drafts of the Italian translation of Blooms of Dublin, a musical adaptation of James Joyce’s Ulysses by Anthony Burgess (1986). I will investigate the genesis of this translation and the way it unfolds in the rich archival records held at the Anthony Burgess Foundation Archives, the Harry Ransom Center, and the Archives of Teatro Verdi in Trieste. By examining the surviving archival traces of this collaborative venture—an unfinished translation project that can be detected only in the archive—, the study aims not only to reconstruct the working methods that were adopted for this translation project, but also to lay the groundwork for further explorations into Burgess’s approach to translation. In exploring the conflicting narratives that emerge in and out of the archive, this paper will attempt to provide some new insights into the dynamics that underlie collaborative (self-)translation (Hersant, 2017, 2020; Manterola Agirrezabalaga, 2017; Huss, 2019; Rulyova, 2020; Verhulst et al., 2021) by examining a case of failed collaboration. It will also show the challenges involved in studying translation-related materials that exist in split collections.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.052 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".