Remapping Melville’s Liverpool: Reading Redburn in Malcolm Lowry’s In Ballast to the White Sea
Bibliographic record
Abstract
Melville was an important influence on the British-Canadian writer Malcolm Lowry, best known for his novel Under the Volcano (1947). Lowry’s letters reveal both his fascination with Melville, and his anxious attempts to obscure his knowledge of Melville’s works, fuelled by fears of being thought a plagiarist. Lowry’s novel In Ballast to the White Sea (1934–36)— thought lost during his lifetime, but now recovered and published—draws particularly on Redburn (1849), despite Lowry’s claims not to have read the book. Lowry’s use of Redburn to examine father-son relations, to chart the fate of the individual in an increasingly globalised world, and to construct the Liverpool setting shared by the two texts suggests that he was, indeed, familiar with the novel. More importantly, Lowry understood Melville as a theorist of modernity’s impact on time and place, anticipating twenty-first century readings of Redburn. Approaching Redburn through In Ballast reveals the interplay between real and imagined space in Melville’s depiction of Liverpool, and his efforts to understand and represent heterotopia. Recovering In Ballast and its debt to Melville, therefore, also recovers Lowry as an original and astute reader of Melville, and repositions Redburn as an experimental fiction.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".