Stealing Lives, Borrowing Voices: Inventing a Secret Life for \nKatherine Mansfield in Sudden Flight. Extract from Sudden Flight and \nCritical Commentary
Bibliographic record
Abstract
My novel, Sudden Flight, envisages an alternative telling for the last few months in the life of the New Zealand modernist writer Katherine Mansfield, closely based on fact, narrated by an imaginary protagonist, the Canadian doctor Charles Jermyn with whom she has had a brief passionate affair during the war in Paris, who unexpectedly re-enters her life. A fable-like blend of historical fiction, life-writing and biographical fiction, the novel straddles several literary subgenres with different methodologies, critical traditions and literary standing; in this critical commentary I contextualize the approach and methodology I used in identifying, describing and weighing up those differences. I analyse how I attempted to meet the challenge of doing biographical justice to my subject, well aware that I would be venturing into territory already heavily mined by Mansfield scholars and biographers, as well a number of novelists, while at the same time constructing a speculative fictional life for her, one deliberately at odds with the version of events presented by Mansfield’s husband John Middleton Murry. \n \nThis commentary is an exploration of the problematic —even controversial — ethical and methodological challenges facing a writer combining real and fictional characters, set within the critical context of biographical and historical scholarship. In particular, I question by what paradox biofiction can promise to satisfy particular curiosities about gaps in the record about the life of a real person while also asking readers to suspend disbelief and trust in its facsimile reality, and ask by what criteria successful biofiction can (and should) be judged.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".