The Girl No One Knew: Photographs, Narratives, and Secrets in Modern Fiction
Bibliographic record
Abstract
The research field is the intersection between photography and modern fiction. The research, which resulted in a published paper, an international conference presentation (‘The Photograph’, University of Manitoba) public symposium paper (‘Out of the Box’, Tate Modern) and scholarly symposium paper (Leeds Humanities Research Institute) analysed works of modern fiction in which textual descriptions of photographs are used to structure narratives. Particular attention is given to Penelope Lively’s 'The Photograph'. It is argued that an incriminating photograph discovered by chance at the start of the narrative comes to dominates the novel and that the narrative is predicated on the main character (depicted in the photograph) finally becoming reincorporated into the lives of the other characters. Theoretically two themes prevail in the research. First (based on Kermode), that secrets within literature are not always hidden. Second (based on Bakhtin) that photographs might function as ‘organising centres’ for the fundamental narrative events of a novel so that a small detail (the clandestine linked hands described by Lively) might act as a vanishing point (or chronotype) through which all of what happens in the novel can be traced back. The argument is made that The Photograph is a fictional world holding photographs, narratives and secrets in a tight, mutually dependent dynamic. Reference was also made to writers who also used photographs in ways similar to Lively such as Carol Shields, Donna Tartt and Kate Atkinson. As the symposium at Leeds the works of other writers were drawn into the presentation including Peter Dickinson and Nina Raine.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.036 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".