Bibliographic record
Abstract
Featured in this issue: Fiction New short stories, 'Downstream the Water Darkens' by David Frankel and 'A Question of Desire' by Michael Humfrey. Poetry From a range of poets including Suad Ali, Emily Bilman, John F. Deane, Pavol Janik, Yahia Lababidi, and Patricia McCarthy. Essays Peter Abbs, the Emeritus Professor of Creative Writing at Sussex University on William Blake and the Forging of the Self. Suzi Feay, the former Literary Editor of the Independent writes on her experience of re-reading the novels of Leon Garfield after enjoying them as a child. Edward Lucie-Smith's fascinating research into his family ancestry and on being a child of World War I. Holly Luhning, a young Canadian novelist describes what London means to her in the sixth of the 'My London' series. Jeffrey Meyers identifies the man who raped Sylvia Plath. Tony Roberts on Edmund Wilson and Sir Isaiah Berlin. Reviews Belinda Cooke reviews recent poetry collections: Roisin Tierney's The Spanish-Italian Border, Ciaran Berry's The Dead Zoo and Derek Mahon's Echo's Grove: Collected Translations. Geoffrey Heptonstall reviews new poetry collections by John Burnside and Toby Martinez de las Rivas Terry Kelly on Hugo William's career as well as his latest poetry collection: I Knew the Bride Steven Matthews on August Kleinzahler and Frederick Seidel Derwent May on How to Open an Art Gallery Michael Thomas on two books on the Great War by Margaret MacMillan and Pete Ayrton
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.187 | 0.083 |
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".