The writer and the holy fool
Bibliographic record
Abstract
The exegesis focuses on the writer’s process of writing The Book of Gesuino, a novel of 165,000 words, whose protagonist develops aspects of the persona of a holy fool. The exegesis explores the historical development of the archetype of the holy fool in the hagiographies of early Christian saints, such as Saint Symeon of Emesa, and the development of the holy fool in the Eastern Orthodox tradition and secular variants in Western literature, as well as the adaptation of the Jesus narrative within Denys Arcand’s film Jesus of Montreal. \nThe difficulties inherent in writing a modern novel containing a holy fool as a central character are explored in light of approaches taken in two recent Russia texts, Svetlana Vasilenko’s novella, ‘Little Fool’ and Eugene Vodolazkin’s novel, Laurus. The writer also examines the historical research that informed the novel, with the Kingdom of Naples during the seventeenth century as its setting, including research regarding the historical presence and veneration of ascetic saints within Southern Italy and the repositioning of the holy fool within the era within which the novel is set. The writer does so with reference to Pier Paolo Pasolini’s The Gospel According to Matthew and his use of the Southern Italian landscape as the setting for his biblical epic. The writer uses the approach of personal essay to explore personal influences in writing the text, including oral storytelling.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".