Hungry Hearts: An Appreciation of the Short Stories of Delia De Santis in the Collection Fast Forward and Other Stories
Bibliographic record
Abstract
When she was thirteen, Delia De Santis and her family immigrated to Canada from Ciociaria in the Italian region of Lazio.I Ciociari (or The Ciociari), as the inhabitants are known, number among them famous figures such as the Roman orator, Marcus Tullius Cicero, the legendary film director, Vittorio De Sica and film star Marcello Mastroiani.The beautiful vistas of the mountain town of Picinisco inspired D.H. Lawrence to begin writing his novel, The Lost Girl, which he set in the town.Just as D.H. Lawrence was inspired by a foreign landscape, De Santis immediately fell in love with the equally compelling attractions of her new hometown, such as the Sarnia Library, where she spent happy solitary hours immersed in its collection and the worlds of wonder they offered her, exploring the literary landscapes of Italo Calvino and Alice Munro who became two of her favorite authors.However, necessity preceded any literary ambitions for the young woman who explored the diverse careers that hard-work and training offered, beginning as a beautician, then marrying and starting a hobby farm, living from the land and raising her two sons.Despite the many responsibilities of being a mother and farmer, she nevertheless found the time and discipline to finally pursue her childhood dream of writing short stories.Eventually, she and her husband formed a construction company building high-end residential homes, a demanding partnership which left her little time for her literary passion.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".