Yearning, Frustration, and Fulfillment: The Return Story in Olive Kitteridge and Kissing in Manhattan
Bibliographic record
Abstract
Cet article explore le rôle du lecteur dans le cycle de nouvelles, en se concentrant sur ce que Gerald Lynch nomme « le récit de retour ». Y sont exploités les récits de retour d’Olive Kitteridge d’Elizabeth Strout et Kissing in Manhattan de David Schickler afin d’expliquer l’importance de ces récits pour la structure des cycles. S’inspirant d’éléments de narratologie cognitive ainsi que des théories de Wolfgang Iser sur l’implication du lecteur dans le texte, cet article étudie le rôle de l’absence dans ces deux cycles. L’emploi d’absences à motifs tout au long d’Olive Kitteridge et Kissing in Manhattan amène à une reconsidération du texte dans son ensemble dans le récit de retour. Cette analyse montre dans quelle mesure l’absence forme un élément structurel décisif du cycle de nouvelles contemporain.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.042 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".