Bibliographic record
Abstract
This novel is an account of the lives of a small-town Pennsylvania family, the Kaminskis: a mother, Helen, and her three children, Noah, Steve, and Jamie.It tells two connected storiesone about a mayoral election, and one about Helen's cancer diagnosis.Helen is the chief of staff (and longtime mistress) of the outgoing mayor; she has also been recruited to help the mayor's daughter win the office he is about to vacate.The affair has been well-concealed, but has also led Helen to make dubious political choices during her tenure.Now, she must reckon with the consequences of her own missteps on the younger woman's campaign.On a smaller scale, the novel is about how the people in Helen's life respond to her terminal illness.For the Kaminski children, a dying parent is nothing new: their father died of colon cancer 25 years prior.Now grown, they must confront Helen's condition-but, more importantly, the ways in which they never fully dealt with their dad's early death.Jamie is a probate attorney who copes with her latent grief by sleeping with a rotation of clients at her law firm; Steve is eager to be a father himself but cannot move past his wife's miscarriage of their first child; and Noah is a recovering alcoholic who still partway blames his own father for his drinking.Utilizing a rotating third-person narrator, the novel chronicles the past quarter decade in these characters' lives, and makes a few best-guesses for their futures.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.098 | 0.039 |
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".