Bibliographic record
Abstract
novel does not attempt to solve the controversy over who first reached the North Pole. This warning is not contained in an epigraph, but comes at the end of the novel: This is a work of fiction. At times, it places real people in imaginary space and time. At others, imaginary people in real space and time. While it draws from the historical record, its purpose is not to answer historical questions or settle historical controver-sies (484). While the purpose of Johnston’s text was “not to answer historical questions, ” the lure of that possibility was most appealing. There is a play between historiography, fiction, and the writing of “contemporary ” history in parallel with the writing of the novel itself. In its chiasmic structure, Johnston’s note seems to urge the reader to re-think the novel she or he has just finished, and like many of his novels it encourages a reading in terms of the fluidity of boundaries between history and fiction. At a first glance, the title of the book, The Navigator of New York, could appear opportunis-tic. The protagonist comes from Newfoundland and goes into self-imposed exile in New York. Devlin, the narrator, writes: “There I was in Manhattan, and all I could think about was Newfoundland ” (Johnston 52). Johnston might have been speak-ing for himself. “New York ” in the title may serve to attract international readers and the protagonist of the novel is not “of ” New York. But one learns, in the course of the story, that the narrator was conceived in New York and “navigated ” in his
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 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".