Bibliographic record
Abstract
Beloved Nature Writer Robert Finch spent greater part of a decade traveling around island of Newfoundland, at the edge of North America. In these evocative sketches, stories, and essays, he explores people, geography, and wildlife of a remote and lovely, but often dangerously inhospitable place. Between icy cliffs and Atlantic Ocean, lush valleys and barren drifts, he collects intimate stories of birds and moose and foxes--and of people who share their space. He evokes a landscape of raw beauty in detailed essays that ebb and flow as we make journey with him, straining to hear waves. But while Newfoundland may be a place of unparalleled beauty, its citizens face serious economic hardships, with fishing industry withered and very little industry to replace it. Finch often steps aside, allowing Newfoundlanders' to tell their stories in their own voices, and allows us to her cadence and movement of individuals and their tales. A wide array of characters--fishermen, hunters, and hitchhikers, newcomers and oldtimers--bring to life an island tucked between provinces, languages, and cultures, a land of ancient hardship and stirring beauty.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".