Bibliographic record
Abstract
When British doctor Wilfred Grenfell arrived in Newfoundland in 1892 to provide medical service to migrant fisherman, he had no clear sense of who his patients were or how they lived - a few weeks on the Labrador coast changed that. Struck by both the rugged beauty of the place and the difficulties faced by those who lived there, Grenfell devoted the rest of his life to improving theirs. At first an evangelical missionary of the Royal National Mission to Deep Sea Fisherman, Grenfell became part of philanthropic movements on both sides of the Atlantic. Raising funds in Canada and the United States, he founded a network of hospitals, nursing stations, schools, and home industries that exists in a modified form to this day. In 1908, the story of his survival after a night marooned on a drifting patch of ice transformed him into a popular hero. He eventually became one of the most successful lecturers of his time. Ronald Rompkey tells the story of Grenfell's education, his Anglo-Saxonism, and his devotion to broader issues of hygiene and public health. Above all, Rompkey shows that Grenfell went beyond being a doctor or a missionary to become a cultural politician who intervened in a colonial culture. Grenfell of Labrador provides a vivid picture of the man himself and the social movements through which he worked.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.287 | 0.095 |
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".