The Sentimentalist: Science and Nature in the Writing of H.U. Green, a.k.a. Tony Lascelles
Bibliographic record
Abstract
H.U. Green was a Royal Canadian Mounted Police officer and, as Tony Lascelles, an occasional nature writer when he met Grey Owl in 1931. Together they penned A Philosophy of the Wild, the only collaborative work either would ever write, and Green's career as a nature writer blossomed. Green's unique background soon landed him a job at Banff National Park as special warden, a sort of naturalist-in-residence. As his naturalist career was reaching its height, he dropped the Lascelles persona forever and sought instead to become accepted, as H.U. Green, for his scientific work. His lack of formal scientific training meant that he was moving against the tide of federal wildlife management, however, and he became embattled in the late 1940s with the scientists of the new Canadian Wildlife Service. The literary career of H.U. Green traces the ascending role of
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.022 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".