Winslow Homer: artist and angler
Bibliographic record
Abstract
This volume and the exhibition it accompanies look closely at Winslow Homer's avid pursuit of fly-fishing and the inspiration that the sport provided for his art. It was fishing that led the eminent painter to three of the locales with which we now associate his name: the Adirondack in northern New York State; Florida; and Quebec. Each of these distinctive regions elicited unique and strong reactions from the painter that took form in works that are brilliant studies of light, atmosphere and the spirit of place. At his favourite fishing spots, Homer worked in the traveller's medium of watercolour, stretching it ever more boldly and unconventionally in order to convey the intensity of his experience of nature, his response to light and atmosphere peculiar to a given region, a specific season and a particular time of day; and his feeling for the physical and psychological demands of his favourite sport. Homer's fly-fishing paintings are an immensely varied and little understood aspect of his art. They serve as a counterpoint to all his other work, especially in the 1880s and beyond when fly-fishing represented a regular and sustained activity for the artist. Homer's fishing watercolours suggested to him new subject matter, inspiring or at least intensifying, for instance, his interest in commercial fishing and in the lives of the men and women who live by the sea. And his fishing expeditions offered recreation, rejuvenation, solace and camaraderie, which spurred his imagination.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.384 | 0.175 |
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".