American Dude Ranch: A Touch of the Cowboy and the Thrill of the West. By Lynn Downey
Bibliographic record
Abstract
Dude ranches in America have been growing in popularity for decades. Drawn by mountain or desert settings, fresh air, and a variety of outdoor activities, hundreds of thousands of tourists every year decide to vacation at dude ranches across the West. The history of such vacation destinations is the subject of author Lynn Downey’s new book American Dude Ranch: A Touch of the Cowboy and the Thrill of the West. Downey takes readers where it all began, the first recorded dude ranch in Medora, North Dakota, in 1881, and introduces us to the influence of dude ranches on Western tourism, fashion, film, and television. The book includes discussions about destinations in Montana, Wyoming, Colorado, and Arizona and notes the special features and activities offered to guests at each ranch. Throughout the book, Downey explains how deeply connected dude ranches are to the history and culture of the American West. What began as a novel experience for wealthy Eastern city dwellers became a new industry, and as the twentieth century progressed the dude ranch became a gateway of sorts to preserving the mythology of the frontier and the figure of the cowboy. As she traces this history, Downey explores the myriad ways dude ranches adapted to offer this experience to a new generation of clientele.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".