Kingbird Highway: The Story of a Natural Obsession that Got a Little Out of Hand, by Kenn Kaufman [Review]
Bibliographic record
Abstract
The gestation period of a book is said to be longer than that of an elephant (up to 22 months).This book is another example; he wrote the first draft in 1975, resurrected it in 1990, obtained help from skilful editors, and finally published the hard-cover edition in 1997.Three years later it was re-issued as an inexpensive paperback, the subject of this review.Keen birders recognize Kaufman as one of the top authorities on bird identification.The first six chapters of Kingbird Highway tell how he got his start.In 1973, after completing high school in Wichita, Kansas, Kaufman determined that he would set a new North American record for the number of bird species seen in a year.Guy Emerson of the National Audubon Society had been the first; he identified 497 species in 1939, followed by Bob Smart with 510 species in 1952, Roger Tory Peterson (accompanied much of the way by James Fisher) with 572 in 1953, Stuart Keith with 598 in 1956, and Ted Parker with 626 in 1971.Kaufman determined to spend 1973 surpassing the Parker record; this quest occupies the last 20 chapters.To run up a large total for the United States and Canada, Kaufman had, like his predecessors, to crisscross North America from California to the Florida Keys, to Gambell Island off the western coast of Alaska.Unlike his predecessors, he made his trips by hitch-hiking.The previous year, 1972, had seen Richard Stallcup edge out Richard Webster, for the largest California-only list, 428 species to 427.Kaufman was aiming higher, for a United States and Canada list of 635 or 640.By 26 January he had ticked off his 200" species for the year, somewhat ahead of his expectations.Yet he was somewhat non-plussed two days later in Portsmouth, New Hampshire, to meet Floyd Murdoch, on an identical quest.Murdoch was researching the history of the National Wildlife Refuges, and in visiting each was certain to gain a large list.Now Kaufman had a competitor, not merely a number to surpass.Some destinations were for a specific purpose, such as San Juan island off the Washington coast, to see the Skylark.From there he went back to the Florida Keys.Who should be with him on a boat trip to the Dry Tortugas but Floyd Murdoch, whose year list by then was about 50 species behind Kaufman's 440.Kaufman shares with us the travails of hitchhiking, including days without food and being wet for several days in succession.He travelled light, but met some of the keenest birders on the continent, including Ted Parker and the author-artist, Roger Tory Peterson, guest speaker at the first-ever convention of the newly formed American Birding Association in Kenmare, North Dakota in June.Kaufman's year-to-date tally was 575.He then that Got a Little Out of Hand, by Kenn Kaufman [Review]."The Canadian
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".