From Very Small to Not Quite So Small: Voyages in Small Sailing Boats
Bibliographic record
Abstract
The title for this review essay might also be the prayer uttered by any sailor who has ventured in a small boat beyond the sight of land: "Dear God, be good to me; the sea is so wide and my boat is so small." As they say, there is more than one way to skin a cat, although I cannot for the life of me imagine why anyone would want to do such a thing, and I also have no idea why the saying arose. But it does seem to be appropriate in discussing these three books. They are authored by Frank Dye, the consummate English minimalist who dodges along the shores of North America and the Great Lakes in his sixteen-foot sloop Wanderer, the Irishman, Dermot O'Neill, who ventures forth from Kinsale to satisfy a dream of sailing solo across the Atlantic in his twenty-six-foot sloop Poitn; and the Dutch immigrant, Jerry Heutink, who, after completing the construction of Trillium II, a forty-six foot catamaran, sets off from Penetanguishene, Ontario, to sail the seven seas, identified by Heutink as the Atlantic, the North Sea, the Baltic, the Mediterranean, the Caribbean, the Indian, and the Red Sea"These are three quite different books in many ways, but have in common the theme of sailing and satisfying an underlying dream to venture forth in a small boat to sail the questing sea.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".