Bibliographic record
Abstract
a no t e o n f ranklin searche sThe period of 165 years covered in this book begins in 1849 -the year that the first major search for Franklin launched by the Royal Navy returned home having found no trace of Franklin or his ships.It's then that we can begin to speak of a Franklin "mystery" -then that the key elements that have made this story so fascinating for so long -hope, disappointment, and speculation -first came together.From then until 1859, the search for Franklin's ships and men encompassed -following the criteria of W. Gillies Ross -roughly three dozen organized efforts.Of the other searches in this period, though, only two brought back significant Inuit testimony as well as physical relics, those of Dr John Rae and Sir Francis Leopold McClintock; no other searches of that era, however significant in terms of the areas they charted and traversed, added to what was known about Franklin's fate.It's no slight to them -their efforts were no less important -but in retelling the story of the Franklin search, my goal has been to focus on the discoveries of those searchers whose work has contributed to the reconstruction of the movements of Franklin's men and ships, up to and including the discovery of hms Erebus in 2014. a no t e o n usage and spe ll ingThis book draws on a wide array of historical sources; as a rule, when quoting from printed or manuscript materials, I have reproduced their original spelling.The word "Eskimo," and its earlier variant "Esquimaux," is given in such sources, though its use is considered pejorative today; in my own
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.577 | 0.455 |
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".