Peter Mancall interview, "Fatal Journey: The Final Expedition of Henry Hudson"
Bibliographic record
Abstract
You've probably heard of the Hudson River, and you may have even heard of Hudson Bay. But have you ever heard of Henry Hudson. Well you should, and now thanks to Peter Mancall's page-turning Fatal Journey: The Final Expedition of Henry Hudson (Basic Books, 2009) you can. And very pleasurably at that. Hudson was an explorer. He was looking for fame and fortune, both of which happened to be located in what Europeans called the "South Sea," that is, the Pacific Ocean. For there were found the Spice Islands on which could be found (you guessed it) spices. These spices were incredibly valuable. A boatload of spices was worth a boatload of cash. Hudson knew it, and so did everyone else. The problem was it was hard to get there, particularly from England. One had to sail around Africa, and that was no easy trick. So Hudson set about looking for a Northeast (above Russia) and Northwest (above Canada) passage. In point of fact the former exists, though only modern icebreakers (often nuclear powered) can get through it, and the latter doesn't exist at all. Hudson didn't know that. He had bad maps. So he tried, four times actually, to make it through. On the fourth voyage everything in the Far North went south, so to say. Cold, hunger, mutiny, murder. Peter tells the whole gripping tale, and very well. I'm hoping the book will be made into a movie. I'm thinking Russell Crowe (obviously) for Hudson.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.076 | 0.017 |
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".