Bibliographic record
Abstract
In letters to The Naval Chronicle (1813) Penrose expressed his confidence that seamen were becoming more than just nominal Christians, and that some would become ‘powerful engines for the dissemination of knowledge and truth’ and play a part in the worldwide spread of Christianity. Penrose imagined the navy’s task as something more sublime than national interest alone – but was this high-minded aspiration shared by the rest of his profession? We shall ask whether the navy can fairly claim to have disseminated knowledge to mankind – through exploration and scientific enquiry – and how the process interacted with faith and piety. Exploration and the Blue Lights The science of navigation rested on astronomical assumptions of predictable order: the cosmos worked (it was generally supposed) because it had a Designer both wise and beneficent, and mankind had been given reason so that the laws through which God governed the universe might be discerned and marvelled at. Investigation in this spirit was in essence worship. It attracted committed believers, like Matthew Maury (1806–73), the American ‘pathfinder of the seas’ whose doctrine of ocean currents grew from his belief in the coherence of the Creator’s ways and works. Science, the pursuit of truth, a cause higher than national pride or commercial gain, for the glory of God and the benefit of humanity, invited evangelical engagement. Blue Lights prominent in survey and polar exploration might have believed they were engaged in the work of God, but would such a mindset prove an enabler or a handicap in polar regions? Even nineteenth-century critics alleged that the Admiralty’s concept of ship-borne Arctic expeditions was flawed: they were more exposed to hazard than small lightly-equipped teams that could cover great distances more rapidly and securely by copying Inuit ways and hunting for their food. More recent writers have laid an additional charge of cultural arrogance, suggesting that naval personnel were ideologically resistant to learning from native peoples, and suffered for it. Evidence might begin with a semi-comic drawing by JohnSackhouse (or Secheuse) of a particular occasion in 1818 when John Ross and Parry, dressed in ceremonial uniform that began with cocked hats and ended with buckled leather shoes, stepped onto the ice to greet sensibly fur-clad Greenland Inuit.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.087 | 0.031 |
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".