The Uses of Travel: Science, Empire and Change in 18th‐Century Travel Writing
Bibliographic record
Abstract
Abstract This essay surveys recent critical approaches to 18th‐century travel writing, with an emphasis on a seeming contradiction in the way the field treats the possibility that the traveller might be changed by the experience of travel. On the one hand, the traveller's vulnerability to external influence seems to represent a threat to British imperial authority, particularly in studies of scientific travel in the service of empire – but on the other hand, recent studies on the novel's debts to travel writing insist that the traveller's capacity to change is fundamental to any argument for travel's edifying potential or contribution to civic improvement. To resolve this divide, this article will argue that reading 18th‐century travel writing for the moments in which the ‘changeable’ traveller appears in a positive light might help to open new avenues of research on the form and function of change in 18th‐century records of scientific observation. Looking ahead, this essay proposes that future studies in scientific travel might draw inspiration from recent research on sympathetic travellers as agents of empire, and continue to investigate how the traveller's capacity for change could add nuance to our history of the scientific observer as – in Captain Cook's terms – a ‘disinterested’ “eyewitness to a fact.”
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.040 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".