Cultivating Commerce: Cultures of Botany in Britain and France, 1760‐1815. By SarahEasterby‐Smith. Cambridge: Cambridge University Press. 2018. xiv + 239 p. 17 b. and w. illus. £75 (hb). ISBN 978‐1‐107‐12684‐8.
Bibliographic record
Abstract
book-writing machine that can spit out text with much human input.In the Adventures of an Author (1767) similar machines are cynically contrived to produce indexes and reviews. What Drury'sNovel Machines shows brilliantly is that these satires are only a very small sample of the eighteenth-century attitudes towards machines.A broader one must account for all the ways in which coaches, clocks and instruments were tolerated, accepted and even celebrated.At the furthest horizon of Drury's argument is the claim that machines may even have been admired most in the hybrid formations that saw them entangled with human nature and its representation.His case in point here is novels themselves.Drury shows fictions hailed as things that move us forward, slow us down, invite improvement and account for the necessity of certain feelings and desires running their course.On all these counts they can be understood as being like the machines that were viewed positively in the period.This case works cleverly because Drury toggles between reading quite closely the representations of machines in novels (for instance, the coaches in Tristram Shandy) and a general sense that some of the more affirmative readers of novels were those who saw them mechanically, or allowed them to understand their own natures mechanically.Take Drury's innovative reading of Haywood's Love in Excess.Here he up-ends the standard idea that machines were seen primarily as disciplinary instruments, designed to bring bodies to order.His reading of Haywood tracks instead the kind of passions that she legitimates as mechanical.This is clever, counter-intuitive stuff: enough to make us question much that we've been taught as humanists about where freedom was first imagined.Theoretically, Drury aligns himself at certain points with Bruno Latour, the most influential newcomer to these old conversations about the human-machine relationship.Perhaps the kinship is obvious: like Latour, Drury wants to contest the idea that people and things were ever best understood in opposition.Like Latour, he shows that many of our most precious kinds of human experience (such as fiction) see us entangled deeply with the material world.But there is also an argument with Latour that Drury circumvents, one that would have made the theoretical stakes of Novel Machines clearer.Latour argues that our sense of modernity has arisen from a false belief that we transcend the material and control the mechanical.Drury shows that this has not been the case.The intellectual history he offers is one of writers from all ends of the political spectrum embracing the idea of the machine.If Drury is right, then Latour must on this count be wrong.Drury's own method is conscientious and historically grounded.He's gone out of his way to follow up every extra eighteenth-century lead he could, and Novel Machines is an exemplary guide to much primary material from the period.But for this reason alone it would be good to know more about what an innovative history such as this one might have to say to the arguments of critics including Latour, Donna Haraway and Joanna Zylinska, which assume that we have never been comfortable with human-technology hybrids: that we were human before we become post-human.Drury's work helps reverse their assumptions, and it does so with the kind of modest wisdom that makes literary historians the unsung heroes in keeping larger debates about what modernity was or wasn't on track.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".