Fostering a new industry in the Industrial Revolution: Boulton & Watt and gaslight 1800–1812
Bibliographic record
Abstract
Abstract Gaslight emerged as a new industry after 1800 in Britain, but not in other countries in Europe where the technology existed as well. Among the many groups trying, it was only the firm of Boulton & Watt that succeeded in commercializing the invention for two important reasons. The first was that they possessed skills and experience related to ironworking and to making scientific instruments, both of which they used as they developed gaslight apparatus. This development involved an extensive series of experiments that ultimately had its root in James Watt's own work with pneumatic chemistry. The second reason was that they possessed many resources such as access to capital, their existing network of industrial customers, and their abilities to publicize their work. As with the steam engine, the firm proved adept at advertising. Boulton & Watt did not give their full attention to gaslight except in two spurts between 1805 and 1809, and by around 1812 they had lost almost all interest in the technology. By this time, however, they had solved many problems associated with scaling up gaslight apparatus for industrial use, they had trained many people who would go on to do further important work in the early years of the industry, and they had drawn extensive public attention to the new invention. Finally, their advertising involved elevating the status of William Murdoch as an inventor while minimizing the role of the firm.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".